Adaptive Candlestick Pattern Recognition System█ INTRODUCTION
Nearly three years in the making, intermittently worked on in the few spare hours of weekends and time off, this is a passion project I undertook to flesh out my skills as a computer programmer. This script currently recognizes 85 different candlestick patterns ranging from one to five candles in length. It also performs statistical analysis on those patterns to determine prior performance and changes the coloration of those patterns based on that performance. In searching TradingView's script library for scripts similar to this one, I had found a handful. However, when I reviewed the ones which were open source, I did not see many that truly captured the power of PineScrypt or leveraged the way it works to create efficient and reliable code; one of the main driving factors for releasing this 5,000+ line behemoth open sourced.
Please take the time to review this description and source code to utilize this script to its fullest potential.
█ CONCEPTS
This script covers the following topics: Candlestick Theory, Trend Direction, Higher Timeframes, Price Analysis, Statistic Analysis, and Code Design.
Candlestick Theory - This script focuses solely on the concept of Candlestick Theory: arrangements of candlesticks may form certain patterns that can potentially influence the future price action of assets which experience those patterns. A full list of patterns (grouped by pattern length) will be in its own section of this description. This script contains two modes of operation for identifying candlestick patterns, 'CLASSIC' and 'BREAKOUT'.
CLASSIC: In this mode, candlestick patterns will be identified whenever they appear. The user has a wide variety of inputs to manipulate that can change how certain patterns are identified and even enable alerts to notify themselves when these patterns appear. Each pattern selected to appear will have their Profit or Loss (P/L) calculated starting from the first candle open succeeding the pattern to a candle close specified some number of candles ahead. These P/L calculations are then collected for each pattern, and split among partitions of prior price action of the asset the script is currently applied to (more on that in Higher Timeframes ).
BREAKOUT: In this mode, P/L calculations are held off until a breakout direction has been confirmed. The user may specify the number of candles ahead of a pattern's appearance (from one to five) that a pattern has to confirm a breakout in either an upward or downward direction. A breakout is constituted when there is a candle following the appearance of the pattern that closes above/at the highest high of the pattern, or below/at its lowest low. Only then will percent return calculations be performed for the pattern that's been identified, and these percent returns are broken up not only by the partition they had appeared in but also by the breakout direction itself. Patterns which do not breakout in either direction will be ignored, along with having their labels deleted.
In both of these modes, patterns may be overridden. Overrides occur when a smaller pattern has been detected and ends up becoming one (or more) of the candles of a larger pattern. A key example of this would be the Bearish Engulfing and the Three Outside Down patterns. A Three Outside Down necessitates a Bearish Engulfing as the first two candles in it, while the third candle closes lower. When a pattern is overridden, the return for that pattern will no longer be tracked. Overrides will not occur if the tail end of a larger pattern occurs at the beginning of a smaller pattern (Ex: a Bullish Engulfing occurs on the third candle of a Three Outside Down and the candle immediately following that pattern, the Three Outside Down pattern will not be overridden).
Important Functionality Note: These patterns are only searched for at the most recently closed candle, not on the currently closing candle, which creates an offset of one for this script's execution. (SEE LIMITATIONS)
Trend Direction - Many of the patterns require a trend direction prior to their appearance. Noting TradingView's own publication of candlestick patterns, I utilize a similar method for determining trend direction. Moving Averages are used to determine which trend is currently taking place for candlestick patterns to be sought out. The user has access to two Moving Averages which they may individually modify the following for each: Moving Average type (list of 9), their length, width, source values, and all variables associated with two special Moving Averages (Least Squares and Arnaud Legoux).
There are 3 settings for these Moving Averages, the first two switch between the two Moving Averages, and the third uses both. When using individual Moving Averages, the user may select a 'price point' to compare against the Moving Average (default is close). This price point is compared to the Moving Average at the candles prior to the appearance of candle patterns. Meaning: The close compared to the Moving Average two candles behind determines the trend direction used for Candlestick Analysis of one candle patterns; three candles behind for two candle patterns and so on. If the selected price point is above the Moving Average, then the current trend is an 'uptrend', 'downtrend' otherwise.
The third setting using both Moving Averages will compare the lengths of each, and trend direction is determined by the shorter Moving Average compared to the longer one. If the shorter Moving Average is above the longer, then the current trend is an 'uptrend', 'downtrend' otherwise. If the lengths of the Moving Averages are the same, or both Moving Averages are Symmetrical, then MA1 will be used by default. (SEE LIMITATIONS)
Higher Timeframes - This script employs the use of Higher Timeframes with a few request.security calls. The purpose of these calls is strictly for the partitioning of an asset's chart, splitting the returns of patterns into three separate groups. The four inputs in control of this partitioning split the chart based on: A given resolution to grab values from, the length of time in that resolution, and 'Upper' and 'Lower Limits' which split the trading range provided by that length of time in that resolution that forms three separate groups. The default values for these four inputs will partition the current chart by the yearly high-low range where: the 'Upper' partition is the top 20% of that trading range, the 'Middle' partition is 80% to 33% of the trading range, and the 'Lower' partition covers the trading range within 33% of the yearly low.
Patterns which are identified by this script will have their returns grouped together based on which partition they had appeared in. For example, a Bullish Engulfing which occurs within a third of the yearly low will have its return placed separately from a Bullish Engulfing that occurred within 20% of the yearly high. The idea is that certain patterns may perform better or worse depending on when they had occurred during an asset's trading range.
Price Analysis - Price Analysis is a major part of this script's functionality as it can fundamentally change how patterns are shown to the user. The settings related to Price Analysis include setting the number of candles ahead of a pattern's appearance to determine the return of that pattern. In 'BREAKOUT' mode, an additional setting allows the user to specify where the P/L calculation will begin for a pattern that had appeared and confirmed. (SEE LIMITATIONS)
The calculation for percent returns of patterns is illustrated with the following pseudo-code (CLASSIC mode, this is a simplified version of the actual code):
type patternObj
int ID
int partition
type returnsArray
float returns
// No pattern found = na returned
patternObj TEST_VAL = f_FindPattern()
priorTestVal = TEST_VAL
if not na( priorTestVal )
pnlMatrixRow = priorTestVal.ID
pnlMatrixCol = priorTestVal.partition
matrixReturn = matrix.get(PERCENT_RETURNS, pnlMatrixRow, pnlMatrixCol)
percentReturn = ( (close - open ) / open ) * 100%
array.push(matrixReturn.returns, percentReturn)
Statistic Analysis - This script uses Pine's built-in array functions to conduct the Statistic Analysis for patterns. When a pattern is found and its P/L calculation is complete, its return is added to a 'Return Array' User-Defined-Type that contains numerous fields which retain information on a pattern's prior performance. The actual UDT is as follows:
type returnArray
float returns = na
int size = 0
float avg = 0
float median = 0
float stdDev = 0
int polarities = na
All values within this UDT will be updated when a return is added to it (some based on user input). The array.avg , array.median and array.stdev will be ran and saved into their respective fields after a return is placed in the 'returns' array. The 'polarities' integer array is what will be changed based on user input. The user specifies two different percentages that declare 'Positive' and 'Negative' returns for patterns. When a pattern returns above, below, or in between these two values, different indices of this array will be incremented to reflect the kind of return that pattern had just experienced.
These values (plus the full name, partition the pattern occurred in, and a 95% confidence interval of expected returns) will be displayed to the user on the tooltip of the labels that identify patterns. Simply scroll over the pattern label to view each of these values.
Code Design - Overall this script is as much of an art piece as it is functional. Its design features numerous depictions of ASCII Art that illustrate what is being attempted by the functions that identify patterns, and an incalculable amount of time was spent rewriting portions of code to improve its efficiency. Admittedly, this final version is nearly 1,000 lines shorter than a previous version (one which took nearly 30 seconds after compilation to run, and didn't do nearly half of what this version does). The use of UDTs, especially the 'patternObj' one crafted and redesigned from the Hikkake Hunter 2.0 I published last month, played a significant role in making this script run efficiently. There is a slight rigidity in some of this code mainly around pattern IDs which are responsible for displaying the abbreviation for patterns (as well as the full names under the tooltips, and the matrix row position for holding returns), as each is hard-coded to correspond to that pattern.
However, one thing I would like to mention is the extensive use of global variables for pattern detection. Many scripts I had looked over for ideas on how to identify candlestick patterns had the same idea; break the pattern into a set of logical 'true/false' statements derived from historically referencing candle OHLC values. Some scripts which identified upwards of 20 to 30 patterns would reference Pine's built-in OHLC values for each pattern individually, potentially requesting information from TradingView's servers numerous times that could easily be saved into a variable for re-use and only requested once per candle (what this script does).
█ FEATURES
This script features a massive amount of switches, options, floating point values, detection settings, and methods for identifying/tailoring pattern appearances. All modifiable inputs for patterns are grouped together based on the number of candles they contain. Other inputs (like those for statistics settings and coloration) are grouped separately and presented in a way I believe makes the most sense.
Not mentioned above is the coloration settings. One of the aims of this script was to make patterns visually signify their behavior to the user when they are identified. Each pattern has its own collection of returns which are analyzed and compared to the inputs of the user. The user may choose the colors for bullish, neutral, and bearish patterns. They may also choose the minimum number of patterns needed to occur before assigning a color to that pattern based on its behavior; a color for patterns that have not met this minimum number of occurrences yet, and a color for patterns that are still processing in BREAKOUT mode.
There are also an additional three settings which alter the color scheme for patterns: Statistic Point-of-Reference, Adaptive coloring, and Hard Limiting. The Statistic Point-of-Reference decides which value (average or median) will be compared against the 'Negative' and 'Positive Return Tolerance'(s) to guide the coloration of the patterns (or for Adaptive Coloring, the generation of a color gradient).
Adaptive Coloring will have this script produce a gradient that patterns will be colored along. The more bullish or bearish a pattern is, the further along the gradient those patterns will be colored starting from the 'Neutral' color (hard lined at the value of 0%: values above this will be colored bullish, bearish otherwise). When Adaptive Coloring is enabled, this script will request the highest and lowest values (these being the Statistic Point-of-Reference) from the matrix containing all returns and rewrite global variables tied to the negative and positive return tolerances. This means that all patterns identified will be compared with each other to determine bullish/bearishness in Adaptive Coloring.
Hard Limiting will prevent these global variables from being rewritten, so patterns whose Statistic Point-of-Reference exceed the return tolerances will be fully colored the bullish or bearish colors instead of a generated gradient color. (SEE LIMITATIONS)
Apart from the Candle Detection Modes (CLASSIC and BREAKOUT), there's an additional two inputs which modify how this script behaves grouped under a "MASTER DETECTION SETTINGS" tab. These two "Pattern Detection Settings" are 'SWITCHBOARD' and 'TARGET MODE'.
SWITCHBOARD: Every single pattern has a switch that is associated with its detection. When a switch is enabled, the code which searches for that pattern will be run. With the Pattern Detection Setting set to this, all patterns that have their switches enabled will be sought out and shown.
TARGET MODE: There is an additional setting which operates on top of 'SWITCHBOARD' that singles out an individual pattern the user specifies through a drop down list. The names of every pattern recognized by this script will be present along with an identifier that shows the number of candles in that pattern (Ex: " (# candles)"). All patterns enabled in the switchboard will still have their returns measured, but only the pattern selected from the "Target Pattern" list will be shown. (SEE LIMITATIONS)
The vast majority of other features are held in the one, two, and three candle pattern sections.
For one-candle patterns, there are:
3 — Settings related to defining 'Tall' candles:
The number of candles to sample for previous candle-size averages.
The type of comparison done for 'Tall' Candles: Settings are 'RANGE' and 'BODY'.
The 'Tolerance' for tall candles, specifying what percent of the 'average' size candles must exceed to be considered 'Tall'.
When 'Tall Candle Setting' is set to RANGE, the high-low ranges are what the current candle range will be compared against to determine if a candle is 'Tall'. Otherwise the candle bodies (absolute value of the close - open) will be compared instead. (SEE LIMITATIONS)
Hammer Tolerance - How large a 'discarded wick' may be before it disqualifies a candle from being a 'Hammer'.
Discarded wicks are compared to the size of the Hammer's candle body and are dependent upon the body's center position. Hammer bodies closer to the high of the candle will have the upper wick used as its 'discarded wick', otherwise the lower wick is used.
9 — Doji Settings, some pulled from an old Doji Hunter I made a while back:
Doji Tolerance - How large the body of a candle may be compared to the range to be considered a 'Doji'.
Ignore N/S Dojis - Turns off Trend Direction for non-special Dojis.
GS/DF Doji Settings - 2 Inputs that enable and specify how large wicks that typically disqualify Dojis from being 'Gravestone' or 'Dragonfly' Dojis may be.
4 Settings related to 'Long Wick Doji' candles detailed below.
A Tolerance for 'Rickshaw Man' Dojis specifying how close the center of the body must be to the range to be valid.
The 4 settings the user may modify for 'Long Legged' Dojis are: A Sample Base for determining the previous average of wicks, a Sample Length specifying how far back to look for these averages, a Behavior Setting to define how 'Long Legged' Dojis are recognized, and a tolerance to specify how large in comparison to the prior wicks a Doji's wicks must be to be considered 'Long Legged'.
The 'Sample Base' list has two settings:
RANGE: The wicks of prior candles are compared to their candle ranges and the 'wick averages' will be what the average percent of ranges were in the sample.
WICKS: The size of the wicks themselves are averaged and returned for comparing against the current wicks of a Doji.
The 'Behavior' list has three settings:
ONE: Only one wick length needs to exceed the average by the tolerance for a Doji to be considered 'Long Legged'.
BOTH: Both wick lengths need to exceed the average of the tolerance of their respective wicks (upper wicks are compared to upper wicks, lower wicks compared to lower) to be considered 'Long Legged'.
AVG: Both wicks and the averages of the previous wicks are added together, divided by two, and compared. If the 'average' of the current wicks exceeds this combined average of prior wicks by the tolerance, then this would constitute a valid 'Long Legged' Doji. (For Dojis in general - SEE LIMITATIONS)
The final input is one related to candle patterns which require a Marubozu candle in them. The two settings for this input are 'INCLUSIVE' and 'EXCLUSIVE'. If INCLUSIVE is selected, any opening/closing variant of Marubozu candles will be allowed in the patterns that require them.
For two-candle patterns, there are:
2 — Settings which define 'Engulfing' parameters:
Engulfing Setting - Two options, RANGE or BODY which sets up how one candle may 'engulf' the previous.
Inclusive Engulfing - Boolean which enables if 'engulfing' candles can be equal to the values needed to 'engulf' the prior candle.
For the 'Engulfing Setting':
RANGE: If the second candle's high-low range completely covers the high-low range of the prior candle, this is recognized as 'engulfing'.
BODY: If the second candle's open-close completely covers the open-close of the previous candle, this is recognized as 'engulfing'. (SEE LIMITATIONS)
4 — Booleans specifying different settings for a few patterns:
One which allows for 'opens within body' patterns to let the second candle's open/close values match the prior candles' open/close.
One which forces 'Kicking' patterns to have a gap if the Marubozu setting is set to 'INCLUSIVE'.
And Two which dictate if the individual candles in 'Stomach' patterns need to be 'Tall'.
8 — Floating point values which affect 11 different patterns:
One which determines the distance the close of the first candle in a 'Hammer Inverted' pattern must be to the low to be considered valid.
One which affects how close the opens/closes need to be for all 'Lines' patterns (Bull/Bear Meeting/Separating Lines).
One that allows some leeway with the 'Matching Low' pattern (gives a small range the second candle close may be within instead of needing to match the previous close).
Three tolerances for On Neck/In Neck patterns (2 and 1 respectively).
A tolerance for the Thrusting pattern which give a range the close the second candle may be between the midpoint and close of the first to be considered 'valid'.
A tolerance for the two Tweezers patterns that specifies how close the highs and lows of the patterns need to be to each other to be 'valid'.
The first On Neck tolerance specifies how large the lower wick of the first candle may be (as a % of that candle's range) before the pattern is invalidated. The second tolerance specifies how far up the lower wick to the close the second candle's close may be for this pattern. The third tolerance for the In Neck pattern determines how far into the body of the first candle the second may close to be 'valid'.
For the remaining patterns (3, 4, and 5 candles), there are:
3 — Settings for the Deliberation pattern:
A boolean which forces the open of the third candle to gap above the close of the second.
A tolerance which changes the proximity of the third candle's open to the second candle's close in this pattern.
A tolerance that sets the maximum size the third candle may be compared to the average of the first two candles.
One boolean value for the Two Crows patterns (standard and Upside Gapping) that forces the first two candles in the patterns to completely gap if disabled (candle 1's close < candle 2's low).
10 — Floating point values for the remaining patterns:
One tolerance for defining how much the size of each candle in the Identical Black Crows pattern may deviate from the average of themselves to be considered valid.
One tolerance for setting how close the opens/closes of certain three candle patterns may be to each other's opens/closes.*
Three floating point values that affect the Three Stars in the South pattern.
One tolerance for the Side-by-Side patterns - looks at the second and third candle closes.
One tolerance for the Stick Sandwich pattern - looks at the first and third candle closes.
A floating value that sizes the Concealing Baby Swallow pattern's 3rd candle wick.
Two values for the Ladder Bottom pattern which define a range that the third candle's wick size may be.
* This affects the Three Black Crows (non-identical) and Three White Soldiers patterns, each require the opens and closes of every candle to be near each other.
The first tolerance of the Three Stars in the South pattern affects the first candle body's center position, and defines where it must be above to be considered valid. The second tolerance specifies how close the second candle must be to this same position, as well as the deviation the ratio the candle body to its range may be in comparison to the first candle. The third restricts how large the second candle range may be in comparison to the first (prevents this pattern from being recognized if the second candle is similar to the first but larger).
The last two floating point values define upper and lower limits to the wick size of a Ladder Bottom's fourth candle to be considered valid.
█ HOW TO USE
While there are many moving parts to this script, I attempted to set the default values with what I believed may help identify the most patterns within reasonable definitions. When this script is applied to a chart, the Candle Detection Mode (along with the BREAKOUT settings) and all candle switches must be confirmed before patterns are displayed. All switches are on by default, so this gives the user an opportunity to pick which patterns to identify first before playing around in the settings.
All of the settings/inputs described above are meant for experimentation. I encourage the user to tweak these values at will to find which set ups work best for whichever charts they decide to apply these patterns to.
Refer to the patterns themselves during experimentation. The statistic information provided on the tooltips of the patterns are meant to help guide input decisions. The breadth of candlestick theory is deep, and this was an attempt at capturing what I could in its sea of information.
█ LIMITATIONS
DISCLAIMER: While it may seem a bit paradoxical that this script aims to use past performance to potentially measure future results, past performance is not indicative of future results . Markets are highly adaptive and often unpredictable. This script is meant as an informational tool to show how patterns may behave. There is no guarantee that confidence intervals (or any other metric measured with this script) are accurate to the performance of patterns; caution must be exercised with all patterns identified regardless of how much information regarding prior performance is available.
Candlestick Theory - In the name, Candlestick Theory is a theory , and all theories come with their own limits. Some patterns identified by this script may be completely useless/unprofitable/unpredictable regardless of whatever combination of settings are used to identify them. However, if I truly believed this theory had no merit, this script would not exist. It is important to understand that this is a tool meant to be utilized with an array of others to procure positive (or negative, looking at you, short sellers ) results when navigating the complex world of finance.
To address the functionality note however, this script has an offset of 1 by default. Patterns will not be identified on the currently closing candle, only on the candle which has most recently closed. Attempting to have this script do both (offset by one or identify on close) lead to more trouble than it was worth. I personally just want users to be aware that patterns will not be identified immediately when they appear.
Trend Direction - Moving Averages - There is a small quirk with how MA settings will be adjusted if the user inputs two moving averages of the same length when the "MA Setting" is set to 'BOTH'. If Moving Averages have the same length, this script will default to only using MA 1 regardless of if the types of Moving Averages are different . I will experiment in the future to alleviate/reduce this restriction.
Price Analysis - BREAKOUT mode - With how identifying patterns with a look-ahead confirmation works, the percent returns for patterns that break out in either direction will be calculated on the same candle regardless of if P/L Offset is set to 'FROM CONFIRMATION' or 'FROM APPEARANCE'. This same issue is present in the Hikkake Hunter script mentioned earlier. This does not mean the P/L calculations are incorrect , the offset for the calculation is set by the number of candles required to confirm the pattern if 'FROM APPEARANCE' is selected. It just means that these two different P/L calculations will complete at the same time independent of the setting that's been selected.
Adaptive Coloring/Hard Limiting - Hard Limiting is only used with Adaptive Coloring and has no effect outside of it. If Hard Limiting is used, it is recommended to increase the 'Positive' and 'Negative' return tolerance values as a pattern's bullish/bearishness may be disproportionately represented with the gradient generated under a hard limit.
TARGET MODE - This mode will break rules regarding patterns that are overridden on purpose. If a pattern selected in TARGET mode would have otherwise been absorbed by a larger pattern, it will have that pattern's percent return calculated; potentially leading to duplicate returns being included in the matrix of all returns recognized by this script.
'Tall' Candle Setting - This is a wide-reaching setting, as approximately 30 different patterns or so rely on defining 'Tall' candles. Changing how 'Tall' candles are defined whether by the tolerance value those candles need to exceed or by the values of the candle used for the baseline comparison (RANGE/BODY) can wildly affect how this script functions under certain conditions. Refer to the tooltip of these settings for more information on which specific patterns are affected by this.
Doji Settings - There are roughly 10 or so two to three candle patterns which have Dojis as a part of them. If all Dojis are disabled, it will prevent some of these larger patterns from being recognized. This is a dependency issue that I may address in the future.
'Engulfing' Setting - Functionally, the two 'Engulfing' settings are quite different. Because of this, the 'RANGE' setting may cause certain patterns that would otherwise be valid under textbook and online references/definitions to not be recognized as such (like the Upside Gap Two Crows or Three Outside down).
█ PATTERN LIST
This script recognizes 85 patterns upon initial release. I am open to adding additional patterns to it in the future and any comments/suggestions are appreciated. It recognizes:
15 — 1 Candle Patterns
4 Hammer type patterns: Regular Hammer, Takuri Line, Shooting Star, and Hanging Man
9 Doji Candles: Regular Dojis, Northern/Southern Dojis, Gravestone/Dragonfly Dojis, Gapping Up/Down Dojis, and Long-Legged/Rickshaw Man Dojis
White/Black Long Days
32 — 2 Candle Patterns
4 Engulfing type patterns: Bullish/Bearish Engulfing and Last Engulfing Top/Bottom
Dark Cloud Cover
Bullish/Bearish Doji Star patterns
Hammer Inverted
Bullish/Bearish Haramis + Cross variants
Homing Pigeon
Bullish/Bearish Kicking
4 Lines type patterns: Bullish/Bearish Meeting/Separating Lines
Matching Low
On/In Neck patterns
Piercing pattern
Shooting Star (2 Lines)
Above/Below Stomach patterns
Thrusting
Tweezers Top/Bottom patterns
Two Black Gapping
Rising/Falling Window patterns
29 — 3 Candle Patterns
Bullish/Bearish Abandoned Baby patterns
Advance Block
Collapsing Doji Star
Deliberation
Upside/Downside Gap Three Methods patterns
Three Inside/Outside Up/Down patterns (4 total)
Bullish/Bearish Side-by-Side patterns
Morning/Evening Star patterns + Doji variants
Stick Sandwich
Downside/Upside Tasuki Gap patterns
Three Black Crows + Identical variation
Three White Soldiers
Three Stars in the South
Bullish/Bearish Tri-Star patterns
Two Crows + Upside Gap variant
Unique Three River Bottom
3 — 4 Candle Patterns
Concealing Baby Swallow
Bullish/Bearish Three Line Strike patterns
6 — 5 Candle Patterns
Bullish/Bearish Breakaway patterns
Ladder Bottom
Mat Hold
Rising/Falling Three Methods patterns
█ WORKS CITED
Because of the amount of time needed to complete this script, I am unable to provide exact dates for when some of these references were used. I will also not provide every single reference, as citing a reference for each individual pattern and the place it was reviewed would lead to a bibliography larger than this script and its description combined. There were five major resources I used when building this script, one book, two websites (for various different reasons including patterns, moving averages, and various other articles of information), various scripts from TradingView's public library (including TradingView's own source code for *all* candle patterns ), and PineScrypt's reference manual.
Bulkowski, Thomas N. Encyclopedia of Candlestick Patterns . Hoboken, New Jersey: John Wiley & Sons Inc., 2008. E-book (google books).
Various. Numerous webpages. CandleScanner . 2023. online. Accessed 2020 - 2023.
Various. Numerous webpages. Investopedia . 2023. online. Accessed 2020 - 2023.
█ AKNOWLEDGEMENTS
I want to take the time here to thank all of my friends and family, both online and in real life, for the support they've given me over the last few years in this endeavor. My pets who tried their hardest to keep me from completing it. And work for the grit to continue pushing through until this script's completion.
This belongs to me just as much as it does anyone else. Whether you are an institutional trader, gold bug hedging against the dollar, retail ape who got in on a squeeze, or just parents trying to grow their retirement/save for the kids. This belongs to everyone.
Private Beta for new features to be tested can be found here .
Vires In Numeris
在脚本中搜索"high low"
GKD-C Adaptive Digital Kahler Variety RSI w/ DZ [Loxx]Giga Kaleidoscope GKD-C Adaptive Digital Kahler Variety RSI w/ DZ is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Adaptive Digital Kahler Variety RSI w/ DZ as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ GKD-C Adaptive Digital Kahler Variety RSI w/ DZ
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI.
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
This indicator contains 7 different types of RSI:
RSX
Regular
Slow
Rapid
Harris
Cuttler
Ehlers Smoothed
What is RSI?
RSI stands for Relative Strength Index . It is a technical indicator used to measure the strength or weakness of a financial instrument's price action.
The RSI is calculated based on the price movement of an asset over a specified period of time, typically 14 days, and is expressed on a scale of 0 to 100. The RSI is considered overbought when it is above 70 and oversold when it is below 30.
Traders and investors use the RSI to identify potential buy and sell signals. When the RSI indicates that an asset is oversold, it may be considered a buying opportunity, while an overbought RSI may signal that it is time to sell or take profits.
It's important to note that the RSI should not be used in isolation and should be used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is RSX?
Jurik RSX is a technical analysis indicator that is a variation of the Relative Strength Index Smoothed ( RSX ) indicator. It was developed by Mark Jurik and is designed to help traders identify trends and momentum in the market.
The Jurik RSX uses a combination of the RSX indicator and an adaptive moving average (AMA) to smooth out the price data and reduce the number of false signals. The adaptive moving average is designed to adjust the smoothing period based on the current market conditions, which makes the indicator more responsive to changes in price.
The Jurik RSX can be used to identify potential trend reversals and momentum shifts in the market. It oscillates between 0 and 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend . Traders can use these levels to make trading decisions, such as buying when the indicator crosses above 50 and selling when it crosses below 50.
The Jurik RSX is a more advanced version of the RSX indicator, and while it can be useful in identifying potential trade opportunities, it should not be used in isolation. It is best used in conjunction with other technical and fundamental analysis tools to make informed trading decisions.
What is Slow RSI?
Slow RSI is a variation of the traditional Relative Strength Index ( RSI ) indicator. It is a more smoothed version of the RSI and is designed to filter out some of the noise and short-term price fluctuations that can occur with the standard RSI .
The Slow RSI uses a longer period of time than the traditional RSI , typically 21 periods instead of 14. This longer period helps to smooth out the price data and makes the indicator less reactive to short-term price fluctuations.
Like the traditional RSI , the Slow RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Slow RSI is a more conservative version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also be slower to respond to changes in price, which may result in missed trading opportunities. Traders may choose to use a combination of both the Slow RSI and the traditional RSI to make informed trading decisions.
What is Rapid RSI?
Same as regular RSI but with a faster calculation method
What is Harris RSI?
Harris RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Larry Harris and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Harris RSI uses a different calculation formula compared to the traditional RSI . It takes into account both the opening and closing prices of a financial instrument, as well as the high and low prices. The Harris RSI is also normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Harris RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Harris RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Harris RSI and the traditional RSI to make informed trading decisions.
What is Cuttler RSI?
Cuttler RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by Curt Cuttler and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Cuttler RSI uses a different calculation formula compared to the traditional RSI . It takes into account the difference between the closing price of a financial instrument and the average of the high and low prices over a specified period of time. This difference is then normalized to a range of 0 to 100, with values above 50 indicating a bullish trend and values below 50 indicating a bearish trend .
Like the traditional RSI , the Cuttler RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Cuttler RSI is a more advanced version of the RSI and can be useful in identifying longer-term trends in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Cuttler RSI and the traditional RSI to make informed trading decisions.
What is Ehlers Smoothed RSI?
Ehlers smoothed RSI is a technical analysis indicator that is a variation of the Relative Strength Index ( RSI ). It was developed by John Ehlers and is designed to help traders identify potential trend changes and momentum shifts in the market.
The Ehlers smoothed RSI uses a different calculation formula compared to the traditional RSI . It uses a smoothing algorithm that is designed to reduce the noise and random fluctuations that can occur with the standard RSI . The smoothing algorithm is based on a concept called "digital signal processing" and is intended to improve the accuracy of the indicator.
Like the traditional RSI , the Ehlers smoothed RSI is used to identify potential overbought and oversold conditions in the market. It oscillates between 0 and 100, with values above 70 indicating overbought conditions and values below 30 indicating oversold conditions. Traders often use these levels as potential buy and sell signals.
The Ehlers smoothed RSI can be useful in identifying longer-term trends and momentum shifts in the market. However, it can also generate more false signals than the standard RSI . Traders may choose to use a combination of both the Ehlers smoothed RSI and the traditional RSI to make informed trading decisions.
What is a Vertical Horizontal Filter?
The Vertical Horizontal Filter (VHF) is a technical indicator used in trading to identify whether a market is trending or in a sideways trading range. It was developed by Adam White, and is based on the concept that markets tend to exhibit more volatility when they are trending, and less volatility when they are in a sideways range.
The VHF is calculated by taking the ratio of the range of the high and low prices over a specified period to the total range of prices over the same period. The resulting ratio is then multiplied by 100 to create a percentage value.
If the VHF is above a certain threshold, typically 60, it is considered to be indicating a trending market. If it is below the threshold, it is indicating a sideways trading range.
Traders use the VHF to help identify market conditions and to adjust their trading strategies accordingly. In a trending market, traders may look for opportunities to enter or exit positions based on the direction of the trend, while in a sideways trading range, traders may look for opportunities to buy at the bottom of the range and sell at the top.
The VHF can also be used in conjunction with other technical indicators, such as moving averages or momentum indicators, to help confirm trading signals. For example, if the VHF is indicating a trending market and the moving average is also indicating a trend, this may provide a stronger signal to enter or exit a trade.
One potential limitation of the VHF is that it can be less effective in markets that are transitioning between trending and sideways trading ranges. During these periods, the VHF may not accurately reflect the current market conditions, and traders may need to use other indicators or methods to help identify the current trend.
In summary, the Vertical Horizontal Filter (VHF) is a technical indicator used in trading to identify whether a market is trending or in a sideways trading range. It is based on the concept that markets exhibit more volatility when they are trending, and less volatility when they are in a sideways range. Traders use the VHF to help identify market conditions and adjust their trading strategies accordingly.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
What is Adaptive Digital Kahler Variety RSI w/ DZ?
We first calculate the VHF filter, we then inject that period output into an RSI calculation, we apply a Digital Kahler filter to this output, and finally, we create Dynamic Zones to determine oscillator extremes. There are four types of signals: Slope, Static Zero-line, Dynamic Levels, and Dynamic Middle
Requirements
Inputs
Confirmation 1 and Solo Confirmation: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Outputs
Confirmation 2 and Solo Confirmation Complex: GKD-E Exit indicator
Confirmation 1: GKD-C Confirmation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest strategy
Additional features will be added in future releases.
Pivot Highs&lows: Short/Medium/Long-term + Spikeyness FilterShows Pivot Highs & Lows defined or 'Graded' on a fractal basis: Short-term, medium-term and long-term. Also applies 'Spikeyness' condition by default to filter-out weak/rounded pivots
ES1! 4hr chart (CME) shown above, with lookback = 15; clearly identifying the major highs & lows on the basis of how they are fractally 'nested' within lesser Pivots.
-- in the above chart Short term pivot highs (STH) are simply represented by green 'ʌ', and short-term pivot lows (STL) are simply represented by orange 'v'.
//Basics: (as applying to pivot highs, the following is reversed for pivot lows)
-Short term highs (STH) are simple pivot highs, albeit refined from standard with the 'spikeyness' filter.
-Medium-term highs (MTH) are defined as having a lower STH on either side of them.
-Long-term highs (LTH) are defined as having a lower MTH on either side of them.
//Purpose:
-Education: Quick and easy visualization of the strength or importance of a pivot high or low; a way of grading them based on their larger context.
-Backtesting: use in combination with other trading methods when backtesting to see the relative significance and price sensitivity of LTHs/LTLs compared to lower grade highs and lows.
//Settings:
-Choose Pivot lookback/lookforward bars: One setting, the basis from which all further pivot calculations are done.
-Toggle on/off 'Spikeyness' condition to filter-out weak/rounded/unimpressive pivot highs or lows (default is ON).
-Toggle on/off each of STH, MTH, LTH, STL, MTL, LTL; and choose label text-styles/colors/sizes independently.
-Set text Vertically, horizonally, or simply use 'ʌ' or 'v' symbols if you want to declutter your chart.
//Usage notes:
-Pivots take time to print (lookback bars must have elapsed before confirmation). Fractally nested pivots as here (i.e. a LTH), take even longer to print/confirm, so please be patient.
-Works across timeframes & Assets. Different timeframes may require slightly tweaked lookback/forward settings for optimal use; default is 15 bars.
Example usage with just symbolic labels short-term, med-term, long-term with 1x, 2x and 3x ʌ/v respectively:
Flat Market and Low ADX Indicator [CHE]Why use the Flat Market and Low ADX Indicator ?
Flat markets, where prices remain within a narrow range for an extended period, can be both critical and dangerous for traders. In a flat market, the price action becomes less predictable, and traders may struggle to find profitable trading opportunities. As a result, many traders may decide to take a break from the market until a clear trend emerges.
However, flat markets can also be dangerous for traders who continue to trade despite the lack of clear trends. In the absence of a clear direction, traders may be tempted to take larger risks or make impulsive trades in an attempt to capture small profits. Such behavior can quickly lead to significant losses, especially if the market suddenly breaks out of its flat range, causing traders to experience large drawdowns.
Therefore, it is essential to approach flat markets with caution and to have a clear trading plan that incorporates strategies for both trending and flat markets. Traders may also use technical indicators, such as the Flat Market and Low ADX Indicator, to help identify flat markets and determine when it is appropriate to enter or exit a position.
The confluence between flat markets and low ADX readings can further increase the risk of trading during these periods. The ADX (Average Directional Index) is a technical indicator used to measure the strength of a trend. A low ADX reading indicates that the market is in a consolidation phase, which can coincide with a flat market. When a flat market occurs during a period of low ADX, traders should be even more cautious, as there is little to no directional bias in the market. In this situation, traders may want to consider waiting for a clear trend to emerge or using range-bound trading strategies to avoid taking excessive risks.
Introduction:
Pine Script is a programming language used for developing custom technical analysis indicators and trading strategies in TradingView. This particular script is an indicator designed to identify flat markets and low ADX conditions. In this description, we will delve deeper into the functionality of this script and how it can be used to improve trading decisions.
Description:
The first input in the script is the length of the moving average used for calculating the center line. This moving average is used to define the high and low range of the market. The script then calculates the middle value of the range by taking the double exponential moving average (EMA) of the high, low, and close prices.
The script then determines whether the market is flat by comparing the middle value of the range with the high and low values. If the middle value is greater than the high value or less than the low value, the market is not flat. If the middle value is within the high and low range, the script considers the market to be flat. The script also uses RSI filter settings to further confirm if the market is flat or not. If the RSI value is between the RSI min and max values, then the market is considered flat. If the RSI value is outside this range, the market is not considered flat.
The script also calculates the ADX (Average Directional Index) to determine whether it's in a low area. ADX is a technical indicator used to measure the strength of a trend. The script uses the ADX filter settings to define the ADX threshold value. If the ADX value is below the threshold value, the script considers the market to be in a low ADX area.
The script provides various input options to customize the display settings, including the option to show the flat market and low ADX areas. Users can choose their preferred colors for the flat market and low ADX areas and adjust the transparency levels to suit their needs.
Conclusion:
In conclusion, this Pine Script indicator is designed to identify flat market and low ADX conditions, which can help traders make informed trading decisions. The script uses a range of inputs and calculations to determine the market direction, RSI filter, and ADX filter. By customizing the display settings, users can adjust the indicator to suit their preferences and improve their trading strategies. Overall, this script can be a valuable tool for traders looking to gain an edge in the markets.
Acknowledgments:
Thanks to the Pine Script™ v5 User Manual www.tradingview.com
Triangulation : Statistically Approved ReversalsA lot of calculation, but a simple and effective result displayed on the chart.
It automatically identifies a very favorable period for a price reversal, by analyzing the daily and intraday price action statistics from the maximum of the most recent bars from the historical data. No repainting. Alerts can be set.
The statistical study is done in real time for each instrument. The probabilities therefore vary over time and adapt to the latest information collected by the indicator.
The time range of the data study can be changed by simply changing the UT :
- 30m = 3.5 last months feed statistics
- 15m = 52 last days feed statistics
- 5m = 17 last days feed statistics (recommanded)
HOW TO USE
This indicator informs when we are in a time period strongly favorable to reversal.
==> Crossing probabilities of different kinds, in price and in time => Triangulation of top and bottom !
HOW It WORK :
fractal statistics on high and low formation.
hour's probabilities of making the high/low of the day are crossed with day's probabilities of making the high/low of the week.
First for the day, we study:
- value of the probability compared to the average probabilities
- value of the coefficient between the high probability and the low probability
which we then refine for the hour, with the same calculation.
Result: bright color for a day + hour with high probability, weak color if the probability is low but remains the only possible bias. Between these two possibilities, intermediate colors are possible - just like looking for shorts if the day is bullish, if it is a high probability hour!
This color is displayed in the background, only if we are forming the high of the day for tops, and the low of the day for bottoms - detected with a stochastic.
All probabilities are studied in real time for the current asset.
We will call this signal "killstats", for "killzones statistics"
fractal statistics on the probability of closure under specific predefined levels according to 36 cycles.
the probabilities of several cycles are studied, for example:
NY session versus London and Asian sessions, London session compared to its opening, NY session compared to its opening, "algorithmic cycles" ( 1h30), Opening of NY compared to its intersection with London..
Each cycle producing a probability of closing with respect to the opening price of each period. The periods are : (Etc/UTC)
15-18h / 15-16h / 9-13h / 14-17h / 18-22h / 10-12h / 9-10h30 / 10h30-12h / 12-13h30 / 13h30-15h / 15h-16h30 / 16h30-18h
The cycles can be superimposed, which allows to support or attenuate a signal for the key periods of the day: 9am-12pm, and 3pm-6pm. The period of the day covered by the study of cycles is 9h-22h.
Result : ==> a straight line with a half bell. Colors = almost transparent for 53% probability (low), and very intense for a high probability (75%). The line displayed corresponds to the opening price, which we are supposed to close within the time limit - before the end of the period, where the line stops.
If the price goes in the opposite direction to the one predicted by the statistics, then a background connects the price to the close level to be respected.
if direction and close is respected, nothing is displayed : there is no opportunity, no divergence between statistics and actual price moves.
By unchecking the "light mode", you can see each close level displayed on the chart, with the corresponding probability and the number of times the cycle was detected. The color varies from intense for a high probability (75%), to light for a low probability (53%)
We will call this signal "cyclic anomalies"
By default, as shown in the indicator presentation image, the "intersection only" option is checked: only the intersection between 1) killstats and 2) cyclic anomalies is displayed. (filter +-30% of killstats signals)
MORE INFORMATIONS
/!\ : during a backtest, it is necessary to refresh the studied data to benefit from the real time signals, and for that you have to use the replay mode. if "Backtesting informations?"is checked, labels are displayed on the graph to warn of the % distortion of the signals. I recommend using the replay mode every 250 candles, and every 1000 candles for premium accounts, to have real signals.
- Alerts can be set for killzone, or intersections ( As in presentation picture)
- The ideal use is in m5. It can trigger several times a day, sometimes in opposite directions, and sometimes not trigger for several days.
- Premium account have 20k candles data, and not 5k => signals may vary depending on your tradingview subscription.
GKD-B Baseline [Loxx]Giga Kaleidoscope Baseline is a Baseline module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is an NNFX algorithmic trading strategy?
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trend. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trend. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average as shown on the chart above
Volatility/Volume: Jurik Volty
Confirmation 1: Vortex
Confirmation 2: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. let's go over what's inside the GKD-B Baseline itself.
GKD Baseline Special Features and Notable Inputs
GKD Baseline v1.0 includes 63 different moving averages:
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
Description. The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Ehlers Optimal Tracking Filter - EOTF
The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving
Average
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
T3 is basically an EMA on steroids, You can read about T3 here:
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Kalman Filter
Kalman filter is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies. This means that the filter was originally designed to work with noisy data. Also, it is able to work with incomplete data. Another advantage is that it is designed for and applied in dynamic systems; our price chart belongs to such systems. This version is true to the original design of the trade-ready Kalman Filter where velocity is the triggering mechanism.
Kalman Filter is a more accurate smoothing/prediction algorithm than the moving average because it is adaptive: it accounts for estimation errors and tries to adjust its predictions from the information it learned in the previous stage. Theoretically, Kalman Filter consists of measurement and transition components.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
Exotic Triggers
This version of Baseline allows the user to select from exotic or source triggers. An exotic trigger determines trend by either slope or some other mechanism that is special to each moving average. A source trigger is one of 32 different source types from Loxx's Exotic Source Types. You can read about these source types here:
Volatility Goldie Locks Zone
This volatility filter is the standard first pass filter that is used for all NNFX systems despite the additional volatility/volume filter used in step 5. For this filter, price must fall into a range of maximum and minimum values calculated using multiples of volatility. Unlike the standard NNFX systems, this version of volatility filtering is separated from the core Baseline and uses it's own moving average with Loxx's Exotic Source Types. The green and red dots at the top of the chart denote whether a candle qualifies for a either or long or short respectively. The green and red triangles at the bottom of the chart denote whether the trigger has crossed up or down and qualifies inside the Goldie Locks zone. White coloring of the Goldie Locks Zone mean line is where volatility is too low to trade.
Volatility Types Included
v1.0 Included Volatility
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator consists of using the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e. it assumes that the underlying asset follows a GBM process with zero drift. Therefore the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
AG FX - Pivot PointsPivot Points High Low
Definition
The Pivot Points High Low indicator is used to determine and anticipate potential changes in market price and reversals. The Highs referred to in the title are created based on the number of bars that exhibit lower highs on either side of a Pivot Point High, whereas the Lows are created based on the number of bars that exhibit higher lows on either side of a Pivot Point Low.
Calculations
As mentioned above, Pivot Point Highs are calculated by the number of bars with lower highs on either side of a Pivot Point High calculation. Similarly, Pivot Point Lows are calculated by the number of bars with higher lows on either side of a Pivot Point Low calculation.
Takeaways and what to look for
A Pivot Point is more significant or noteworthy if the trend is extended or longer than average. This can mean if a trader selects a higher period for before and after the Pivot Point, the trend could be longer and therefore prove the Pivot Point itself more notable.
Additionally, Pivot Points can help a trader assess where would be best to draw. By analyzing price changes and reversals, a trader has more of an ability to determine and predict price patterns and general price trends.
Summary
The Pivot Points High Low indicator can predict and determine price changes and potential reversals in the market. Pivot Points can also help traders identify price patterns and trends, depending on the period and significance of the Pivot Point value.
Fibonacci-Trading-Indikator_3Daily (weekly, monthly) profits with the Fibonacci trading indicator_3
Quotes move in Fibonacci ratios in liquid markets. With this indicator you receive information for daily trades or for position trades based on a week or on a monthly basis, in which area you should ideally enter the market and where the minimum achievable price target is. This price target is 61.8% of yesterday's trading range, or the trading range of the previous week, or the trading range of the previous month, depending on the time frame for which the indicator should calculate the minimum achievable high / low. This is also where you realize your profit.
For this calculation, the following entries must be made in the properties window of the indicator:
• Preselection uptrend / downtrend.
• Time frame (day, week, ...) of the price bar for the possible high / low to be determined.
• Trading range of the previous day, or the previous week, or the previous month.
• Current lowest low of the selected time frame when trading has started and prices are rising.
• Current highest high of the selected time frame when trading has started and prices are falling.
Important areas for trading are:
• The entry range 0% - 23.6% for long or short.
• The target price level 61.8%.
Choose a suitable time frame to detect the direction of movement while the quotes are still moving in the entry area. The camelback indicator can be of great help. Also test the resolution setting of the camelback indicator. With a resolution of 1 hour in the 6 or 12 minute chart, you get a perspective for the broader direction. Movement patterns of corrections or consolidations, if they last more than a day or a week, also give clues to the coming direction of movement for the trade. So look back to see what happened yesterday, a week ago, or a month ago. Pay attention to the market anatomy, find out how the market works, count the price bars in consolidations and trends.
After entering the values the indicator will show the Fibonacci expansion price levels for the possible high or low for the selected time frame. Buy / sell within the entry range between 0% and 23.6% as the market moves towards the last long / or short entry point. This is the course range up to the 23.6% course level. The 61.8% price level is the minimum expected price target. We assume that the current bar will reach at least 61.8% of the trading range of the previous day, week or month. Depending on the set time frame. You should therefore realize the profits you have made with 50% of the position when the prices have reached the 61.8% level. With a suitable trailing stop you can be stopped with the rest of the position, but do not risk more than 50% of the profits.
With the quarter or year preselection and the corresponding entries, the minimum expected quarterly high / quarterly low or annual high / annual low can be determined.
The Fibonacci price levels can be shown and hidden. In the chart click on the gear wheel for “Chart Settings”. In the “Scaling” menu, the price levels can be displayed with the preselection “Label for indicator names” and “Label for last indicator value”. Slide the chart to the right to find possible support and resistance at the price levels that could provide confirmation of the target.
In the event of input errors or missing entries for a time frame, the indicator is hidden.
Pay attention to your trade management to avoid losses.
The new Fibonacci Trading Indicator_3 has the following additions and changes:
Area code for the quarter time frame has been added.
The entry area received a 23.6% and a 50% subdivision. Two envelope lines above the 23.6% entry level in the case of an upward trend and below the 23.6% entry level in the case of a downtrend, with a width of 23.6% and 14.6% of the entry level, are intended to indicate that the closing price is higher the quotations have broken out of the entry-level area.
A volatility stop for upward and downward trends can be activated.
A factor is added to the fluctuation range of each price bar for the stop. Then a moving average is calculated with an adjustable period. The period setting should be set between 5 and 10. The result can be smoothed adjustable.
Presetting:
Periods = 10
Factor = 1.4
Smoothing = 7
With the assumption that the market entry in an upward trend occurs when the prices break out above a bar high, the result of the stop calculation is subtracted from the bar high. In the case of a downward trend, the result of the stop calculation is added to the price bar low.
When entering the market, set the factor to 2.4. If inside bars follow a trend movement, the stop should be brought closer. Try the factor setting 0.4 or less. The smallest adjustable factor is 0.1.
For the entry into an established trend, as described in an idea contribution by me, there are two switchable moving averages. The application for the (MA_H) takes place on high and for the (MA_L) adjustable on high, low, shot, h + 1/2 etc. Period and offset (shift) are adjustable. With this idea, the entry into the market occurs between a 618% correction (the Fibonacci entry point) and the DEP (average entry point). The DEP in this case is the MA_H with period = 4 and an offset = 1 in the case of a downward trend, or the MA_L with the same setting and application to lows in an upward trend.
Also test the MA_L in trends with the settings (period, offset) 3.3 or 5, 3 or 7.5 and applying it to closing prices for a close encompassing of the highs / lows.
Tägliche (wöchentliche, monatliche) Gewinne mit dem Fibonacci-Trading Indikator_3
Kursnotierungen bewegen sich in liquiden Märkten in Fibonacci-Verhältnisse. Mit diesem Indikator erhalten Sie für Tagesgeschäfte, oder für Positionstrades auf Basis einer Woche, oder auf Basis eines Monats Informationen, in welchem Bereich Sie idealerweise in den Markt einsteigen sollten und wo das mindeste erreichbare Kursziel liegt. Dieses Kursziel liegt bei 61,8% der gestrigen Handelspanne, oder der Handelspanne der Vorwoche, oder der Handelspanne des Vormonats, also abhängig davon für welchen Zeitrahmen der Indikator das mindeste erreichbare Hoch/Tief berechnen soll. Dort realisieren Sie auch Ihren Gewinn.
Für diese Berechnung sind folgende Eingaben im Eigenschaftenfenster des Indikators einzustellen:
• Vorwahl Aufwärtstrend/ Abwärtstrend.
• Zeitrahmen (Tag, Woche, …) des Kursbalkens für das zu ermittelnde mögliche Hoch/ Tief.
• Handelspanne des vorherigen Tages, oder der vorherigen Woche, oder des vorherigen Monats.
• Aktuell tiefstes Tief des vorgewählten Zeitrahmens, wenn der Handel begonnen hat und die Notierungen steigen.
• Aktuell höchstes Hoch des vorgewählten Zeitrahmens, wenn der Handel begonnen hat und die Notierungen fallen.
Wichtige Bereiche für das Trading sind:
• Der Einstiegsbereich 0% - 23,6% für long oder short.
• Der Kursziellevel 61,8%.
Wählen Sie für die Erkennung der Bewegungsrichtung einen geeigneten Zeitrahmen, während sich die Notierungen noch im Einstiegsbereich bewegen. Der Camelback-Indikator kann eine gute Hilfe sein. Testen Sie auch die Auflösung-Einstellung des Camelback-Indikators. Mit der Auflösung 1 Stunde Im 6- oder 12 Minuten-Chart erhalten Sie einen Blickwinkel für die große Richtung. Auch Bewegungsmuster von Korrekturen oder Konsolidierungen, wenn sie mehr als einen Tag oder eine Woche andauern geben Hinweise auf die kommende Bewegungsrichtung für den Trade. Schauen Sie also zurück um zu prüfen, was sich gestern, vor einer Woche oder vor einem Monat abgespielt hat. Achten sie auf die Marktanatomie, finden Sie heraus wie der Markt funktioniert, zählen Sie Kursstäbe in Konsolidierungen und Trends.
Nach Eingabe der Werte zeigt der Indikator die Fibonacci-Ausweitungskurslevels für das mögliche Hoch oder Tief für den ausgewählten Zeitrahmen. Kaufen/ verkaufen Sie innerhalb des Einstiegsbereichs zwischen 0% und 23,6%, während sich der Markt in Richtung des letzten long-/ oder short-Einstiegspunktes bewegt. Das ist der Kursbereich bis zum 23,6%- Kurslevel. Der 61,8%-Kurslevel ist das mindeste erwartbare Kursziel. Wir gehen davon aus, dass der aktuelle Kursbalken mindestens 61,8% der Handelsspanne des vorherigen Tages, der vorherigen Woche oder des vorherigen Monats erreichen wird. Abhängig vom eingestellten Zeitrahmen. Realisieren Sie deshalb die angelaufenen Gewinne mit 50% der Position, wenn die Notierungen den 61,8% - Level erreicht haben. Mit einem geeigneten Trailing-Stopp lassen Sie sich mit der restlichen Position ausstoppen, riskieren Sie dafür aber nicht mehr als 50 % der angelaufenen Gewinne.
Mit der Vorwahl Quartal oder Jahr und den entsprechenden Eingaben kann auch das mindeste erwartbare Quartalshoch/ Quartalstief bzw. Jahreshoch/ Jahrestief ermittelt werden.
Die Fibonacci-Kurslevels lassen sich ein- und ausblenden. Klicken Sie im Chart auf das Zahnrad für „Chart Einstellungen“. Im Menü „Skalierungen“ kann mit der Vorwahl „Label für Indikatornahmen“ und „Label für letzten Indikatorwert“ die Kurslevels angezeigt werden. Schieben Sie den Chart nach rechts um mögliche Unterstützungen und Widerstände an den Kurslevels zu finden, die Bestätigung für das Ziel geben könnten.
Bei Eingabefehlern oder fehlenden Eingaben zu einem Zeitrahmen wird der Indikator ausgeblendet.
Achten Sie zur Vermeidung von Verlusten auf ihr Handelsmanagement.
Der neue Fibonacci-Trading-Indikator_3 besitz folgende Zusätze und Änderungen:
Vorwahl für den Zeitrahmen Quartal wurde hinzugefügt.
Der Einstiegsbereich erhielt eine 23,6% und eine 50% Unterteilung. Zwei Umschlagslinien über dem 23,6%-Einstiegslevel bei einem Aufwärtstrend, bzw. unter dem 23,6%-Einstiegslevel bei einem Abwärtstrend, mit der Breite 23,6% und 14,6% vom Einstiegsbereich, sollen bei höherem Schlusskurs signalisieren, dass die Notierungen aus dem Einstiegsbereich ausgebrochen sind.
Ein Volatilitätsstopp jeweils für Aufwärts- und Abwärtstrend kann zugeschaltet werden.
Für den Stopp wird die Schwankungsbreite jedes Kursbalkens wird mit einem Faktor beaufschlagt. Danach erfolgt die Berechnung eines gleitenden Durchschnitts mit einstellbarer Periode. Die Periodeneinstellung sollte zwischen 5 und 10 eingestellt werden. Das Ergebnis kann einstellbar geglättet werden.
Voreinstellung:
Perioden = 10
Faktor = 1,4
Glättung = 7
Mit der Annahme, dass der Markteinstieg in einem Aufwärtstrend bei Ausbruch der Notierungen über ein Kursbalkenhoch erfolgt, wird das Ergebnis der Stoppberechnung vom Kursbalkenhoch subtrahiert. Bei einem Abwärtstrend wird das Ergebnis der Stoppberechnung zum Kursbalkentief addiert.
Stellen Sie bei Markteintritt den Faktor auf 2,4. Folgen nach einer Trendbewegung Innenstäbe sollte der Stopp näher herangeführt werden. Probieren Sie die Faktoreinstellung 0,4 oder kleiner. Der kleinste einstellbare Faktor ist 0,1.
Für den Einstieg in einen etablierten Trend, wie in einem Ideenbeitrag von mir beschrieben, gibt es zwei zuschaltbare gleitende Durchschnitte. Die Anwendung für den (MA_H) erfolgt auf Hochs und für den (MA_L) einstellbar auf Hoch, Tief, Schuss, h+l/2 usw.. Periode und Offset (Verschiebung) sind einstellbar. Bei dieser Idee erfolgt der Einstieg in den Markt zwischen einer 618%-Korrektur (dem Fibonacci-Einstiegspunkt) und dem DEP (Durchschnittlicher Einstiegspunkt). Der DEP ist in diesem Fall der MA_H mit Periode = 4 und einem Offset = 1, bei einem Abwärtstrend, oder der MA_L mit identischer Einstellung und Anwendung auf Tiefs in einem Aufwärtstrend.
Testen Sie den MA_L auch in Trends mit den Einstellungen (Periode, Offset) 3,3 oder 5, 3 oder 7,5 und Anwendung auf Schlusskurse für eine enge Umfassung der Hochs/ Tiefs.
Non Parametric Adaptive Moving AverageIntroduction
Not be confused with non-parametric statistics, i define a "non-parametric" indicator as an indicator who does not have any parameter input. Such indicators can be useful since they don't need to go through parameter optimization. I present here a non parametric adaptive moving average based on exponential averaging using a modified ratio of open-close to high-low range indicator as smoothing variable.
The Indicator
The ratio of open-close to high-low range is a measurement involving calculating the ratio between the absolute close/open price difference and the range (high - low) , now the relationship between high/low and open/close price has been studied in econometrics for some time but there are no reason that the ohlc range ratio may be an indicator of volatility, however we can make the hypothesis that trending markets contain less indecision than ranging market and that indecision is measured by the high/low movements, this is an idea that i've heard various time.
Since the range is always greater than the absolute close/open difference we have a scaled smoothing variable in a range of 0/1, this allow to perform exponential averaging. The ratio of open-close to high-low range is calculated using the vwap of the close/high/low/open price in order to increase the smoothing effect. The vwap tend to smooth more with low time frames than higher ones, since the indicator use vwap for the calculation of its smoothing variable, smoothing may differ depending on the time frame you are in.
1 minute tf
1 hour tf
Conclusion
Making non parametric indicators is quite efficient, but they wont necessarily outperform classical parametric indicators. I also presented a modified version of the ratio of open-close to high-low range who can provide a smoothing variable for exponential averaging. I hope the indicator can help you in any way.
Thanks for reading !
Volume Bubbles & Liquidity Heatmap 30% + biasLuxAlgo gave us an open script, I just primmed it up with the use of Chat GPT:There is no single magic number (like “delta must be 800”) that will guarantee directional follow-through in every market. But you can make a mathematically rigorous filter that gives you a high-probability test — by normalizing the delta against that market’s typical behavior and requiring multiple confirmations. Below is a compact, actionable algorithm you can implement immediately (in your platform or spreadsheet) plus concrete thresholds and the math behind them.
High-IQ rule set (math + trade logic)
Use three independent checks. Only take the trade if ALL three pass.
1) Z-score (statistical significance of the delta)
Compute rolling mean
𝜇
μ and std dev
𝜎
σ of delta on the same timeframe (e.g. 5m) over a lookback window
𝑊
W (suggest
𝑊
=
50
W=50–200 bars).
𝑍
=
delta
bar
−
𝜇
𝑊
𝜎
𝑊
Z=
σ
W
delta
bar
−μ
W
Threshold: require
𝑍
≥
2.5
Z≥2.5 (strong) — accept 2.0 for less strict, 3.0 for very rare signals.
Why: a Z>=2.5 means this delta is an outlier (~<1% one-sided), not normal noise.
2) Relative Imbalance (strength vs total volume)
Compute imbalance ratio:
𝑅
=
∣
delta
bar
∣
volume
bar
R=
volume
bar
∣delta
bar
∣
Threshold: require
𝑅
≥
0.25
R≥0.25 (25% of the bar’s volume is one-sided). For scalping you can tighten to 0.30–0.40.
Why: a big delta with tiny volume isn’t meaningful; this normalizes to participation.
3) Net follow-through over a confirmation window
Look ahead
𝑁
N bars (or check the next bar if you need intrabar speed). Compute cumulative delta and price move:
cum_delta
𝑁
=
∑
𝑖
=
1
𝑁
delta
bar
+
𝑖
cum_delta
N
=
i=1
∑
N
delta
bar+i
price_move
=
close
bar
+
𝑁
−
close
bar
price_move=close
bar+N
−close
bar
Thresholds: require
cum_delta
𝑁
cum_delta
N
has the same sign as the trigger and
∣
cum_delta
𝑁
∣
≥
0.5
×
∣
delta
bar
∣
∣cum_delta
N
∣≥0.5×∣delta
bar
∣, and
price_move
price_move exceeds a minimum meaningful tick amount (instrument dependent). For ES / US30 type futures: price move ≥ 5–10 ticks; for forex pairs maybe 10–20 pips? Use ATR
20
20
×0.05 as a generic minimum.
Why: separates immediate absorption (buy delta then sellers soak it) from genuine continuation.
Bonus check — Structural context (must be satisfied)
Trigger should not occur against a strong structural barrier (VWAP, daily high/low, previous session POC) unless you’re explicitly trading exhaustion/absorption setups.
If signal occurs near resistance and price does not clear that resistance within
𝑁
N bars, treat as probable trap.
Putting it together — final trade decision
Take the long (example):
If
𝑍
≥
2.5
Z≥2.5 and
𝑅
≥
0.25
R≥0.25 and cum_delta_N confirms and no hard resistance above (or you’re willing to trade absorption), then enter.
Place stop: under the low of the last 2–3 bars or X ATR (instrument dependent).
Initial target: risk:reward 1:1 minimum, scale out at 1.5–2R after confirming further delta.
Concrete numeric illustration using your numbers
You saw FOL = 456, then sell reaction with ~350 opposite. How to interpret:
Suppose your 5-min rolling mean
𝜇
μ = 100 and
𝜎
σ=120 (example):
𝑍
=
(
456
−
100
)
/
120
≈
2.97
⇒
statistically big
Z=(456−100)/120≈2.97⇒statistically big
So it passes Z.
If volume on that bar = 2000 contracts:
𝑅
=
456
/
2000
=
0.228
⇒
just below 0.25 threshold
R=456/2000=0.228⇒just below 0.25 threshold
So it fails R (weak participation proportionally), explaining why 456 alone didn’t move price.
Seller came back with 350 opposite soon after — check cum_delta_N:
cum_delta
𝑛
𝑒
𝑥
𝑡
3
≈
456
−
350
=
106
net
cum_delta
next3
≈456−350=106 net
Net is small relative to the initial spike — not convincing follow-through.
Conclusion: despite a big absolute number (456), relative measures and lack of follow-through meant the move failed. That’s exactly why raw numbers alone are unreliable.
Advanced refinement (for elite performance)
Use rolling median + MAD instead of mean/std if delta distribution is skewed.
Scale Z by volume volatility: divide Z by
volume
bar
/
volume
‾
volume
bar
/
volume
to penalize low-volume bars.
Use a signed cumulative delta over micro-windows: compute windowed cumulative delta standardized:
𝑍
cum
=
∑
𝑖
=
0
𝑀
−
1
delta
𝑡
−
𝑖
−
𝑀
𝜇
𝑀
𝜎
Z
cum
=
M
σ
∑
i=0
M−1
delta
t−i
−Mμ
and require
𝑍
cum
≥
3
Z
cum
≥3 for very high confidence.
Add market-depth / DOM confirmation (if available): require that resting ask size above is less than resting bid size below by a factor (i.e. visible liquidity supports the move).
Practical thresholds to start with (tune per instrument)
Lookback
𝑊
W: 100 bars (5m → about a trading day)
Z threshold: 2.5
Imbalance ratio
𝑅
R: ≥ 0.25 (tighten to 0.30 for scalping)
Confirmation window
𝑁
N: next 1–3 bars for intraday scalps; 3–6 bars for short swings
Cum delta confirmation: ≥ 0.5 × initial delta and same sign
Price move confirmation: ≥ 0.03 × ATR20 (or set absolute ticks per instrument)
TL;DR — the single best rule
Don’t chase absolute numbers. Use Z-score of delta + delta/volume ratio + real follow-through. If all three align, odds are heavily in your favor.
If you want, I can:
give you a tiny script (pseudocode or Pine / Python) that computes Z, R, cum_delta_N and flags qualifying bars, or
run the calculation on a sample of your recent bars if you paste a small CSV of time, delta, volume, close.
Which do you want? (I’ll give code right away.)
You said:
give me a percentage of difference where we have a high probability
ChatGPT said:
Thought for 7s
Nice — straight to the point. Here’s a concise, practical set of percentage thresholds (and associated confidence estimates) you can use right now to flag a “high probability” delta signal. I’ll give you three tiers (good / strong / elite), explain what each means, show how to compute it, and give a short example using your 456/2000 bar.
One-line rule
Compute delta percent
𝑃
=
∣
delta
∣
volume
×
100
%
P=
volume
∣delta∣
×100%.
Then require Z-score of delta ≥ 2.5 and P to be at or above the threshold below for the desired confidence tier.
Threshold tiers (percent of bar volume)
Good (high-probability trade candidate)
P ≥ 20–25%
Typical success probability (when combined with Z≥2.5 and no hard structural resistance): ~60–70%.
Use when you want a steady flow of signals with decent edge.
Strong (high confidence)
P ≥ 30–35%
Typical success probability: ~70–80% (with Z≥2.5 + structural alignment).
Fewer signals, higher win-rate. Good default for intraday.
Elite (very high probability / low false positives)
P ≥ 40–50%
Typical success probability: ~80–90% (with Z≥3 and confirmation).
Rare signals. Use for meaningful size or when you need maximum certainty.
Why percentage matters (short)
Absolute delta (456) is meaningless without volume context. A 456 delta on 2,000 volume → P = 456/2000 = 22.8% → sits just below the Good threshold, which matches why it failed: decent but not dominant participation.
Additional required checks (don’t skip these)
To turn P into a reliable filter, always require:
Z-score of the delta ≥ 2.5 (or ≥3 for Elite signals).
No immediate structural barrier (VWAP, strong resistance) that would plausibly absorb the order.
Follow-through: within next N bars (N = 1–3 for scalps) price moves in the same direction by ≥ 0.03×ATR20 (or instrument-specific tick threshold). If this fails, cut fast.
Combine all three and your realized win-rate will approach the probabilities above.
Practical quick checklist (to apply each signal)
Compute P = |delta|/volume. Is P ≥ 30%? (or your chosen tier)
Compute Z = (delta − mean)/std over last 100 bars. Is Z ≥ 2.5?
Is price not pinned under a heavy resistance?
Enter on next bar close (or intrabar on continuation), stop under last 2-bar low (for longs).
If price fails to move ≥ 0.03×ATR20 within 3 bars, exit.
Example (your bar)
delta = 456, volume = 2000 → P = 22.8% → below Good threshold (25%).
Even if Z was high, P failed — explains the failure. You need P ≥ ~30% plus Z≥2.5 to call it a Strong signal.
Final notes (instrument & timeframe)
These percentages were calibrated for futures/US indices and short intraday bars (1–5m).
For FX or low-tick instruments, use absolute ticks + a smaller P threshold (start at 15–20%).
Always backtest on the specific instrument/timeframe and tune thresholds.
If you want, I’ll generate a tiny script (Python or Pine) that calculates P and Z and flags Good/Strong/Elite signals for your chart history so you can see exact historical hit rates. Which language (Python or Pine)?
You said:
so if we have 456 g vs 350 r what pct is that in favour of green?
ChatGPT said:
Perfect — let’s calculate it carefully, digit by digit so we don’t make a slip.
We have:
Green (buy) volume = 456
Red (sell) volume = 350
We want to know what percentage is in favor of green, relative to the total volume.
Step 1. Compute total volume
Total
=
456
+
350
=
806
Total=456+350=806
Step 2. Compute green’s share
\text{Green %} = \frac{456}{806} \times 100
Now do it precisely:
456
÷
806
=
0.565506
456÷806=0.565506 (rounded)
So:
0.565506
×
100
=
56.55
%
0.565506×100=56.55%
Step 3. Compute red’s share (for context)
350
806
=
0.434494
→
43.45
%
806
350
=0.434494→43.45%
Step 4. Compute difference (bias toward green)
56.55
%
−
43.45
%
=
13.10
%
56.55%−43.45%=13.10%
✅ Final answer:
Green = 56.6% of total
Red = 43.4% of total
Bias = +13.1 percentage points in favor of green
So that’s only a 13% advantage to buyers — modest pressure, not a dominant imbalance.
For a high-probability signal (as we discussed earlier), you generally want ≥30% imbalance (e.g. ~65/35 split or stronger).
Original:
''The Volume Bubbles & Liquidity Heatmap indicator is a powerful trading tool designed to give traders a clearer picture of volume dynamics and liquidity distribution across multiple timeframes. By combining dynamic volume bubbles with a liquidity heatmap, this indicator makes it easy to identify areas of price interest, spot market imbalances, and improve decision-making for both scalpers and swing traders.
This trading indicator is ideal for volume traders, price action traders, and liquidity-focused traders who need a clean, multi-dimensional view of buyer/seller activity and the zones where market participants are most active. With full customization over bubble display, timeframes, and visual settings, traders can tailor the tool to fit virtually any trading strategy or market.''
Charles PO3# Charles PO3 - Release Notes
## 📊 Introduction
**Charles PO3** is a powerful PO3 (Power of 3) indicator designed for traders who need to simultaneously observe **Higher Time Frame (HTF)** price action on **Lower Time Frame (LTF)** charts.
This indicator draws multiple HTF candles on the right side of the chart and connects the current price to the HTF **Open, High, and Low** with dynamic projection lines. It helps you:
- View **Daily/Weekly** structure on a minute chart.
- Track HTF key price levels in **real time**.
- Better understand **multi-timeframe trend relationships**.
- Improve **timeframe consistency** in your trading decisions.
**Applicable Markets**: Forex, Futures, Stocks, Cryptocurrencies, and all other financial markets.
This script is based on the (www.google.com) created by (www.google.com).
This indicator is released under TradingViews default license (Mozilla Public License 2.0)
-----
## ✨ Core Features
### 🕐 Smart Timeframe Management
- **Automatic Timeframe Selection**: Automatically selects a suitable HTF based on the current chart period (optionally 1 or 2 levels of progression).
- **Manual Timeframe**: Supports custom selection of any timeframe (15 minutes, 1 hour, 4 hours, Daily, Weekly, etc.).
- **Custom Opening Time**: Supports custom HTF candle opening time and timezone (useful for non-standard trading sessions).
### 📈 Candle Display
- **Configurable Quantity**: Display 1-20 HTF candles (default 5).
- **Three Sizes**: Small, Medium, Large candles available.
- **Two Types**:
- Standard Candles
- Heikin Ashi (Smoothed Candles)
- **Custom Colors**:
- Bullish (Up) Candles: Independent color settings for body, wick, and border.
- Bearish (Down) Candles: Independent color settings for body, wick, and border.
- **Position Adjustment**: Adjustable offset from the right edge of the chart and spacing between candles.
### 🎯 Dynamic Projection Lines
- **Open Price Projection**: Extends from the HTF Open price to the center of the current candle.
- **High/Low Projection**: Extends from the HTF High/Low to the center of the current candle.
- **Real-Time Updates**: Projection lines automatically update their starting point upon price breakthrough.
- **Customizable Style**:
- Three line styles: Solid, Dashed, Dotted.
- Adjustable color and width.
- Independent On/Off switches.
### 🏷️ OHLC Price Labels
- **Real-Time Price Display**: Shows O/H/L/C prices to the right of the latest HTF candle.
- **Six Font Sizes**: Auto, Tiny, Small, Normal, Large, Huge.
- **Follows Candle Movement**: Label position updates dynamically with the candle.
### 🕒 Smart Time Labels
- **Adaptive Format**:
- **Daily**: Displays the day of the week (Mon, Tue, Wed...).
- **Weekly**: Displays Month-Day (10-05, 10-12...).
- **Other Timeframes**: Displays Hour:Minute (14:30, 21:00...).
- **Asset Type Recognition**:
- **Forex/Futures**: Automatically adjusts to display trading days (Mon-Fri).
- **Crypto**: Displays actual date (7 days a week).
- **Center Alignment**: Time label is positioned below the center of the candle.
- **Customizable Color**: Supports adjusting text color (default gray).
### 📊 HTF Data Mode
- **Weekly**: Only use HTF data to generate projections when on a weekly chart.
- **Always**: Always use HTF data.
- **Never**: Always use LTF data to construct the HTF candles.
### 🐛 Debug Tools
- **Debug Table**: Real-time display of indicator status (parameters, candle count, label count, etc.).
- **Pine Logs**: Detailed logs for timestamp conversions and label creation.
- **Optional Switch**: Debug features can be disabled in a production environment to improve performance.
-----
## ⚙️ Parameter Descriptions
### 📁 Settings (Basic Settings)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Timeframe** | Timeframe | Blank (Auto) | Sets the HTF timeframe; leave blank for automatic selection. |
| **Set Automatically** | Boolean | ✅ | Enables automatic timeframe selection. |
| **Two Levels** | Boolean | ✅ | Use 2 levels of progression (e.g., 15min→4H); off uses 1 level (15min→1H). |
| **Number of HTF Candles** | Integer | 5 | Number of HTF candles to display (1-20). |
| **Offset** | Integer | 10 | Bar offset of the candle group from the right edge of the chart. |
| **Size** | Option | Medium | Candle size: Small / Medium / Large. |
| **Type** | Option | Candles | Candle type: Candles (Standard) / Heikin Ashi (Smoothed). |
| **Margin** | Integer | 1 | Spacing between candles (in bars). |
| **Use HTF data to generate candles** | Option | Weekly | Weekly / Always / Never. |
### 🟢 Up Candles (Bullish Candles)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Body** | Color | \#6ba583 | Color for the bullish candle body. |
| **Wick** | Color | Black | Color for the bullish candle wick. |
| **Border** | Color | Black | Color for the bullish candle border. |
### 🔴 Down Candles (Bearish Candles)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Body** | Color | \#d75442 | Color for the bearish candle body. |
| **Wick** | Color | Black | Color for the bearish candle wick. |
| **Border** | Color | Black | Color for the bearish candle border. |
### 📏 Projections (Projection Lines & Labels)
#### Open Price Projection Line
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Open** | Boolean | ✅ | Show Open price projection line. |
| ⚫ **Color** | Color | Translucent Black | Open price line color. |
| **Style** | Option | Dotted | Solid / Dotted / Dashed. |
| **Width** | Integer | 1 | Line width (1-5). |
#### High/Low Projection Lines
| Parameter | Type | Default | Description |
|---|---|---|---|
| **High/Low** | Boolean | ✅ | Show High/Low projection lines. |
| ⚫ **Color** | Color | Translucent Black | High/Low line color. |
| **Style** | Option | Dotted | Solid / Dotted / Dashed. |
| **Width** | Integer | 1 | Line width (1-5). |
#### OHLC Price Labels
| Parameter | Type | Default | Description |
|---|---|---|---|
| **OHLC Prices** | Boolean | ✅ | Show price labels. |
| ⚫ **Color** | Color | Translucent Black | Text color. |
| **Size** | Option | Auto | Auto / Tiny / Small / Normal / Large / Huge. |
#### HTF Time Labels
| Parameter | Type | Default | Description |
|---|---|---|---|
| **HTF Time** | Boolean | ✅ | Show time labels. |
| **Time Label Color** | Color | Gray | Time text color. |
### 🕐 Custom Opening Time (Custom Opening Time)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Use Custom Opening Time?** | Boolean | ❌ | Enable custom opening time. |
| **Timezone** | Option | Exchange | Timezone selection (using Timezone library). |
| **Time (hh:mm)** | Time | 02:00 | Custom opening time (hour:minute). |
### 🐛 Debug (Debugging)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Enable Debug Info** | Boolean | ❌ | Enable Pine Logs for detailed logging. |
| **Show Debug Table** | Boolean | ✅ | Display the debug info table in the top right corner. |
-----
## 🎓 Usage Recommendations
### Recommended Timeframe Combinations
- **1-Minute Chart** → HTF: 15 Minutes
- **5-Minute Chart** → HTF: 1 Hour
- **15-Minute Chart** → HTF: 4 Hours
- **1-Hour Chart** → HTF: Daily
- **4-Hour Chart** → HTF: Weekly
- **Daily Chart** → HTF: Weekly/Monthly
### Best Practices
1. **Trend Trading**: Use the Daily HTF on a 1-Hour chart to ensure you are trading with the higher-timeframe trend.
2. **Support/Resistance**: The HTF High/Low projection lines serve as natural support and resistance levels.
3. **Open Breakout**: Observe the HTF Open price projection line to catch directional breakouts after the open.
4. **Time Synchronization**: Use the time labels to understand the lifecycle stage of the HTF candle.
5. **Multi-Timeframe Confirmation**: Observe multiple HTF candles simultaneously to confirm trend consistency.
-----
## 📌 Version Information
- **Version**: 1.0
- **Pine Script**: v6
- **Dependency Library**: `n00btraders/Timezone/1`
- **Chart Limitations**:
- Max historical bars: 500
- Max Box objects: 500
- Max Label objects: Default (TradingView limit)
-----
**Happy Trading\! 📈**
ICT Concepts(Liquidity, FVG & Liquidity Sweeps)📄 Description:
A Smart Money Concept (SMC)-based utility that blends ICT-style Liquidity Sweeps, Fair Value Gap (FVG) mapping, and Swing Structure proxies – designed for traders seeking clean precision in price imbalance analysis.
⸻
🔍 1. What This Script Does
T his indicator brings together three core Institutional Concepts:
• Liquidity Sweep Detection : Identifies buy/sell-side liquidity grabs (fakeouts) confirmed by volume spikes – a common precursor to institutional order flow shifts.
• Fair Value Gaps (FVGs) : Highlights inefficiencies between price legs using strict ICT-style 3-candle or gap-based rules. These are areas institutions often revisit.
• Swing Structure Proxy (OB Mapping) : Tracks dynamic swing highs/lows to act as proxy zones for potential order blocks and structural boundaries.
It also includes a cooldown-based signal filtering engine to prevent overfitting and noise, helping traders avoid false positives in choppy markets.
⚙️ 2. How It Works (Core Logic)
✅ A. Liquidity Sweep Engine
• Looks back N bars to find Equal Highs or Equal Lows.
• Triggers a signal only if price sweeps the level and closes on the other side with a volume spike.
• Customizable volume threshold (e.g., 1.5x average volume).
• Includes a signal cooldown period to reduce clutter and boost quality.
Bullish Sweep = Price dips below equal lows but closes higher
Bearish Sweep = Price spikes above equal highs but closes lower
Visuals: Signal arrows with alerts (BUY LQ / SELL LQ)
⸻
✅ B. Fair Value Gap (FVG) Zones
• Detects FVGs using:
• Sequential logic: Low > High (bullish), High < Low (bearish)
• Gap logic: Open gaps at bar open
• Dynamic box drawing:
• Automatically extends FVG zones until price fully closes through them.
• Different color coding for bullish (teal) and bearish (orange) gaps.
• Customizable:
• Opacity control
• Option to include/exclude gap-based FVGs
• Hide filled zones
• Limit total zones rendered (for performance)
⸻
✅ C. Swing High/Low Structure
• Uses a lookback period to find latest swing high/low levels.
• Acts as a proxy for Order Block zones or structural shift reference points.
• Plotted as red (high) and green (low) lines.
⸻
🚀 3. How to Use It
• Scalpers and Intraday Traders can use Liquidity Sweep + FVG Confluence to time reversals or catch early entries into trend continuation moves.
• Swing Traders can observe swing OB proxies and recent FVG zones to frame directional bias and target zones.
• Volume-Aware Traders benefit from the volume filter that confirms sweeps are meaningful – not just random stop hunts.
🔔 Set alerts on:
• Bullish Liquidity Sweeps
• Bearish Liquidity Sweeps
You can use this in combination with your own trend filters, or even confluence it with Order Blocks, VWAP, or EMA trend tools.
⸻
💡 What Makes It Original?
• The script doesn’t merely combine standard tools — it builds a cohesive ICT-style detection system using:
• A custom volume-confirmed liquidity sweep filter
• Dynamic FVG rendering with filled logic + performance optimization
• Visual hierarchy to avoid clutter: clean line plots, contextual boxes, and conditional signals
• Highly customizable yet lightweight, making it suitable for fast-paced decision making.
⸻
✅ Notes
• Invite-only script for serious traders interested in Smart Money and ICT concepts.
• Does not repaint signals.
• All visuals are dynamically managed for clarity and performance.
BB_MES Playbook Levels + Auto Alerts (Start/TP1/TP2)Indicator Name: MES Playbook Levels + Auto Alerts (Start/TP1/TP2)
1. Indicator Overview
This is a comprehensive technical analysis tool designed for day traders, specifically for Micro E-mini S&P 500 futures (MES) but applicable to other instruments. Its primary purpose is to automate the drawing of key price levels and to provide timely alerts for a specific trading strategy, often called a "playbook" setup.
The core of the strategy involves identifying a "start" level during the regular trading session. Once the price crosses this level, the indicator automatically projects two take-profit (TP1 and TP2) targets and monitors the price action in relation to these levels.
2. Key Features
Automatic Level Plotting: The indicator plots several critical price levels on the chart, saving the trader from having to draw them manually every day.
Dynamic Start Levels: It offers two methods for establishing the bullish and bearish entry or "start" levels:
Previous Day's High/Low (PDH/PDL): The default setting uses the high and low of the prior trading day as the trigger points for long and short trades.
RTH VWAP Bands: Alternatively, it can calculate the Volume-Weighted Average Price (VWAP) that resets at the start of the Regular Trading Hours (RTH) session and create a "band" around it. The edges of this band then serve as the start levels.
Automated Take-Profit Targets: Upon a cross of a "start" level, the indicator immediately plots two take-profit lines (TP1 and TP2) based on a user-defined point value.
Trade State Management: The script intelligently manages the state of a trade. It knows when a long or short trade is active and will stop looking for new signals until the current trade is concluded (either by hitting TP2 or the end of the session).
Comprehensive Alerts: A major feature is its robust alert system. Traders can set up alerts for a wide variety of events, allowing for less screen time.
Session Highlighting: It specifically monitors the Regular Trading Hours (RTH) session and can also plot the high and low of the overnight (ON) session.
3. On-Chart Visuals
When you apply this indicator to your chart, you will see the following lines and plots:
Previous Day Levels:
PDH (Previous Day High): Plotted as a green line.
PDL (Previous Day Low): Plotted as a red line.
PDC (Previous Day Close): Plotted as a gray line.
Start Levels:
StartBull: A lime green line representing the trigger for a long trade.
StartBear: A maroon line representing the trigger for a short trade.
Take-Profit Levels:
TP1 / TP2: Teal-colored lines that appear only after a StartBull or StartBear level is crossed. TP1 is a dotted line, and TP2 is solid.
Other Levels:
RTH VWAP: A blue line showing the volume-weighted average price for the main session only.
ON High / ON Low: Orange lines showing the high and low points established outside of the RTH session.
4. How It Works: The Trading Logic
Define Session: The script first identifies the Regular Trading Hours (e.g., 9:30 AM to 4:00 PM EST).
Calculate Levels: It calculates the PDH/PDL and the RTH VWAP. Based on user input, it determines the startBullLevel (either PDH or the upper VWAP band) and the startBearLevel (either PDL or the lower VWAP band).
Wait for Signal: During the RTH session, the indicator waits for the live price (close) to cross over the startBullLevel or cross under the startBearLevel.
Initiate Trade State:
If a bullish cross occurs (longStart), it logs the entryPrice, sets the trade state to longActive, and plots the TP1 and TP2 lines above the entry price.
If a bearish cross occurs (shortStart), it does the opposite, plotting TP1 and TP2 below the entry price.
Monitor Trade: While a trade is active, it checks if the price hits TP1 or TP2.
End Trade:
When the price hits the TP2 level, the trade is considered complete. The script clears the TP lines from the chart and resets itself to look for the next start signal.
At the end of the RTH session, any active trade is automatically terminated, and all TP lines are cleared to ensure a clean slate for the next day.
5. Input Settings (Customization)
The user can customize the following parameters in the indicator's settings:
RTH Session: Define the start and end times for the main trading session.
Start from RTH VWAP band: A checkbox to switch between using PDH/PDL or the VWAP band for start levels.
VWAP band offset (pts): If using the VWAP band, this sets how many points away from the VWAP the start levels are drawn.
TP1 (pts): The number of points from the entry price to set the first take-profit target.
TP2 (pts): The number of points for the second take-profit target.
Show Overnight High/Low: A toggle to show or hide the overnight session levels.
6. Configurable Alerts
You can create alerts in TradingView for any of the following conditions generated by the script:
StartBull / StartBear: Triggers when a long or short trade is initiated.
TP1 Hit / TP2 Hit: Triggers when the price reaches the take-profit levels for both long and short trades.
Level Crosses: Separate alerts can be set for when the price crosses the PDH, PDL, PDC, RTH VWAP, ON High, or ON Low. This is useful for general market awareness.
HH/HL/LH/LL Swing MapHH/HL/LH/LL Swing Map
Overview
The HH/HL/LH/LL Swing Map is a Pine Script v6 indicator for TradingView that classifies market structure swings in real time. It identifies and labels Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL) using verified pivot logic, ensuring accuracy without repainting. Custom non-repainting comparisons support reliable structure mapping. Designed for price action traders, it provides a clear, systematic view of evolving swing structure directly on the chart.
How It Works
The indicator uses ta.pivothigh and ta.pivotlow functions with configurable left/right bar settings to verify swing points—delaying labels until full verification for no repaints. Each verified pivot is compared to the previous swing of the same type: If a new high is above the prior high, it is marked as HH; otherwise, LH. If a new low is above the prior low, it is marked as HL; otherwise, LL. Labels and optional triangle markers are plotted on the exact bar where the swing confirms, with customizable offsets in ticks for consistent placement. Users can also enable connection lines between consecutive highs or lows, providing a simple zigzag visualization of structure shifts.
Key Features
• Non-Repainting Logic: Uses verified pivots (bar_index - rightBars) for accurate HH/HL/LH/LL classification.
• Customizable Labels: Adjustable colors, offsets, and visibility for clean chart integration.
• Optional Connection Lines: Connects successive highs and lows to highlight market structure flow.
• Trend Clarity: Quickly distinguishes bullish (HH/HL) and bearish (LH/LL) conditions.
• Alerts Built-In: Alert conditions trigger when new HH, HL, LH, or LL points are verified.
• Lightweight Design: Refined for fast rendering without cluttering the chart.
What It Displays
The indicator plots visual labels and markers for each verified structural pivot (HH, HL, LH, LL). It can also draw connecting lines between pivots to form a simplified swing map of price action. These elements help traders spot shifts in trend direction, continuation, and reversal zones.
Originality
This is an original Pine v6 implementation. It applies verified pivot logic, label/line management, and alert conditions.
Common Ways People Use It
• Price action traders mapping bullish or bearish structure (HH/HL vs. LH/LL).
• Swing traders validating entry/exit signals with structural verification.
• Technical analysts combining market structure with support/resistance or supply/demand zones.
• Day traders monitoring micro-structure shifts for intraday scalping strategies.
Configuration Notes
Users can adjust left/right bar counts for swing verification, label and triangle visibility, line drawing options, and color schemes. Offsets allow labels to remain readable across symbols and timeframes. Alerts may be set for specific structure changes (e.g., “New Higher High Verified”).
Legal Disclaimer
These indicators are for informational and educational purposes only—not investment, financial, or trading advice. Past performance is not indicative of future results; trading involves high risk of loss. Provided "as is" with no warranties. Consult a qualified professional before decisions. By using, you assume all risk and agree to this disclaimer.
ICT Multi-Timeframe Market Structure Tracker [SwissAlgo]ICT Multi-Timeframe Market Structure Tracker
Tracks the ICT market structure across three core timeframes (1-Week, 1-Day, 1-Hour) simultaneously.
----------------------------------------------------------------------
Why this Indicator?
You know market structure matters, whether you trade stocks, Forex, commodities, or crypto.
You've studied ICT concepts - " Change of Character ", " Break of Structure ", " Premium/discount zones ". You understand that multi-timeframe alignment is where the edge lives.
But here's what's probably happening while you apply the ICT concepts for your trading decisions:
You're manually drawing structural highs and lows across three timeframes
You're calculating Fibonacci retracements by hand for each timeframe
You're switching between weekly, daily, and hourly charts, trying to remember where each pivot was, trying to detect the critical events you're waiting for
By the time you've mapped it all out, the setup is gone. Or worse, you missed that the 1-hour just broke the structure while you were checking the weekly bias.
What about seeing all three timeframes at once instead? You need to know immediately when the price enters a premium or discount zone. You need alerts that fire when structure breaks or character changes - across all timeframes - without babysitting your screen.
----------------------------------------------------------------------
The Indicator, at a Glance
This indicator:
tracks ICT market structure across three core timeframes (1-Week, 1-Day, 1-Hour) simultaneously .
automatically plots Fibonacci retracement levels from your defined structural pivots
monitors price position (during retracements) in real-time
sends consolidated alerts when actionable events occur on any timeframe
The 1-Week View: Mid-Term Trend Bias for lower timeframes
The 1-Day View: Swings nested within the 1-Week Structure
The 1-Hour View: Swings nested within the 1-Day Structure
One glance tells you:
* Current trend direction per timeframe
* Exact Fib zone price is trading right now
* Whether the structure just broke or the character changed
* If you're in a potential long/short setup zone
The indicator helps you reduce chart-hopping, manual calculations, and minimize the missed structural shifts.
----------------------------------------------------------------------
Who is this for?
This tool is built for day traders who understand ICT concepts and need efficient multi-timeframe structure tracking. If you know what a Change of Character is, why 0.382-0.5 retracements matter in uptrends, and how to trade external structure, this indicator eliminates the manual structure tracking so you can focus on confirming and executing your trading tactics.
New to ICT? This indicator assumes foundational knowledge of the Inner Circle Trader methodology developed by Michael J. Huddleston. Before using this tool, familiarize yourself with concepts like market structure breaks, premium/discount arrays, and liquidity engineering. The ICT framework offers a unique perspective on institutional order flow and price action - but this indicator is designed for those already applying these concepts, not learning them for the first time.
Critical Skill Required : You must understand the difference between external structure (key swing highs/lows that define market direction) and internal structure (minor fluctuations within the range).
Selecting incorrect pivots - such as marking internal noise instead of true structural points - will generate false signals and undermine the entire analysis. This indicator tracks structure based on YOUR inputs. If those inputs are wrong, every Fibonacci level, alert, and bias signal will be wrong. Learn to identify clean structural breaks before using this tool.
Trading Experience Matters: This tool tracks structure and fires alerts, but interpreting those signals requires understanding context, confluences, and risk management. If you're early in your trading journey, consider this a professional-grade instrument that becomes powerful once you have the conceptual foundation to use it effectively.
----------------------------------------------------------------------
How It Works
Step 1: Define Your Structure
You, the ICT expert or student, define the structural high and low for each timeframe, with their exact dates. This empowers you to control the analysis.
Based on your entries, the indicator establishes trend direction by timeframe and calculates Fibonacci retracement levels automatically.
* Structural High/Low: Key swing points that define external structure per ICT methodology
* Auto-Validation: Built-in autoscan feature confirms your pivot entries match actual price extremes
* Deterministic Behavior: Date stamps ensure the indicator behaves consistently across all sessions
Step 2: Monitor The Tables
Two tables provide a structural context:
Multi-Timeframe Analysis Table (top-right):
Current close, high, low, and 0.5 Fib for all three timeframes
Trend direction (↑/↓)
Days since structure established (i.e., "age" or maturity)
Current Fibonacci zone
Real-time alerts: Trend changes, breakouts, and trade bias signals
Detailed Fibonacci Table (middle-right):
All nine Fib retracement levels (1.0 to 0.0) for the selected timeframe
Exact price at each level
Percentage distance from current price
Visual marker showing current position
Step 3: Monitor The Chart
Visual elements show structure at a glance:
Fibonacci Retracement Zones: Color-coded bands show premium (red), discount (green), and equilibrium (gray) areas based on trend direction
Structural Lines: Red (high) and green (low) horizontal lines mark your defined pivots with automatic fill showing the current range (based on higher timeframe pivots)
Pivot Dots: Optional small markers highlight potential structural turning points on your current timeframe (reference only - always validate pivots yourself)
Trend Indicator: Top-center banner displays the selected timeframe's current trend
Auto-pivot points
Step 4: Get Alerts and Decide the Way Forward
Set one alert on the 1-hour chart only (if you set the alert on other timeframes, you may get delayed feedback).
You'll receive notifications when ANY of these events occur on ANY timeframe:
* Change of Character (ChoC): Trend reversal confirmed by price breaking the opposite structural level
* Break of Structure (BoS): Continuation confirmed by price breaking the same-direction structural level
* Trade Bias Signals: Price entering key Fibonacci zones (0.382-0.5 for longs in uptrend, 0.5-0.618 for shorts in downtrend, with + and ++ variants for deeper retracements)
* Reversal Warnings: Price entering extreme zones (0.882-1.0 or 0.0-0.118), suggesting potential trend exhaustion and reversal towards the opposite direction
All alerts fire once per bar close with a consolidated message showing which timeframes triggered and what conditions were met.
----------------------------------------------------------------------
Understanding the 3 Timeframes Hierarchy
The three timeframes may be conceived as nested layers of structure:
* 1-Week (Macro Bias) : May help you determine your core directional bias (long/short) in a mid-term perspective. The 1-Week TF may operate as your highest-conviction filter and help you contextualize shorter-term market moves (which may align or misalign with the trend appearing on such a timeframe).
* 1-Day (Swing Structure) : Operates within the weekly range. The daily structure can contradict the weekly structure temporarily (due to retracements, consolidations). This is where you may identify intermediate swing opportunities.
* 1-Hour (Execution Structure) : Operates within the daily range. It may help you identify entry timing and short-term bias. Can show opposite trends during retracements, and some traders look for alignment with higher timeframes as part of their setup criteria.
Example: Weekly uptrend (bullish bias) → Daily pulls back into downtrend (retracement phase) → Hourly shows uptrend resumption (this may be interpreted as an entry signal). All three trends can differ simultaneously, but when all three align (in one direction or another), you may start evaluating your moves.
----------------------------------------------------------------------
Using the Tool effectively
When this indicator signals a potential setup (entering key Fibonacci zones, structure breaks, or bias shifts), treat it as a starting point for deeper analysis, not a direct entry signal.
Before executing, consider using additional tools to refine timing:
Fair Value Gaps (FVG) : Identify imbalances where the price moved too quickly, leaving potential fill zones
Order Blocks : Locate the last opposing candle before a strong move - often institutional entry points
Liquidity Zones : Map where stop losses likely cluster (equal highs/lows, round numbers)
Premium/Discount Confirmation: Verify you're buying at a discount or selling at a premium relative to the current range
Session Timing/Kill Zones : Align entries with high-liquidity sessions (London/New York opens)
This indicator shows you where the structure sits and when it shifts. Your job is to combine that context with precise entry models. The alerts narrow your focus to high-probability zones - then you apply your edge within those zones.
----------------------------------------------------------------------
How to Set Up Alerts
This indicator monitors all three timeframes simultaneously and fires consolidated alerts when any condition triggers. Follow these steps to configure alerts properly:
Step 1: Set Your Chart to the 1-Hour Timeframe
Alerts must be created on the 1-hour chart for optimal timing
Do not use higher timeframes (4H, 1D, 1W) or alerts may be delayed
Lower timeframes (15M, 5M) will work but may generate more frequent notifications
Step 2: Open the Alert Menu
Click the "Alert" button (clock icon) in the top toolbar
Or use keyboard shortcut: Alt+A (Windows) / Option+A (Mac)
Step 3: Configure Alert Settings
Condition: Select "ICT Multi-Timeframe Market Structure Tracker "
Alert Type: Choose "Any alert() function call"
Options: Select "Once Per Bar Close"
Expiration: Set to "Open-ended alert" (no expiration)
Alert Name: Choose a descriptive name (e.g., "BTC Market Structure Alerts")
Step 4: Configure Notifications
Notification Methods: Check your preferred channels (app notification, email, webhook, etc.)
Sound: Optional — choose alert sound if desired
Step 5: Create Alert
Click the "Create" button
Alert is now active and will monitor all three timeframes
Important Notes:
You only need ONE alert setup total — it monitors 1W, 1D, and 1H simultaneously
Alert messages show which timeframe(s) triggered and what conditions were met
Alerts fire once per bar close to avoid mid-bar noise
If you change your structural pivot inputs, the alert continues working with new parameters
Example Alert Message:
BTC Market Structure Alert:
🟢 1D Bullish BoS
📈 1H Long Setup (0.382-0.5)
This tells you the 1-Day broke structure bullishly AND the 1-Hour entered a long setup zone — both events happened on the same bar close.
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Key Features
* Tracks 1-Week, 1-Day, and 1-Hour structure simultaneously
* Automatic Fibonacci retracement calculation (9 levels + extensions up or down, depending on timeframe trend)
* Real-time Change of Character and Break of Structure detection
* Color-coded premium/discount zone visualization
* Multi-condition alerts across all timeframes (single alert setup required)
* Autoscan validation to confirm manual pivot entry accuracy
* Timezone-adjustable for global markets
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Important Notes
* Requires ICT Knowledge: This is not a plug-and-play system. Understanding market structure, liquidity concepts, and Fibonacci confluence is essential for effective use.
* Manual Structure Definition: You define the structural pivots. The indicator tracks and alerts - it doesn't make trading decisions.
* Chart Timeframe: Set alerts on the 1-hour chart for optimal timing across all three monitored timeframes.
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Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial, investment, or trading advice.
The indicator:
* Makes no guarantees about future market performance
* Cannot predict market movements with certainty
* May generate false indications
* Relies on historical patterns that may not repeat
* Should not be used as the sole basis for trading decisions
Users are responsible for:
* Conducting independent research and analysis
* Understanding the risks of trading
* Making their own investment/divestment decisions
* Managing position sizes and risk exposure appropriately
Trading involves substantial risk and may not be suitable for all investors. Past performance does not guarantee future results. Users should only invest what they can afford to lose and consult qualified professionals before making financial decisions. The indicator’s assumptions may be invalidated by changing market conditions.
By using this tool, users acknowledge these limitations and accept full responsibility for their trading decisions.
Opening Range IndicatorComplete Trading Guide: Opening Range Breakout Strategy
What Are Opening Ranges?
Opening ranges capture the high and low prices during the first few minutes of market open. These levels often act as key support and resistance throughout the trading day because:
Heavy volume occurs at market open as overnight orders execute
Institutional activity is concentrated during opening minutes
Price discovery happens as market participants react to overnight news
Psychological levels are established that traders watch all day
Understanding the Three Timeframes
OR5 (5-Minute Range: 9:30-9:35 AM)
Most sensitive - captures immediate market reaction
Quick signals but higher false breakout rate
Best for scalping and momentum trading
Use for early entry when conviction is high
OR15 (15-Minute Range: 9:30-9:45 AM)
Balanced approach - most popular among day traders
Moderate sensitivity with better reliability
Good for swing trades lasting several hours
Primary timeframe for most strategies
OR30 (30-Minute Range: 9:30-10:00 AM)
Most reliable but slower signals
Lower false breakout rate
Best for position trades and trend following
Use when looking for major moves
Core Trading Strategies
Strategy 1: Basic Breakout
Setup:
Wait for price to break above OR15 high or below OR15 low
Enter on the breakout candle close
Stop loss: Opposite side of the range
Target: 2-3x the range size
Example:
OR15 range: $100.00 - $102.00 (Range = $2.00)
Long entry: Break above $102.00
Stop loss: $99.50 (below OR15 low)
Target: $104.00+ (2x range size)
Strategy 2: Multiple Confirmation
Setup:
Wait for OR5 break first (early signal)
Confirm with OR15 break in same direction
Enter on OR15 confirmation
Stop: Below OR30 if available, or OR15 opposite level
Why it works:
Multiple timeframe confirmation reduces false signals and increases probability of sustained moves.
Strategy 3: Failed Breakout Reversal
Setup:
Price breaks OR15 level but fails to hold
Wait for re-entry into the range
Enter reversal trade toward opposite OR level
Stop: Recent breakout high/low
Target: Opposite side of range + extension
Key insight: Failed breakouts often lead to strong moves in the opposite direction.
Advanced Techniques
Range Quality Assessment
High-Quality Ranges (Trade these):
Range size: 0.5% - 2% of stock price
Clean boundaries (not choppy)
Volume spike during range formation
Clear rejection at range levels
Low-Quality Ranges (Avoid these):
Very narrow ranges (<0.3% of stock price)
Extremely wide ranges (>3% of stock price)
Choppy, overlapping candles
Low volume during formation
Volume Confirmation
For Breakouts:
Look for volume spike (2x+ average) on breakout
Declining volume often signals false breakout
Rising volume during range formation shows interest
Market Context Filters
Best Conditions:
Trending market days (SPY/QQQ with clear direction)
Earnings reactions or news-driven moves
High-volume stocks with good liquidity
Volatility above average (VIX considerations)
Avoid Trading When:
Extremely low volume days
Major economic announcements pending
Holidays or half-days
Choppy, sideways market conditions
Risk Management Rules
Position Sizing
Conservative: Risk 0.5% of account per trade
Moderate: Risk 1% of account per trade
Aggressive: Risk 2% maximum per trade
Stop Loss Placement
Inside the range: Quick exit but higher stop-out rate
Outside opposite level: More room but larger risk
ATR-based: 1.5-2x Average True Range below entry
Profit Taking
Target 1: 1x range size (take 50% off)
Target 2: 2x range size (take 25% off)
Runner: Trail remaining 25% with moving stops
Specific Entry Techniques
Breakout Entry Methods
Method 1: Immediate Entry
Enter as soon as price closes above/below range
Fastest entry but highest false signal rate
Best for strong momentum situations
Method 2: Pullback Entry
Wait for breakout, then pullback to range level
Enter when price bounces off former resistance/support
Better risk/reward but may miss some moves
Method 3: Volume Confirmation
Wait for breakout + volume spike
Enter after volume confirmation candle
Reduces false signals significantly
Multiple Timeframe Entries
Aggressive: OR5 break → immediate entry
Conservative: OR5 + OR15 + OR30 all align → enter
Balanced: OR15 break with OR30 support → enter
Common Mistakes to Avoid
1. Trading Poor-Quality Ranges
❌ Don't trade ranges that are too narrow or too wide
✅ Focus on clean, well-defined ranges with good volume
2. Ignoring Volume
❌ Don't chase breakouts without volume confirmation
✅ Always check for volume spike on breakouts
3. Over-Trading
❌ Don't force trades when ranges are unclear
✅ Wait for high-probability setups only
4. Poor Risk Management
❌ Don't risk more than planned or use tight stops in volatile conditions
✅ Stick to predetermined risk levels
5. Fighting the Trend
❌ Don't fade breakouts in strongly trending markets
✅ Align trades with overall market direction
Daily Trading Routine
Pre-Market (8:00-9:30 AM)
Check overnight news and earnings
Review major indices (SPY, QQQ, IWM)
Identify potential opening range candidates
Set alerts for range breakouts
Market Open (9:30-10:00 AM)
Watch opening range formation
Note volume and price action quality
Mark key levels on charts
Prepare for breakout signals
Trading Session (10:00 AM - 4:00 PM)
Execute breakout strategies
Manage existing positions
Trail stops as profits develop
Look for additional setups
Post-Market Review
Analyze winning and losing trades
Review range quality vs. outcomes
Identify improvement areas
Prepare for next session
Best Stocks/ETFs for Opening Range Trading
Large Cap Stocks (Best for beginners):
AAPL, MSFT, GOOGL, AMZN, TSLA
High liquidity, predictable behavior
Good range formation most days
ETFs (Consistent patterns):
SPY, QQQ, IWM, XLF, XLE
Excellent liquidity
Clear range boundaries
Mid-Cap Growth (Advanced traders):
Stocks with good volume (1M+ shares daily)
Recent news catalysts
Clean technical patterns
Performance Optimization
Track These Metrics:
Win rate by range type (OR5 vs OR15 vs OR30)
Average R/R (risk vs reward ratio)
Best performing market conditions
Time of day performance
Continuous Improvement:
Keep detailed trade journal
Review failed breakouts for patterns
Adjust position sizing based on win rate
Refine entry timing based on backtesting
Final Tips for Success
Start small - Paper trade or use tiny positions initially
Focus on quality - Better to miss trades than take bad ones
Stay disciplined - Stick to your rules even during losing streaks
Adapt to conditions - What works in trending markets may fail in choppy conditions
Keep learning - Markets evolve, so should your approach
The opening range strategy is powerful because it captures natural market behavior, but like all strategies, it requires practice, discipline, and proper risk management to be profitable long-term.
The Black Sheep v1.0Black Sheep v1.0 is a comprehensive, multi-signal indicator designed to identify statistically significant market anomalies that often signal the activity of institutional traders or "smart money." The core principle is that institutional footprints are visible not in typical price action but in the unusual and statistically improbable events that deviate from the norm.
This indicator does not provide simple buy or sell signals. Instead, it acts as a powerful scanner, alerting you to moments of potential market manipulation, absorption, exhaustion, or stealth accumulation. Each signal is grounded in a statistical comparison of the current bar's price range and volume against a recent baseline, making it adaptive to any market and timeframe.
The name "Black Sheep" reflects the indicator's purpose: to find the bars that stand out from the flock—the anomalies that tell a deeper story about market dynamics.
Features
8 Unique Signals: Identifies distinct market phenomena, from stop hunts to absorption events.
Statistically Driven: Uses standard deviations for volume and range to define "unusual" activity, adapting automatically to changing market volatility.
Fully Customizable: Every parameter for every signal can be tweaked, allowing you to fine-tune the indicator's sensitivity to your specific trading instrument and style.
Clear Visual Alerts: Signals are plotted as clean, non-intrusive labels on the chart for immediate recognition.
Comprehensive Tooltips: Every setting is explained directly in the indicator's menu, making configuration intuitive.
The Signals Explained
Each of the 8 signals is designed to detect a specific type of market behavior.
1. Ghost Spike (Stop Hunt)
Concept: A sharp, sudden spike that breaks a recent high or low, only to reverse quickly. Crucially, this move happens on low volume, suggesting it lacks genuine market conviction. This is the classic signature of a stop hunt, designed to trigger stop-loss orders and trap retail traders.
Logic: Identifies bars with a very large range, a tiny body (wick-dominated), and volume that is statistically lower than average.
2. Absorption Candle (Iceberg Order)
Concept: Indicates a major battle between buyers and sellers at a key price level. This candle is characterized by massive volume but a very small body. It suggests a large passive order (an "iceberg order") is absorbing all the aggressive market orders, preventing price from moving. This is a sign of a strong support or resistance level being defended.
Logic: Detects bars with statistically massive volume but a price range that is mostly wicks.
3. VWAP Slingshot
Concept: The Volume-Weighted Average Price (VWAP) is a key benchmark for institutional traders. This signal identifies a sharp, high-volume rejection from the VWAP line. It signifies that price tested this important level and was forcefully "slingshotted" away, validating its importance as a dynamic support/resistance zone.
Logic: Triggers on a bar that touches the VWAP, has a long rejection wick (measured in ATRs), and is accompanied by high volume.
4. Session Close Markup
Concept: Highlights aggressive, high-volume buying or selling that occurs in the final minutes of a major trading session (e.g., the NYSE close). This can indicate institutions "marking up" or "marking down" the closing price for portfolio management or positioning themselves for the next session.
Logic: Fires within a user-defined window before the session close on candles with a large, decisive body and high volume.
5. Dawn Raid (Pre-Market Spike)
Concept: A "Dawn Raid" is a sudden burst of high-volume activity during the typically quiet and illiquid pre-market session. This is often the first sign of significant interest in an asset, usually triggered by news, an earnings release, or a large fund building a position before the market opens.
Logic: Detects candles in the pre-market session with volume that is multiple standard deviations above the average pre-market volume.
6. Liquidity Vacuum
Concept: Identifies periods of extremely low volume and price volatility. In these "vacuums," the market is thin, and even small orders can cause disproportionate price movement. These periods often precede explosive, high-volume breakouts, acting as the "calm before the storm."
Logic: Flags candles where both volume and range are a small fraction of their recent averages (ATR and average volume).
7. Delta Divergence
Concept: A classic pattern that signals weakening momentum. A bearish divergence occurs when price makes a higher high, but the candle's body ("delta") fails to confirm it, suggesting the upward thrust is losing power. A bullish divergence occurs when price makes a lower low, but the delta shows less downward conviction.
Logic: Compares recent price pivot highs/lows with the corresponding pivots of the candle's delta (close - open).
8. Fake Breakout (High Volume)
Concept: This signal captures a failed breakout attempt that occurs on high volume. Unlike the low-volume Ghost Spike, this pattern shows that there was a genuine attempt to break a level, but it was met with even stronger opposing force. This creates a powerful trap and often leads to a strong reversal.
Logic: Identifies a large-range breakout candle with a small body and high volume.
How to Use
The Black Sheep indicator should be used as a confluence tool, not a standalone system. The signals it generates are points of interest that warrant further investigation. Use them to:
Confirm or deny a trade thesis based on your existing strategy.
Identify potential market tops and bottoms.
Spot institutional trapping and positioning.
Understand the context behind price movements.
For best results, combine these signals with analysis of market structure, support/resistance levels, order flow, and other contextual clues. Adjust the input settings for each signal to match the volatility profile of the asset you are trading.
Smart Money Flow TrackerSmart Money Flow Tracker - Liquidity & Fair Value Gap Indicator
Overview
The Smart Money Flow Tracker is a comprehensive Pine Script indicator designed to identify and analyze institutional trading patterns through liquidity prints and Fair Value Gaps (FVGs). This advanced tool combines multiple analytical approaches to help traders understand where smart money is operating in the market, providing crucial insights for better trade timing and market structure analysis.
Core Functionality
1. Liquidity Prints Detection
The indicator identifies liquidity prints by analyzing pivot highs and lows that represent potential areas where institutional orders may be resting. Key features include:
Pivot-Based Analysis: Uses configurable pivot lengths (default 5) to identify significant highs and lows
Volume Confirmation: Optional volume filter ensures liquidity prints occur during periods of significant trading activity
Dynamic Labeling: Visual markers on chart showing liquidity print locations with customizable colors
Success Rate Tracking: Monitors how often liquidity prints lead to meaningful price reactions
2. Fair Value Gap (FVG) Analysis with Volume Integration
Advanced FVG detection that goes beyond basic gap identification:
Three-Bar Pattern Recognition: Identifies gaps where the high of bar 1 is below the low of bar 3 (bullish) or low of bar 1 is above high of bar 3 (bearish)
Volume-Enhanced Detection: Incorporates comprehensive volume analysis including:
Average volume calculation over configurable periods
Total volume across the 3-bar FVG pattern
Dominant volume bar identification
Volume ratio calculations for strength assessment
Volume Threshold Filtering: Optional minimum volume requirements to filter out low-conviction FVGs
Visual Enhancement: FVG boxes with volume-based coloring and detailed volume labels
3. Comprehensive Statistics Dashboard
Real-time statistics table displaying:
Total liquidity prints detected
Success rate percentage with dynamic color coding
Volume filter status
Total Fair Value Gaps identified
High-volume FVG count and percentage
All metrics update in real-time as new data becomes available
4. Advanced Alert System
Multiple alert conditions for different scenarios:
Standard liquidity print detection
Volume-confirmed liquidity prints
Bullish and bearish FVG formation
High-volume FVG alerts for institutional-grade setups
Key Input Parameters
Display Controls
Show Liquidity Prints: Toggle main functionality on/off
Show Statistics Table: Control visibility of the analytics dashboard
Show Fair Value Gaps: Enable/disable FVG detection and display
Technical Settings
Pivot Length: Adjusts sensitivity of liquidity print detection (1-20 range)
Volume Confirmation: Requires above-average volume for liquidity print validation
Volume Lookback: Period for calculating average volume (5-50 bars)
FVG Volume Settings
Show FVG Volume Info: Display detailed volume metrics on FVG labels
FVG Volume Threshold: Minimum volume multiplier for high-volume FVG classification
FVG Volume Average Period: Lookback period for FVG volume calculations
Visual Customization
Bullish/Bearish Colors: Separate color schemes for different market directions
Text Colors: Bright lime green for optimal visibility on all background types
Table Positioning: Flexible placement options for the statistics dashboard
Trading Applications & Use Cases
1. Institutional Order Flow Analysis
Liquidity Hunting: Identify areas where institutions may be targeting retail stops
Smart Money Tracking: Follow institutional footprints through volume-confirmed liquidity prints
Market Structure Understanding: Recognize key levels where large orders are likely resting
2. Fair Value Gap Trading Strategies
Gap Fill Trading: Trade the statistical tendency of FVGs to get filled
Volume-Confirmed Entries: Use high-volume FVGs as higher-probability trade setups
Institutional FVG Recognition: Focus on FVGs with dominant volume bars indicating institutional participation
3. Multi-Timeframe Analysis
Higher Timeframe Context: Use on daily/weekly charts to identify major institutional levels
Intraday Precision: Apply to lower timeframes for precise entry and exit timing
Cross-Timeframe Confirmation: Combine signals across multiple timeframes for enhanced accuracy
4. Risk Management Applications
Stop Loss Placement: Use liquidity print levels as logical stop loss areas
Position Sizing: Adjust position sizes based on volume confirmation and success rates
Trade Filtering: Use statistics dashboard to assess current market conditions
Technical Logic & Methodology
Liquidity Print Algorithm
Pivot Identification: Scans for pivot highs/lows using the specified lookback period
Volume Validation: Optionally confirms prints occur during above-average volume periods
Success Tracking: Monitors subsequent price action to calculate effectiveness rates
Dynamic Updates: Continuously updates statistics as new data becomes available
FVG Detection Process
Pattern Recognition: Identifies 3-bar patterns with qualifying gaps
Volume Analysis: Calculates comprehensive volume metrics across the pattern
Strength Assessment: Determines volume ratios and dominant bars
Classification: Categorizes FVGs based on volume thresholds and characteristics
Visual Representation: Creates boxes and labels with volume-based styling
Statistical Framework
Real-time Calculations: All metrics update with each new bar
Percentage-based Metrics: Success rates and volume confirmations shown as percentages
Color-coded Feedback: Visual indicators for quick assessment of current conditions
Historical Tracking: Maintains running totals throughout the session
Best Practices for Usage
1. Parameter Optimization
Start with default settings and adjust based on market conditions
Lower pivot lengths for more sensitive detection on volatile instruments
Higher volume thresholds for cleaner signals in high-volume markets
2. Market Context Consideration
Combine with broader market structure analysis
Consider economic events and news that may affect institutional flow
Adjust expectations based on market volatility and liquidity conditions
3. Integration with Other Analysis
Use alongside support/resistance levels for confluence
Combine with momentum indicators for timing confirmation
Integrate with volume profile analysis for additional context
Conclusion
The Smart Money Flow Tracker represents a sophisticated approach to institutional flow analysis, combining traditional liquidity concepts with modern volume analytics. By providing both visual signals and comprehensive statistics, it enables traders to make more informed decisions based on where smart money is likely operating in the market. The indicator's flexibility and customization options make it suitable for various trading styles and timeframes, from scalping to position trading.
Trend Bars with Okuninushi Line Filter# Trend Bars with Okuninushi Line Filter: A Powerful Trading Indicator
## Introduction
The **Trend Bars with Okuninushi Line Filter** is an innovative technical indicator that combines two powerful concepts: trend bar analysis and the Okuninushi Line filter. This indicator helps traders identify high-quality trending moves by analyzing candle body strength relative to the overall price range while ensuring the price action aligns with the dominant market structure.
## What Are Trend Bars?
Trend bars are candles where the body (distance between open and close) represents a significant portion of the total price range (high to low). These bars indicate strong directional momentum with minimal indecision, making them valuable signals for trend continuation.
### Key Characteristics:
- **Strong directional movement**: Large body relative to total range
- **Minimal upper/lower shadows**: Shows sustained pressure in one direction
- **High conviction**: Represents decisive market action
## The Okuninushi Line Filter
The Okuninushi Line, also known as the Kijun Line in Ichimoku analysis, is calculated as the midpoint of the highest high and lowest low over a specified period (default: 52 periods).
**Formula**: `(Highest High + Lowest Low) / 2`
This line acts as a dynamic support/resistance level and trend filter, helping to:
- Identify the overall market bias
- Filter out counter-trend signals
- Provide confluence for trade entries
## How the Indicator Works
The indicator combines these two concepts with the following logic:
### Bull Trend Bars (Green)
A candle is colored **green** when ALL conditions are met:
1. **Bullish candle**: Close > Open
2. **Strong body**: |Close - Open| ≥ Threshold × (High - Low)
3. **Above trend filter**: Close > Okuninushi Line
### Bear Trend Bars (Red)
A candle is colored **red** when ALL conditions are met:
1. **Bearish candle**: Close < Open
2. **Strong body**: |Close - Open| ≥ Threshold × (High - Low)
3. **Below trend filter**: Close < Okuninushi Line
### Neutral Bars (Gray)
All other candles that don't meet the complete criteria are colored **gray**.
## Customizable Parameters
### Trend Bar Threshold
- **Range**: 10% to 100%
- **Default**: 75%
- **Purpose**: Controls how "strong" a candle must be to qualify as a trend bar
**Threshold Effects:**
- **Low (10-30%)**: More sensitive, catches smaller trending moves
- **Medium (50-75%)**: Balanced approach, filters out most noise
- **High (80-100%)**: Very selective, only captures the strongest moves
### Okuninushi Line Length
- **Default**: 52 periods
- **Purpose**: Determines the lookback period for calculating the midpoint
- **Common Settings**:
- 26 periods: More responsive to recent price action
- 52 periods: Standard setting, good balance
- 104 periods: Longer-term trend perspective
## Trading Applications
### 1. Trend Continuation Signals
- **Green bars**: Look for bullish continuation opportunities
- **Red bars**: Consider bearish continuation setups
- **Gray bars**: Exercise caution, mixed signals
### 2. Market Structure Analysis
- Clusters of same-colored bars indicate strong trends
- Alternating colors suggest choppy, indecisive markets
- Transition from red to green (or vice versa) may signal trend changes
### 3. Entry Timing
- Use colored bars as confirmation for existing trade setups
- Wait for color alignment with your market bias
- Avoid trading during predominantly gray periods
### 4. Risk Management
- Gray bars can serve as early warning signs of weakening trends
- Color changes might indicate appropriate exit points
- Use in conjunction with other risk management tools
## Advantages
1. **Dual Filtering**: Combines momentum (trend bars) with trend direction (Okuninushi Line)
2. **Visual Clarity**: Immediate visual feedback through candle coloring
3. **Customizable**: Adjustable parameters for different trading styles
4. **Versatile**: Works across multiple timeframes and instruments
5. **Objective**: Rule-based system reduces subjective interpretation
## Limitations
1. **Lagging Nature**: Based on historical price data
2. **False Signals**: Can produce whipsaws in choppy markets
3. **Parameter Sensitivity**: Requires optimization for different instruments
4. **Market Conditions**: May be less effective in ranging markets
## Best Practices
### Optimization Tips:
- **Volatile Markets**: Use higher thresholds (80-90%)
- **Steady Trends**: Use moderate thresholds (60-75%)
- **Short-term Trading**: Shorter Okuninushi Line periods (26)
- **Long-term Analysis**: Longer Okuninushi Line periods (104+)
### Combination Strategies:
- Pair with volume indicators for confirmation
- Use alongside support/resistance levels
- Combine with other trend-following indicators
- Consider market context and overall trend direction
## Conclusion
The Trend Bars with Okuninushi Line Filter offers traders a sophisticated yet intuitive way to identify high-quality trending moves. By combining the momentum characteristics of trend bars with the directional filter of the Okuninushi Line, this indicator helps traders focus on the most promising opportunities while avoiding low-probability setups.
Remember that no single indicator should be used in isolation. Always consider market context, risk management, and other technical factors when making trading decisions. The true power of this indicator lies in its ability to quickly highlight periods of strong, aligned price action – exactly what trend traders are looking for.
---
*Disclaimer: This article is for educational purposes only and should not be considered as financial advice. Always conduct your own research and consider your risk tolerance before making any trading decisions.*
Trend FriendTrend Friend — What it is and how to use it
I built Trend Friend to stop redrawing the same trendlines all day. It automatically connects confirmed swing points (fractals) and keeps the most relevant lines in front of you. The goal: give you clean, actionable structure without the guesswork.
What it does (in plain English)
Finds swing highs/lows using a Fractal Period you choose.
Draws auto-trendlines between the two most recent confirmed highs and the two most recent confirmed lows.
Colours by intent:
Lines drawn from highs (potential resistance / bearish) = Red
Lines drawn from lows (potential support / bullish) = Green
Keeps the chart tidy: The newest lines are styled as “recent,” older lines are dimmed as “historical,” and it prunes anything beyond your chosen limit.
Optional crosses & alerts: You can highlight when price closes across the most recent line and set alerts for new lines formed and upper/lower line crosses.
Structure labels: It tags HH, LH, HL, LL at the swing points, so you can quickly read trend/rotation.
How it works (under the hood)
A “fractal” here is a confirmed pivot: the highest high (or lowest low) with n bars on each side. That means pivots only confirm after n bars, so signals are cleaner and less noisy.
When a new pivot prints, the script connects it to the prior pivot of the same type (high→high, low→low). That gives you one “bearish” line from highs and one “bullish” line from lows.
The newest line is marked as recent (brighter), and the previous recent line becomes historical (dimmed). You can keep as many pairs as you want, but I usually keep it tight.
Inputs you’ll actually use
Fractal Period (n): this is the big one. It controls how swingy/strict the pivots are.
Lower n → more swings, more lines (faster, noisier)
Higher n → fewer swings, cleaner lines (slower, swing-trade friendly)
Max pair of lines: how many pairs (up+down) to keep on the chart. 1–3 is a sweet spot.
Extend: extend lines Right (my default) or Both ways if you like the context.
Line widths & colours: recent vs. historical are separate so you can make the active lines pop.
Show crosses: toggle the X markers when price crosses a line. I turn this on when I’m actively hunting breakouts/retests.
Reading the chart
Red lines (from highs): I treat these as potential resistance. A clean break + hold above a red line often flips me from “fade” to “follow.”
Green lines (from lows): Potential support. Same idea in reverse: break + hold below and I stop buying dips until I see structure reclaim.
HH / LH / HL / LL dots: quick read on structure.
HH/HL bias = uptrend continuation potential
LH/LL bias = downtrend continuation potential
Mixed prints = rotation/chop—tighten risk or wait for clarity.
My H1 guidance (fine-tuning Fractal Period)
If you’re mainly on H1 (my use case), tune like this:
Fast / aggressive: n = 6–8 (lots of signals, good for momentum days; more chop risk)
Balanced (recommended): n = 9–12 (keeps lines meaningful but responsive)
Slow / swing focus: n = 13–21 (filters noise; better for trend days and higher-TF confluence)
Rule of thumb: if you’re getting too many touches and whipsaws, increase n. If you’re late to obvious breaks, decrease n.
How I trade it (example workflow)
Pick your n for the session (H1: start at 9–12).
Mark the recent red & green lines. That’s your immediate structure.
Look for interaction:
Rejections from a line = fade potential back into the range.
Break + close across a line = watch the retest for continuation.
Confirm with context: session bias, HTF structure, and your own tools (VWAP, RSI, volume, FVG/OB, etc.).
Plan the trade: enter on retest or reclaim, stop beyond the line/last swing, target the opposite side or next structure.
Alerts (set and forget)
“New trendline formed” — fires when a new high/low pivot confirms and a fresh line is drawn.
“Upper/lower trendline crossed” — fires when price crosses the most recent red/green line.
Use these to track structure shifts without staring at the screen.
Good to know (honest limitations)
Confirmation lag: pivots need n bars on both sides, so signals arrive after the swing confirms. That’s by design—less noise, fewer fake lines.
Lines update as structure evolves: when a new pivot forms, the previous “recent” line becomes “historical,” and older ones can be removed based on your max setting.
Not an auto trendline crystal ball: it won’t predict which line holds or breaks—it just keeps the most relevant structure clean and up to date.
Final notes
Works on any timeframe; I built it with H1 in mind and scale to H4/D1 by increasing n.
Pairs nicely with session tools and VWAP for intraday, or with supply/demand / FVGs for swing planning.
Risk first: lines are structure, not guarantees. Manage position size and stops as usual.
Not financial advice. Trade your plan. Stay nimble.
ICT Sessions & Killzones +PRO (VinceFxBT)ICT Sessions & Killzones +PRO (VinceFxBT)
All in one Session and Killzone script for FX, Futures and Crypto markets. It includes London, New York, CBDR & Asia Sessions and Killzones.
Features
Includes London, New York, Asia, CBDR sessions
Includes all ICT Killzones
Extended session highs/lows up to 90s back, until mitigated.
Set recurring alerts for session highs and lows
Includes Indices price levels and opens
Uses UTC timezones with automatic Daylight Saving Time so NO timezone correction needed ; ) Works out of the box for all regions, including different dates of DST for US/EU.
Session highs/lows displayed on chart as lines, box or background color
Customize line styles, width and colors
Customize colors for Sessions and Killzones
Optionally include weekends for Session or Killzone separately
Optionally display day separators and labels
Fully control which options are displayed at higher or lower timeframes. (e.g. hide sessions when timeframe is 1h or higher)
Session display options
Session Background Color.
Session High & Low Lines, including Session Middle Line.
Extended session highs/lows until mitigated
Extended Session Highs & Lows until mitigated.
Session Background Color with extended Asia Session Highs & Lows until mitigated.
Set recurring alerts for session highs and lows
Set automatic alerts when previous and/or current session levels are broken.
4-Hour Range HighlighterThe 4-Hour Range Highlighter is a powerful visual analysis tool designed for traders operating on lower timeframes (like 5m, 15m, or 1H). It overlays the critical price range of the 4-hour (4H) candlestick onto your chart, providing immediate context from a higher timeframe. This helps you align your intraday trades with the dominant higher-timeframe structure, identifying key support and resistance zones, breakouts, and market volatility at a glance.
Key Features:
Visual Range Overlay: Draws a semi-transparent colored background spanning the entire High and Low of each 4-hour period.
Trend-Based Coloring: Automatically colors the range based on the 4H candle's direction:
Green: Bullish 4H candle (Close > Open)
Red: Bearish 4H candle (Close < Open)
Blue: Neutral 4H candle (Close = Open)
Customizable High/Low Lines: Optional, subtle lines plot the exact high and low of the 4H bar, acting as dynamic support/resistance levels.
Fully Customizable: Easily change colors and toggle visual elements on/off in the settings to match your chart's theme.
How to Use It:
Identify Key Levels: The top and bottom of the shaded area represent significant intraday support and resistance. Watch for price reactions at these levels.
Trade in Context: Use the trend color to gauge sentiment. For example, look for buy opportunities near the low of a bullish (green) 4H range.
Spot Breakouts: A strong candle closing above the high or below the low of the current 4H range can signal a continuation or the start of a new strong move.
Gauge Volatility: A large shaded area indicates a high-volatility 4H period. A small area suggests consolidation or low volatility.
Settings:
Visual Settings: Toggle the background and choose colors for Bullish, Bearish, and Neutral ranges.
Line Settings: Toggle the high/low lines and customize their colors.
Note: This is a visual aid, not a standalone trading system. It provides context but does not generate buy/sell signals. Always use it in conjunction with your own analysis and risk management.
Perfect for Day Traders, Swing Traders, and anyone who needs higher-timeframe context on their chart!
How to Use / Instructions:
After adding the script to your chart, open the settings menu (click on the indicator's name and then the gear icon).
In the "Inputs" tab, you will find two groups: "Visual Settings" and "Line Settings".
In Visual Settings, you can:
Toggle Show 4H Range Background on/off.
Change the Bullish Color, Bearish Color, and Neutral Color for the transparent background.
In Line Settings, you can:
Toggle Show High/Low Lines on/off.
Change the line colors for each trend type.
Adjust the colors to your preference. The default settings use transparency for a clean look that doesn't clutter the chart.
BTC/USD 3-Min Binary Prediction [v7.2 EN]BTC/USD 3-Minute Binary Prediction Indicator v7.2 - Complete Guide
Overview
This is an advanced technical analysis indicator designed for Bitcoin/USD binary options trading with 3-minute expiration times. The system aims for an 83% win rate by combining multiple analysis layers and pattern recognition.
How It Works
Core Prediction Logic
- Timeframe: Predicts whether BTC price will be ±$25 higher (HIGH) or lower (LOW) after 3 minutes
- Entry Signals: Generates HIGH/LOW signals when confidence exceeds threshold (default 75%)
- Verification: Automatically tracks and displays win/loss statistics in real-time
5-Layer Filter System
The indicator uses a sophisticated scoring system (0-100 points):
1. Trend Filter (25 points) - Analyzes EMA alignments and price momentum
2. Leading Indicators (25 points) - RSI and MACD divergence analysis
3. Volume Confirmation (20 points) - Detects unusual volume patterns
4. Support/Resistance (15 points) - Identifies key price levels
5. Momentum Alignment (15 points) - Measures acceleration and deceleration
Pattern Recognition
Automatically detects and visualizes:
- Double Tops/Bottoms - Reversal patterns
- Triangles - Ascending, descending, symmetrical
- Channels - Trending price channels
- Candlestick Patterns - Engulfing, hammer, hanging man
Multi-Timeframe Analysis
- Uses 1-minute and 5-minute data for confirmation
- Aligns multiple timeframes for higher probability trades
- Monitors trend consistency across timeframes
Key Features
Display Panels
1. Statistics Panel (Top Right)
- Overall win rate percentage
- Hourly performance (wins/losses)
- Daily performance
- Current system status
2. Analysis Panel (Left Side)
- Market trend analysis
- RSI status (overbought/oversold)
- Volume conditions
- Filter scores for each component
- Final HIGH/LOW/WAIT decision
Visual Signals
- Green Triangle (↑) = HIGH prediction
- Red Triangle (↓) = LOW prediction
- Yellow Background = Entry opportunity
- Blue Background = Waiting for result
Configuration Options
Basic Settings
- Range Width: Target price movement (default $50 = ±$25)
- Min Confidence: Minimum confidence to enter (default 75%)
- Max Daily Trades: Risk management limit (default 5)
Filters (Can be toggled on/off)
- Trend Filter
- Volume Confirmation
- Support/Resistance Filter
- Momentum Alignment
Display Options
- Show/hide signals, statistics, analysis
- Minimal Mode for cleaner charts
- EMA line visibility
Important Risk Warnings
Binary Options Trading Risks:
1. High Risk Product - Binary options are extremely risky and banned in many countries
2. Not Investment Advice - This tool is for educational/analytical purposes only
3. No Guaranteed Returns - Past performance doesn't predict future results
4. Capital at Risk - You can lose your entire investment in seconds
Technical Limitations:
- Requires stable internet connection
- Performance varies with market conditions
- High volatility can reduce accuracy
- Not suitable for news events or low liquidity periods
Best Practices
1. Paper Trade First - Test thoroughly on demo accounts
2. Risk Management - Never risk more than 1-2% per trade
3. Market Conditions - Works best in normal volatility conditions
4. Avoid Major Events - Don't trade during major news releases
5. Monitor Performance - Track your actual results vs displayed statistics
Setup Instructions
1. Add to TradingView chart (BTC/USD preferred)
2. Use 30-second or 1-minute chart timeframe
3. Adjust settings based on your risk tolerance
4. Monitor F-Score (should be >65 for entries)
5. Wait for clear HIGH/LOW signals with high confidence
Alert Configuration
The indicator provides three alert types:
- HIGH Signal alerts
- LOW Signal alerts
- General entry opportunity alerts
Legal Disclaimer
Binary options trading may not be legal in your jurisdiction. Many countries including the USA, Canada, and EU nations have restrictions or outright bans on binary options. Always check local regulations and consult with financial advisors before trading.
Remember: This is a technical analysis tool, not a money-printing machine. Successful trading requires discipline, risk management, and continuous learning. The displayed statistics are historical and don't guarantee future performance.