ATR GOD Strategy by TradeSmart (PineConnector-compatible)This is a highly-customizable trading strategy made by TradeSmart, focusing mainly on ATR-based indicators and filters. The strategy is mainly intended for trading forex , and has been optimized using the Deep Backtest feature on the 2018.01.01 - 2023.06.01 interval on the EUR/USD (FXCM) 15M chart, with a Slippage value of 3, and a Commission set to 0.00004 USD per contract. The strategy is also made compatible with PineConnector , to provide an easy option to automate the strategy using a connection to MetaTrader. See tooltips for details on how to set up the bot, and check out our website for a detailed guide with images on how to automate the strategy.
The strategy was implemented using the following logic:
Entry strategy:
A total of 4 Supertrend values can be used to determine the entry logic. There is option to set up all 4 Supertrend parameters individually, as well as their potential to be used as an entry signal/or a trend filter. Long/Short entry signals will be determined based on the selected potential Supertrend entry signals, and filtered based on them being in an uptrend/downtrend (also available for setup). Please use the provided tooltips for each setup to see every detail.
Exit strategy:
4 different types of Stop Losses are available: ATR-based/Candle Low/High Based/Percentage Based/Pip Based. Additionally, Force exiting can also be applied, where there is option to set up 4 custom sessions, and exits will happen after the session has closed.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Plot SL/TP lines: false by default, Checking this option will result in the TP and SL lines to be plotted on the chart.
Supertrend 1-4:
All the parameters of the Supertrends can be set up here, as well as their individual role in the entry logic.
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 100 by default
ATR Smoothing (of the SL): RMA/SMMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Candle Lookback (of the SL): 50 by default
Percentage Based Stop Loss: false by default, Set the stop loss to current price - % of current price (long) or price + % of current price (short).
Percentage (of the SL): 0.3 by default
Pip Based Stop Loss: Set the stop loss to current price - x pips (long) or price + x pips (short). Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Pip (of the SL): 10 by default
Base Risk Multiplier: 4.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 1.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exiting:
4 total Force exit on custom session close options: none applied by default. If enabled, trades will close automatically after the set session is closed (on next candle's open).
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 10 by default
Order Type: Capital Percentage by default, allows adjustment on how the position size is calculated: Cash: only the set cash amount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade
ATR Limiter:
Use ATR Limiter: true by default, Only enter into any position (long/short) if ATR value is higher than the Low Boundary and lower than the High Boundary.
ATR Limiter Length: 50 by default
ATR Limiter Smoothing: RMA/SMMA by default
High Boundary: 1000 by default
Low Boundary: 0.0003 by default
MA based calculation: ATR value under MA by default, If not Unspecified, an MA is calculated with the ATR value as source. Only enter into position (long/short) if ATR value is higher/lower than the MA.
MA Type: RMA/SMMA by default
MA Length: 400 by default
Waddah Attar Filter:
Explosion/Deadzone relation: Not specified by default, Explosion over Deadzone: trades will only happen if the explosion line is over the deadzone line; Explosion under Deadzone: trades will only happen if the explosion line is under the deadzone line; Not specified: the opening of trades will not be based on the relation between the explosion and deadzone lines.
Limit trades based on trends: Not specified by default, Strong Trends: only enter long if the WA bar is colored green (there is an uptrend and the current bar is higher then the previous); only enter short if the WA bar is colored red (there is a downtrend and the current bar is higher then the previous); Soft Trends: only enter long if the WA bar is colored lime (there is an uptrend and the current bar is lower then the previous); only enter short if the WA bar is colored orange (there is a downtrend and the current bar is lower then the previous); All Trends: only enter long if the WA bar is colored green or lime (there is an uptrend); only enter short if the WA bar is colored red or orange (there is a downtrend); Not specified: the color of the WA bar (trend) is not relevant when considering entries.
WA bar value: Not specified by default, Over Explosion and Deadzone: only enter trades when the WA bar value is over the Explosion and Deadzone lines; Not specified: the relation between the explosion/deadzone lines to the value of the WA bar will not be used to filter opening trades.
Sensitivity: 150 by default
Fast MA Type: SMA by default
Fast MA Length: 10 by default
Slow MA Type: SMA
Slow MA Length: 20 by default
Channel MA Type: EMA by default
BB Channel Length: 20 by default
BB Stdev Multiplier: 2 by default
Trend Filter:
Use long trend filter 1: false by default, Only enter long if price is above Long MA.
Show long trend filter 1: false by default, Plot the selected MA on the chart.
TF1 - MA Type: EMA by default
TF1 - MA Length: 120 by default
TF1 - MA Source: close by default
Use short trend filter 1: false by default, Only enter long if price is above Long MA.
Show short trend filter 1: false by default, Plot the selected MA on the chart.
TF2 - MA Type: EMA by default
TF2 - MA Length: 120 by default
TF2 - MA Source: close by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: RMA/SMMA by default
MA Length: 200 by default
Date Range Limiter:
Limit Between Dates: false by default
Start Date: Jan 01 2023 00:00:00 by default
End Date: Jun 24 2023 00:00:00 by default
Session Limiter:
Show session plots: false by default, show market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Trading Time:
Limit Trading Time: true by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 123567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 123456 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 1800-2000 by default, hours between which the trades can happen. The time is always in the exchange's timezone
All other options are also disabled by default
PineConnector Automation:
Use PineConnector Automation: false by default, In order for the connection to MetaTrader to work, you will need do perform prerequisite steps, you can follow our full guide at our website, or refer to the official PineConnector Documentation. To set up PineConnector Automation on the TradingView side, you will need to do the following:
1. Fill out the License ID field with your PineConnector License ID;
2. Fill out the Risk (trading volume) with the desired volume to be traded in each trade (the meaning of this value depends on the EA settings in Metatrader. Follow the detailed guide for additional information);
3. After filling out the fields, you need to enable the 'Use PineConnector Automation' option (check the box in the strategy settings);
4. Check if the chart has updated and you can see the appropriate order comments on your chart;
5. Create an alert with the strategy selected as Condition, and the Message as {{strategy.order.comment}} (should be there by default);
6. Enable the Webhook URL in the Notifications section, set it as the official PineConnector webhook address and enjoy your connection with MetaTrader.
License ID: 60123456789 by default
Risk (trading volume): 1 by default
NOTE! Fine-tuning/re-optimization is highly recommended when using other asset/timeframe combinations.
在脚本中搜索"11月1日是什么星座"
itradesize /\ Overnight Session & Silver BulletOvernight Session & Silver Bullet indicator
The indicator can be divided into two separate stuff:
ONS ( Overnight Session ) based on TCM’s ( TheCurrencyMerchant ) theory and Silver Bullet based on what ICT ( InnerCircleTrader ) is teaching to us.
Overnight Session
• ONS will be always based on Chicago 4am to 8am time according to TCM’s CME teaching.
The indicator has the option to show TSO ( Today’s session only ) which is good to have the chart not messed up by it. At this time when it comes to backtesting just turn this off to have the past ONS and SB ranges showed up on your chart.
• Mid line at the ONS range is useful to have as you are able to decide wether price is in a premium or a discount under the ONS.
If Im a buyer target is above the range, if Im a seller target is below the range.
• You are also able to have SD ( Standard Deviation ) lines for price projections. In the variety of TCM’s videos you are able to have a deeper knowledge.
• You can also extend Today’s ONS lines to the very end of the chart which could make an easier looking on the levels you eyeing with.
Silver Bullet
It’s based on New York time as ICT ( Inner Circle Trader ) is always teaching to us that we should use New York time, every time when it comes to his concepts.
Silver Bullets are always be there aiming of an opposing liquidity pool. They are working even on choppy days.
Silver Bullet hours:
• 03:00 - 04:00am NY Time
• 10:00 - 11:00am NY Time
• 02:00 - 03:00pm NY Time
SB highlighted areas could be shown as a box or a range according to your taste, with or without Start/End lines.
Both of them ca be used to form trades.
You should dig yourself into Silver Bullet ( InnerCircleTrader ) and Overnight Session ( TheCurrencyMerchant ) teachings before the use of the indicator.
Simple setups
• Silver Bullet
Look 20-30 minutes before any SB where the Buy or Sell program has started.
Where the first 1m FVG ( Fair Value Gap ) appears under the range, enter the trade.
Expect only a 5 handle move as a beginner.
1m chart is a must for these kind of FVG entries. ( 30s , 15s can also be used )
• ONS
Price is trading aggressively out of the range to take liquidity.
Once price grabbed liquidity that candle on the 3-5m could considered as on order block for the further movement.
If you are trading in the range, then the opposite side can be the target, if its out of the range and trading one sided, then use standard deviations as 0.5 is a minimum target.
MTF MAs and Crosses Nexus [DarkWaveAlgo]🧾 Description:
A nexus is a connection, link, or neuronal junction where signals and information are transmitted between different elements.
The MTF MAs and Crosses Nexus indicator serves as a nexus between MTF Moving Averages by facilitating the visualization and interaction of up to eight multi-timeframe moving averages, each with its own customizable timeframe, period, cross-over and cross-under alerts and plot markers, moving average calculation type, and price source.
It acts as a utility/control center that brings together multiple MTF moving averages (MTF MAs) and allows you to visualize the interactions between them with exceptional ease-of-use and customizability, helping to provide you with valuable insights into potential trend reversals, momentum shifts, and trading opportunities.
💡 Originality and Usefulness:
While there are other multi-timeframe moving average indicators available, MTF MAs and Crosses Nexus' customizable alert and signal settings offer intra-indicator MTF moving average cross markers and alerts not seen in other MTF MA indicators, allowing you to visualize the cross-over and cross-under relationships between the indicator's MAs with an 'all-in-one' experience. We also believe it stands above the rest with its sheer quantity and quality of settings, features, and usability.
✔️ Re-Published to Avoid Misleading Values
This script has been re-published to ensure that it does not use `request.security()` calls using lookahead_on to access future data when referencing moving averages from other timeframes. This decreases the likelihood that the indicator will provide deceiving values. This change has been made in accordance with the PineScript documentation: "Using barmerge.lookahead_on at timeframes higher than the chart's without offsetting the `expression` argument like in `close ` will introduce future leak in scripts, as the function will then return the `close` price before it is actually known in the current context" and the Publishing Rule: "Do not use `request.security()` calls using lookahead to access future data".
💠 Features:
8 toggleable MTF Moving Averages with customizable timeframes, periods, moving average calculation types, and price sources
Customizable cross-over and cross-under alert and chart signal options for each MTF MA (toggleable cross alerts and signals for crosses between intra-indicator MAs and bar price values)
Aesthetic and flexible coloring and color theme styling options
End-of chart labels and options for ease-of-use and legibility
⚙️ Settings:
Use a Color Theme: When this setting is enabled, all manual 'Bullish and Bearish Colors' are overridden. All plots will use the colors from your selected Color Theme - excepting those plots set to use the 'Single Color' coloring method.
Color Theme: When 'Use a Color Theme' is enabled, this setting allows you to select the color theme you wish to use.
Hide MAs on Timeframes Lower Than the Chart: When this setting is enabled, any MTF MA with a timeframe smaller than that of the chart the indicator is applied to will be hidden from view.
Enable: Show/hide a specific MTF MA.
Timeframe: Set the timeframe for a specific MTF MA.
Period: Set the lookback period for a specific MTF MA.
Type: Set the calculation type for a specific MTF MA. Options include: Exponential, Simple, Weighted, Volume-Weighted, and Hull.
Source Price: Set the source value used for a specific MTF MA's calculation.
Enable Cross Over Signals & Alerts: When enabled, cross-over chart signals (markers) and alerts are enabled for when this specific MTF MA crosses above its respective 'Cross Over Cross Source'.
Enable Cross Under Signals & Alerts: When enabled, cross-under chart signals (markers) and alerts are enabled for when this specific MTF MA crosses below its respective 'Cross Under Cross Source'.
Cross Source: Set the target plot which this specific MTF MA must cross (for either a cross-over or cross-under event) to trigger a chart signal and alert.
Marker Position: Set the position where this specific MTF MA's cross chart signal should appear. Options include: Above Bar, Below Bar, and On MA Line.
Coloring Method: Set the coloring method for this specific MA. The coloring method defines how the MA should be dynamically colored. Options include: Single Color, Increasing/Decreasing, and Over/Under Price.
Bullish Color: When 'Use a Color Theme' is disabled, this will set the 'bullish color' for this specific MTF MA.
Bearish Color: When 'Use a Color Theme' is disabled, this will set the 'bearish color' for this specific MTF MA.
Single Color: When the 'Coloring Method' is set to Single Color for this specific MA, this color option will set the MA's color.
Enable Label: When enabled, a label will show at the end of the chart displaying the timeframe, period, MA type, and current price value of this specific MTF MA.
Size: Sets the font size of this specific MTF MA's label.
Label Offset (in Bars): Sets the distance from the latest bar, in bars, at which this specific MTF MA's label is displayed.
Show Label Line: When enabled, this specific MTF MA's label will be accommodated by a dashed line connecting it to its plot.
📈 Chart:
The chart shown in this original publication displays the 15 minute chart on BTCUSDT. Displayed on the chart are 4 MTF MAs: the 15m 20 WMA, 30m 100 EMA, 1h 11 EMA, and 1D 7 VWMA - offering an exemplary view of how you can use these MTF MAs and crosses to your advantage in gauging trend relationships across multiple timeframes.
Monthly Strategy Performance TableWhat Is This?
This script code adds a Monthly Strategy Performance Table to your Pine Script strategy scripts so you can see a month-by-month and year-by-year breakdown of your P&L as a percentage of your account balance.
The table is based on realized equity rather than open equity, so it only updates the metrics when a trade is closed.
That's why some numbers will not match the Strategy Tester metrics (such as max drawdown), as the Strategy Tester bases metrics like max drawdown on open trade equity and not realized equity (closed trades).
The script is still a work-in-progress, so make sure to read the disclaimer below. But I think it's ready to release the code for others to play around with.
How To Use It
The script code includes one of my strategies as an example strategy. You need to replace my strategy code with your own. To do that just copy the source code below into a blank script, delete lines 11 -> 60 and paste your strategy code in there instead of mine. The script should work with most systems, but make sure to read the disclaimer below.
It works best with a significant amount of historical data, so it may not work very effectively on intraday timeframes as there is a severe limitation of available bars on TradingView. I recommend using it on 4HR timeframes and above, as anything less will produce very little usable data. Having a premium TradingView plan will also help boost the number of available bars.
You can hover your mouse over a table cell to get more information in the form of tooltips (such as the Long and Short win rate if you hover over your total return cell).
Credit
The code in this script is based on open-source code originally written by QuantNomad, I've made significant changes and additions to the original script but all credit for the idea and especially the display table code goes to them - I just built on top of it:
Why Did I Make This?
None of this is trading or investment advice, just my personal opinion based on my experience as a trader and systems developer these past 6+ years:
The TradingView Strategy Tester is severely limited in some important ways. And unless you use complex Excel formulas on exported test data, you can't see a granular perspective of your system's historical performance.
There is much more to creating profitable and tradeable systems than developing a strategy with a good win rate and a good return with a reasonable drawdown.
Some additional questions we need to ask ourselves are:
What did the system's worst drawdown look like?
How long did it last?
How often do drawdowns occur, and how quickly are they typically recovered?
How often do we have a break-even or losing month or year?
What is our expected compounded annual growth rate, and how does that growth rate compare to our max drawdown?
And many more questions that are too long to list and take a lifetime of trading experience to answer.
Without answering these kinds of questions, we run the risk of developing systems that look good on paper, but when it comes to live trading, we are uncomfortable or incapable of enduring the system's granular characteristics.
This Monthly Performance Table script code is intended to help bridge some of that gap with the Strategy Tester's limited default performance data.
Disclaimer
I've done my best to ensure the numbers this code outputs are accurate, and according to my testing with my personal strategy scripts it appears to work fine. But there is always a good chance I've missed something, or that this code will not work with your particular system.
The majority of my TradingView systems are extremely simple single-target systems that operate on a closed-candle basis to minimize many of the data reliability issues with the Strategy Tester, so I was unable to do much testing with multiple targets and pyramiding etc.
I've included a Debug option in the script that will display important data and information on a label each time a trade is closed. I recommend using the Debug option to confirm that the numbers you see in the table are accurate and match what your strategy is actually doing.
Always do your own due diligence, verify all claims as best you can, and never take anyone's word for anything.
Take care, and best of luck with your trading :)
Kind regards,
Matt.
PS. If you're interested in learning how this script works, I have a free hour-long video lesson breaking down the source code - just check out the links below this script or in my profile.
Statistics TableThis script display some useful Statistics data that can be useful in making trading decision.
Here the list of information this script is display in table format.
You can change each and every single ema and rs length as per your need from setting.
1) close difference from first ema
2) close difference from second ema
3) close difference from third ema
4) close difference from fourth ema
5) difference between first and second ema
6) difference between second and third ema
7) difference between first and third ema
8) volume up down ratio
9) ATR/ADR %
10) volume pocket pivot count
11) daily closing range
12) weekly closing range
13) close difference from 52week high
14) close difference from 52week low
15) close difference from All time high
16) close difference from All time low
17) rs line above or below first rs ema
18) rs line above or below second rs ema
19) rs line above or below third rs ema
20) rs line above or below fourth rs ema
21) first rs value
22) second rs value
23) third rs value
24) fourth rs value
25) difference between previous first rs length days change % and current first rs length days change %
26) difference between previous second rs length days change % and current second rs length days change %
27) difference between previous third rs length days change % and current third rs length days change %
Vector3Library "Vector3"
Representation of 3D vectors and points.
This structure is used to pass 3D positions and directions around. It also contains functions for doing common vector operations.
Besides the functions listed below, other classes can be used to manipulate vectors and points as well.
For example the Quaternion and the Matrix4x4 classes are useful for rotating or transforming vectors and points.
___
**Reference:**
- github.com
- github.com
- github.com
- www.movable-type.co.uk
- docs.unity3d.com
- referencesource.microsoft.com
- github.com
\
new(x, y, z)
Create a new `Vector3`.
Parameters:
x (float) : `float` Property `x` value, (optional, default=na).
y (float) : `float` Property `y` value, (optional, default=na).
z (float) : `float` Property `z` value, (optional, default=na).
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.new(1.1, 1, 1)
```
from(value)
Create a new `Vector3` from a single value.
Parameters:
value (float) : `float` Properties positional value, (optional, default=na).
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.from(1.1)
```
from_Array(values, fill_na)
Create a new `Vector3` from a list of values, only reads up to the third item.
Parameters:
values (float ) : `array` Vector property values.
fill_na (float) : `float` Parameter value to replace missing indexes, (optional, defualt=na).
Returns: `Vector3` Generated new vector.
___
**Notes:**
- Supports any size of array, fills non available fields with `na`.
___
**Usage:**
```
.from_Array(array.from(1.1, fill_na=33))
.from_Array(array.from(1.1, 2, 3))
```
from_Vector2(values)
Create a new `Vector3` from a `Vector2`.
Parameters:
values (Vector2 type from RicardoSantos/CommonTypesMath/1) : `Vector2` Vector property values.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.from:Vector2(.Vector2.new(1, 2.0))
```
___
**Notes:**
- Type `Vector2` from CommonTypesMath library.
from_Quaternion(values)
Create a new `Vector3` from a `Quaternion`'s `x, y, z` properties.
Parameters:
values (Quaternion type from RicardoSantos/CommonTypesMath/1) : `Quaternion` Vector property values.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.from_Quaternion(.Quaternion.new(1, 2, 3, 4))
```
___
**Notes:**
- Type `Quaternion` from CommonTypesMath library.
from_String(expression, separator, fill_na)
Create a new `Vector3` from a list of values in a formated string.
Parameters:
expression (string) : `array` String with the list of vector properties.
separator (string) : `string` Separator between entries, (optional, default=`","`).
fill_na (float) : `float` Parameter value to replace missing indexes, (optional, defualt=na).
Returns: `Vector3` Generated new vector.
___
**Notes:**
- Supports any size of array, fills non available fields with `na`.
- `",,"` Empty fields will be ignored.
___
**Usage:**
```
.from_String("1.1", fill_na=33))
.from_String("(1.1,, 3)") // 1.1 , 3.0, NaN // empty field will be ignored!!
```
back()
Create a new `Vector3` object in the form `(0, 0, -1)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.back()
```
front()
Create a new `Vector3` object in the form `(0, 0, 1)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.front()
```
up()
Create a new `Vector3` object in the form `(0, 1, 0)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.up()
```
down()
Create a new `Vector3` object in the form `(0, -1, 0)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.down()
```
left()
Create a new `Vector3` object in the form `(-1, 0, 0)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.left()
```
right()
Create a new `Vector3` object in the form `(1, 0, 0)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.right()
```
zero()
Create a new `Vector3` object in the form `(0, 0, 0)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.zero()
```
one()
Create a new `Vector3` object in the form `(1, 1, 1)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.one()
```
minus_one()
Create a new `Vector3` object in the form `(-1, -1, -1)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.minus_one()
```
unit_x()
Create a new `Vector3` object in the form `(1, 0, 0)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.unit_x()
```
unit_y()
Create a new `Vector3` object in the form `(0, 1, 0)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.unit_y()
```
unit_z()
Create a new `Vector3` object in the form `(0, 0, 1)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.unit_z()
```
nan()
Create a new `Vector3` object in the form `(na, na, na)`.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.nan()
```
random(max, min)
Generate a vector with random properties.
Parameters:
max (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Maximum defined range of the vector properties.
min (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Minimum defined range of the vector properties.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.random(.from(math.pi), .from(-math.pi))
```
random(max)
Generate a vector with random properties (min set to 0.0).
Parameters:
max (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Maximum defined range of the vector properties.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
.random(.from(math.pi))
```
method copy(this)
Copy a existing `Vector3`
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .one().copy()
```
method i_add(this, other)
Modify a instance of a vector by adding a vector to it.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other Vector.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_add(.up())
```
method i_add(this, value)
Modify a instance of a vector by adding a vector to it.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_add(3.2)
```
method i_subtract(this, other)
Modify a instance of a vector by subtracting a vector to it.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other Vector.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_subtract(.down())
```
method i_subtract(this, value)
Modify a instance of a vector by subtracting a vector to it.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_subtract(3)
```
method i_multiply(this, other)
Modify a instance of a vector by multiplying a vector with it.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other Vector.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_multiply(.left())
```
method i_multiply(this, value)
Modify a instance of a vector by multiplying a vector with it.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` value.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_multiply(3)
```
method i_divide(this, other)
Modify a instance of a vector by dividing it by another vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other Vector.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_divide(.forward())
```
method i_divide(this, value)
Modify a instance of a vector by dividing it by another vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_divide(3)
```
method i_mod(this, other)
Modify a instance of a vector by modulo assignment with another vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other Vector.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_mod(.back())
```
method i_mod(this, value)
Modify a instance of a vector by modulo assignment with another vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_mod(3)
```
method i_pow(this, exponent)
Modify a instance of a vector by modulo assignment with another vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
exponent (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Exponent Vector.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_pow(.up())
```
method i_pow(this, exponent)
Modify a instance of a vector by modulo assignment with another vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
exponent (float) : `float` Exponent Value.
Returns: `Vector3` Updated source vector.
___
**Usage:**
```
a = .from(1) , a.i_pow(2)
```
method length_squared(this)
Squared length of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1)
Returns: `float` The squared length of this vector.
___
**Usage:**
```
a = .one().length_squared()
```
method magnitude_squared(this)
Squared magnitude of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `float` The length squared of this vector.
___
**Usage:**
```
a = .one().magnitude_squared()
```
method length(this)
Length of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `float` The length of this vector.
___
**Usage:**
```
a = .one().length()
```
method magnitude(this)
Magnitude of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `float` The Length of this vector.
___
**Usage:**
```
a = .one().magnitude()
```
method normalize(this, magnitude, eps)
Normalize a vector with a magnitude of 1(optional).
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
magnitude (float) : `float` Value to manipulate the magnitude of normalization, (optional, default=1.0).
eps (float)
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .new(33, 50, 100).normalize() // (x=0.283, y=0.429, z=0.858)
a = .new(33, 50, 100).normalize(2) // (x=0.142, y=0.214, z=0.429)
```
method to_String(this, precision)
Converts source vector to a string format, in the form `"(x, y, z)"`.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
precision (string) : `string` Precision format to apply to values (optional, default='').
Returns: `string` Formated string in a `"(x, y, z)"` format.
___
**Usage:**
```
a = .one().to_String("#.###")
```
method to_Array(this)
Converts source vector to a array format.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `array` List of the vector properties.
___
**Usage:**
```
a = .new(1, 2, 3).to_Array()
```
method to_Vector2(this)
Converts source vector to a Vector2 in the form `x, y`.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector2` Generated new vector.
___
**Usage:**
```
a = .from(1).to_Vector2()
```
method to_Quaternion(this, w)
Converts source vector to a Quaternion in the form `x, y, z, w`.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Sorce vector.
w (float) : `float` Property of `w` new value.
Returns: `Quaternion` Generated new vector.
___
**Usage:**
```
a = .from(1).to_Quaternion(w=1)
```
method add(this, other)
Add a vector to source vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).add(.unit_z())
```
method add(this, value)
Add a value to each property of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).add(2.0)
```
add(value, other)
Add each property of a vector to a base value as a new vector.
Parameters:
value (float) : `float` Value.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(2) , b = .add(1.0, a)
```
method subtract(this, other)
Subtract vector from source vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).subtract(.left())
```
method subtract(this, value)
Subtract a value from each property in source vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).subtract(2.0)
```
subtract(value, other)
Subtract each property in a vector from a base value and create a new vector.
Parameters:
value (float) : `float` Value.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .subtract(1.0, .right())
```
method multiply(this, other)
Multiply a vector by another.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).multiply(.up())
```
method multiply(this, value)
Multiply each element in source vector with a value.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).multiply(2.0)
```
multiply(value, other)
Multiply a value with each property in a vector and create a new vector.
Parameters:
value (float) : `float` Value.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .multiply(1.0, .new(1, 2, 1))
```
method divide(this, other)
Divide a vector by another.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).divide(.from(2))
```
method divide(this, value)
Divide each property in a vector by a value.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).divide(2.0)
```
divide(value, other)
Divide a base value by each property in a vector and create a new vector.
Parameters:
value (float) : `float` Value.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .divide(1.0, .from(2))
```
method mod(this, other)
Modulo a vector by another.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).mod(.from(2))
```
method mod(this, value)
Modulo each property in a vector by a value.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
value (float) : `float` Value.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).mod(2.0)
```
mod(value, other)
Modulo a base value by each property in a vector and create a new vector.
Parameters:
value (float) : `float` Value.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .mod(1.0, .from(2))
```
method negate(this)
Negate a vector in the form `(zero - this)`.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .one().negate()
```
method pow(this, other)
Modulo a vector by another.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(2).pow(.from(3))
```
method pow(this, exponent)
Raise the vector elements by a exponent.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
exponent (float) : `float` The exponent to raise the vector by.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).pow(2.0)
```
pow(value, exponent)
Raise value into a vector raised by the elements in exponent vector.
Parameters:
value (float) : `float` Base value.
exponent (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` The exponent to raise the vector of base value by.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .pow(1.0, .from(2))
```
method sqrt(this)
Square root of the elements in a vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).sqrt()
```
method abs(this)
Absolute properties of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).abs()
```
method max(this)
Highest property of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `float` Highest value amongst the vector properties.
___
**Usage:**
```
a = .new(1, 2, 3).max()
```
method min(this)
Lowest element of the vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `float` Lowest values amongst the vector properties.
___
**Usage:**
```
a = .new(1, 2, 3).min()
```
method floor(this)
Floor of vector a.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .new(1.33, 1.66, 1.99).floor()
```
method ceil(this)
Ceil of vector a.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .new(1.33, 1.66, 1.99).ceil()
```
method round(this)
Round of vector elements.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .new(1.33, 1.66, 1.99).round()
```
method round(this, precision)
Round of vector elements to n digits.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
precision (int) : `int` Number of digits to round the vector elements.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .new(1.33, 1.66, 1.99).round(1) // 1.3, 1.7, 2
```
method fractional(this)
Fractional parts of vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1.337).fractional() // 0.337
```
method dot_product(this, other)
Dot product of two vectors.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `float` Dot product.
___
**Usage:**
```
a = .from(2).dot_product(.left())
```
method cross_product(this, other)
Cross product of two vectors.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).cross_produc(.right())
```
method scale(this, scalar)
Scale vector by a scalar value.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
scalar (float) : `float` Value to scale the the vector by.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).scale(2)
```
method rescale(this, magnitude)
Rescale a vector to a new magnitude.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
magnitude (float) : `float` Value to manipulate the magnitude of normalization.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(20).rescale(1)
```
method equals(this, other)
Compares two vectors.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
other (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Other vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).equals(.one())
```
method sin(this)
Sine of vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).sin()
```
method cos(this)
Cosine of vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).cos()
```
method tan(this)
Tangent of vector.
Namespace types: TMath.Vector3
Parameters:
this (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .from(1).tan()
```
vmax(a, b)
Highest elements of the properties from two vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .vmax(.one(), .from(2))
```
vmax(a, b, c)
Highest elements of the properties from three vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
c (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .vmax(.new(0.1, 2.5, 3.4), .from(2), .from(3))
```
vmin(a, b)
Lowest elements of the properties from two vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .vmin(.one(), .from(2))
```
vmin(a, b, c)
Lowest elements of the properties from three vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
c (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .vmin(.one(), .from(2), .new(3.3, 2.2, 0.5))
```
distance(a, b)
Distance between vector `a` and `b`.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Target vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = distance(.from(3), .unit_z())
```
clamp(a, min, max)
Restrict a vector between a min and max vector.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
min (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Minimum boundary vector.
max (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Maximum boundary vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .clamp(a=.new(2.9, 1.5, 3.9), min=.from(2), max=.new(2.5, 3.0, 3.5))
```
clamp_magnitude(a, radius)
Vector with its magnitude clamped to a radius.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.object, vector with properties that should be restricted to a radius.
radius (float) : `float` Maximum radius to restrict magnitude of vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .clamp_magnitude(.from(21), 7)
```
lerp_unclamped(a, b, rate)
`Unclamped` linearly interpolates between provided vectors by a rate.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Target vector.
rate (float) : `float` Rate of interpolation, range(0 > 1) where 0 == source vector and 1 == target vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .lerp_unclamped(.from(1), .from(2), 1.2)
```
lerp(a, b, rate)
Linearly interpolates between provided vectors by a rate.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Target vector.
rate (float) : `float` Rate of interpolation, range(0 > 1) where 0 == source vector and 1 == target vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = lerp(.one(), .from(2), 0.2)
```
herp(start, start_tangent, end, end_tangent, rate)
Hermite curve interpolation between provided vectors.
Parameters:
start (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Start vector.
start_tangent (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Start vector tangent.
end (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` End vector.
end_tangent (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` End vector tangent.
rate (int) : `float` Rate of the movement from `start` to `end` to get position, should be range(0 > 1).
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
s = .new(0, 0, 0) , st = .new(0, 1, 1)
e = .new(1, 2, 2) , et = .new(-1, -1, 3)
h = .herp(s, st, e, et, 0.3)
```
___
**Reference:** en.m.wikibooks.org
herp_2(a, b, rate)
Hermite curve interpolation between provided vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Target vector.
rate (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Rate of the movement per component from `start` to `end` to get position, should be range(0 > 1).
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
h = .herp_2(.one(), .new(0.1, 3, 2), 0.6)
```
noise(a)
3D Noise based on Morgan McGuire @morgan3d
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = noise(.one())
```
___
**Reference:**
- thebookofshaders.com
- www.shadertoy.com
rotate(a, axis, angle)
Rotate a vector around a axis.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
axis (string) : `string` The plane to rotate around, `option="x", "y", "z"`.
angle (float) : `float` Angle in radians.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .rotate(.from(3), 'y', math.toradians(45.0))
```
rotate_x(a, angle)
Rotate a vector on a fixed `x`.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
angle (float) : `float` Angle in radians.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .rotate_x(.from(3), math.toradians(90.0))
```
rotate_y(a, angle)
Rotate a vector on a fixed `y`.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
angle (float) : `float` Angle in radians.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .rotate_y(.from(3), math.toradians(90.0))
```
rotate_yaw_pitch(a, yaw, pitch)
Rotate a vector by yaw and pitch values.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
yaw (float) : `float` Angle in radians.
pitch (float) : `float` Angle in radians.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .rotate_yaw_pitch(.from(3), math.toradians(90.0), math.toradians(45.0))
```
project(a, normal, eps)
Project a vector off a plane defined by a normal.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
normal (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` The normal of the surface being reflected off.
eps (float) : `float` Minimum resolution to void division by zero (default=0.000001).
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .project(.one(), .down())
```
project_on_plane(a, normal, eps)
Projects a vector onto a plane defined by a normal orthogonal to the plane.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
normal (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` The normal of the surface being reflected off.
eps (float) : `float` Minimum resolution to void division by zero (default=0.000001).
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .project_on_plane(.one(), .left())
```
project_to_2d(a, camera_position, camera_target)
Project a vector onto a two dimensions plane.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
camera_position (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Camera position.
camera_target (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Camera target plane position.
Returns: `Vector2` Generated new vector.
___
**Usage:**
```
a = .project_to_2d(.one(), .new(2, 2, 3), .zero())
```
reflect(a, normal)
Reflects a vector off a plane defined by a normal.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
normal (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` The normal of the surface being reflected off.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .reflect(.one(), .right())
```
angle(a, b, eps)
Angle in degrees between two vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Target vector.
eps (float) : `float` Minimum resolution to void division by zero (default=1.0e-15).
Returns: `float` Angle value in degrees.
___
**Usage:**
```
a = .angle(.one(), .up())
```
angle_signed(a, b, axis)
Signed angle in degrees between two vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Target vector.
axis (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Axis vector.
Returns: `float` Angle value in degrees.
___
**Usage:**
```
a = .angle_signed(.one(), .left(), .down())
```
___
**Notes:**
- The smaller of the two possible angles between the two vectors is returned, therefore the result will never
be greater than 180 degrees or smaller than -180 degrees.
- If you imagine the from and to vectors as lines on a piece of paper, both originating from the same point,
then the /axis/ vector would point up out of the paper.
- The measured angle between the two vectors would be positive in a clockwise direction and negative in an
anti-clockwise direction.
___
**Reference:**
- github.com
angle2d(a, b)
2D angle between two vectors.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
b (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Target vector.
Returns: `float` Angle value in degrees.
___
**Usage:**
```
a = .angle2d(.one(), .left())
```
transform_Matrix(a, M)
Transforms a vector by the given matrix.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
M (matrix) : `matrix` A 4x4 matrix. The transformation matrix.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
mat = matrix.new(4, 0)
mat.add_row(0, array.from(0.0, 0.0, 0.0, 1.0))
mat.add_row(1, array.from(0.0, 0.0, 1.0, 0.0))
mat.add_row(2, array.from(0.0, 1.0, 0.0, 0.0))
mat.add_row(3, array.from(1.0, 0.0, 0.0, 0.0))
b = .transform_Matrix(.one(), mat)
```
transform_M44(a, M)
Transforms a vector by the given matrix.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
M (M44 type from RicardoSantos/CommonTypesMath/1) : `M44` A 4x4 matrix. The transformation matrix.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .transform_M44(.one(), .M44.new(0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0))
```
___
**Notes:**
- Type `M44` from `CommonTypesMath` library.
transform_normal_Matrix(a, M)
Transforms a vector by the given matrix.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
M (matrix) : `matrix` A 4x4 matrix. The transformation matrix.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
mat = matrix.new(4, 0)
mat.add_row(0, array.from(0.0, 0.0, 0.0, 1.0))
mat.add_row(1, array.from(0.0, 0.0, 1.0, 0.0))
mat.add_row(2, array.from(0.0, 1.0, 0.0, 0.0))
mat.add_row(3, array.from(1.0, 0.0, 0.0, 0.0))
b = .transform_normal_Matrix(.one(), mat)
```
transform_normal_M44(a, M)
Transforms a vector by the given matrix.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector.
M (M44 type from RicardoSantos/CommonTypesMath/1) : `M44` A 4x4 matrix. The transformation matrix.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .transform_normal_M44(.one(), .M44.new(0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0))
```
___
**Notes:**
- Type `M44` from `CommonTypesMath` library.
transform_Array(a, rotation)
Transforms a vector by the given Quaternion rotation value.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector. The source vector to be rotated.
rotation (float ) : `array` A 4 element array. Quaternion. The rotation to apply.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .transform_Array(.one(), array.from(0.2, 0.2, 0.2, 1.0))
```
___
**Reference:**
- referencesource.microsoft.com
transform_Quaternion(a, rotation)
Transforms a vector by the given Quaternion rotation value.
Parameters:
a (Vector3 type from RicardoSantos/CommonTypesMath/1) : `Vector3` Source vector. The source vector to be rotated.
rotation (Quaternion type from RicardoSantos/CommonTypesMath/1) : `array` A 4 element array. Quaternion. The rotation to apply.
Returns: `Vector3` Generated new vector.
___
**Usage:**
```
a = .transform_Quaternion(.one(), .Quaternion.new(0.2, 0.2, 0.2, 1.0))
```
___
**Notes:**
- Type `Quaternion` from `CommonTypesMath` library.
___
**Reference:**
- referencesource.microsoft.com
[TT] Sectors Dist % From MA- The script shows the distance in percentages from the 200 MA (or any other MA period) , for the 11 SP500 sectors.
- It works based on the current time frames.
Could be useful when working with mean reversion strategies to detect extremes zones and overbought/oversold conditions in the given sectors compared others.
Slight Swing Momentum Strategy.Introduction:
The Swing Momentum Strategy is a quantitative trading strategy designed to capture mid-term opportunities in the financial markets by combining swing trading principles with momentum indicators. It utilizes a combination of technical indicators, including moving averages, crossover signals, and volume analysis, to generate buy and sell signals. The strategy aims to identify market trends and capitalize on price momentum for profit generation.
Highlights:
The strategy offers several key highlights that make it unique and potentially attractive to traders:
Swing Trading with Momentum: The strategy combines the principles of swing trading, which aim to capture short-to-medium-term price swings, with momentum indicators that help identify strong price trends and potential breakout opportunities.
Technical Indicator Optimization: The strategy utilizes a selection of optimized technical indicators, including moving averages and crossover signals, to filter out the noise and focus on high-probability trading setups. This optimization enhances the strategy's ability to identify favourable entry and exit points.
Risk Management: The strategy incorporates risk management techniques, such as position sizing based on equity and dynamic stop loss levels, to manage risk exposure and protect capital. This helps to minimize drawdowns and preserve profits.
Buy Condition:
The buy condition in the strategy is determined by a combination of factors, including A1, A2, A3, XG, and weeklySlope. Let's break it down:
A1 Condition: The A1 condition checks for specific price relationships. It verifies that the ratio of the highest price to the closing price is less than 1.03, the ratio of the opening price to the lowest price is less than 1.03, and the ratio of the highest price to the previous day's closing price is greater than 1.06. This condition looks for a specific pattern indicating potential bullish momentum.
A2 Condition: The A2 condition checks for price relationships related to the closing price. It verifies that the ratio of the closing price to the opening price is greater than 1.05 or that the ratio of the closing price to the previous day's closing price is greater than 1.05. This condition looks for signs of upward price movement and momentum.
A3 Condition: The A3 condition focuses on volume. It checks if the current volume crosses above the highest volume over the last 60 periods. This condition aims to identify increased buying interest and potentially confirms the strength of the potential upward price movement.
XG Condition: The XG condition combines the A1 and A2 conditions and checks if they are true for both the current and previous bars. It also verifies that the ratio of the closing price to the 5-period EMA crosses above the 9-period SMA of the same ratio. This condition helps identify potential buy signals when multiple factors align, indicating a strong bullish momentum and potential entry point.
Weekly Trend Factor: The weekly slope condition calculates the slope of the 50-period SMA over a weekly timeframe. It checks if the slope is positive, indicating an overall upward trend on a weekly basis. This condition provides additional confirmation that the stock is in an upward trend.
When all of these conditions align, the buy condition is triggered, indicating a favourable time to enter a long position.
Sell Condition:
The sell condition is relatively straightforward in the strategy:
Sell Signal: The sell condition simply checks if the closing price crosses below the 10-period EMA. When this condition is met, it indicates a potential reversal or weakening of the upward price momentum, and a sell signal is generated.
Backtest Outcome:
The strategy was backtested over the period from January 22nd, 1999 to May 3rd, 2023, using daily candlestick charts for the NASDAQ: NVDA. The strategy used an initial capital of 1,000,000 USD, The order quantity is defined as 10% of the equity. The strategy allows for pyramiding with 1 order, and the transaction fee is set at 0.03% per trade. Here are the key outcomes of the backtest:
Net Profit: 539,595.84 USD, representing a return of 53.96%.
Percent Profitable: 48.82%
Total Closed Trades: 127
Profit Factor: 2.331
Max Drawdown: 68,422.70 USD
Average Trade: 4,248.79 USD
Average Number of Bars in Trades: 11, indicating the average duration of the trades.
Conclusion:
In conclusion, the Swing Momentum Strategy is a quantitative trading approach that combines swing trading principles with momentum indicators to identify and capture mid term trading opportunities. The strategy has demonstrated promising results during backtesting, including a significant net profit and a favourable profit factor.
Rounded Forex Levels: Big-Figure, Mid-Figure, 80-20 levels, BFRNSimple indicator to show Rounded levels in typical Forex pairs: Big figure, Mid-figure, 80-20 Insitutional Levels, 10pip levels, 5pip levels
Wrote this indicator because other ones out there seem to clutter the chart. This is simple, low-clutter and can be set by user to have arbitrary start and end points for the lines.
I wanted the ability for lines to plot discreetly to the right hand side of price as in the chart above, since in my opinion, these are only of secondary consideration to a trader, an extra confirmation/confluence to an existing idea.
//Purpose & Usage:
-Big-figure levels (100pips) & Mid-figure levels (50pips) will have a senstitivity to price, that can be an additional tool when looking for confluence for a target or an entry.
-As well as BF levels and MF levels; Institutional levels (20pips below and 20 pips above a Big Figure level) and standard 10pip or 5pip levels, can be useful in the right context (i.e added confirmation that of a minor sweep target; added conviction in an idea if the level aligns with another seperately derived level).
//User inputs:
-Toggle on/off each of the types of level.
-Line spacing: choose pip spacing of lines .
-Number of lines above/below (i.e. setting of 5 will be 11 lines. One central, 5 above, 5 below).
-Formatting: for each class of lines, code by color, style and width (as per the example chart below).
-Line start offset and line end offset: bars forward/back for each of start point and end point. So lines could be spread right across chart; or neatly pushed to the far right or left of the chart.
//Notes:
-Designed for typical Forex pairs with units close to 1.0 (like Eur/Usd, Usd/Cad, Aud/Usd, Gbp/Usd, Eur/Gbp, Nzd/Usd).
-Lines are based from the rounded close of the previous bar, Updating (if applicable) on each new bar.
Demo Plotting levels in the past; Dialog box example display:
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
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Leavitt Convolution Acceleration [CC]The Leavitt Convolution Slope indicator was created by Jay Leavitt (Stocks and Commodities Oct 2019, page 11), who is most well-known for creating the Volume-Weighted Average Price indicator. This indicator didn't have a good explanation or description so I custom-coded most of it. The way it works is it will give trend spikes in the direction of the underlying trend. If you don't see a spike then it means that the stock isn't trending at the moment. One possible avenue to explore with this indicator is judging the size of the trend spike before you open a position in that direction (or the opposite direction if you are shorting). I added a normalization function using code from a good friend @loxx that I recommend leaving on but feel free to experiment with it. I have color coded the lines to turn light green for a standard buy signal or dark green for a strong buy signal and light red for a standard sell signal, and dark red for a strong sell signal.
This is another indicator in a series that I'm publishing to fulfill a special request from @ashok1961 so let me know if you ever have any special requests for me.
The On Balance Volume & Accumulation Distribution RibbonMedic trades using "Smart Money Concepts", and Medic's system revolves around the one taught by MentFX (i.e. Structure, Supply/ Demand Zone , and Confirmation). While this system per se doesn't require the use of a volume indicator, Medic has come to respect the OBV and Accumulation / Distribution .
The OBV Ribbon is available in many a shape and form, but Medic wanted something more responsive, and the OBVAD is just that.
This ribbon works across all time frames, and allows users to visualize what is happening behind the scenes of The Trigger indicator.
The Ribbon applies 11 DEMA of different periods to the cumulative sum of SpaceTrader's OBV/AD formula: volume*(close-open)/( high-low )*hlc3.
The Ribbon is able to identify the general trend, and changes into a blu ein an uptrend, and purple in a downtrend, and also potential reversals by means of divergences.
Week & Day Boxes Projected forward; with day-of-week labelsProjecting Week and Day boxes forward into the future, as an aide in framing the shape/profile of the coming week(s)/day(s).
////user inputs////
~toggle on/off daily and/or weekly boxes.
~input number of 2week blocks or number of 2day blocks to project forward.
~independently format colors and opacities of weekly and daily boxes.
~toggle on/off day-of-week labels (if you just want day labels, make opacity of day boxes&borders zero).
////notes////
-I have limited the project-forward numbers to keep it neat. If you want to play around with them, edit UP the FIRST integer in lines 56, 58, 62, 64 (currently set to 11,10, 41, 40 respectively). And edit UP maxvals in lines 9 and 15.
-To change the height of weekly and/or daily boxes, tweak the SECOND integer in lines 56, 58, 62, 64.
-Written for ES (S&P); tested/working on FX and BTC too.
-Starts painting/Resets at the beginning of a new week (i.e. Sunday eve).
-Sunday is blended into Monday; day's are defined as finishing at 6pm (New York Time).
Futures All List Candle Analysis - FALCAIn this command; There is an alphabetical list of USDS-M coins with the USDT PERP extension on the Binance Futures side.
There are 13 lists in total. Each list contains 39 data. Due to data limitation, 13 lists are formed. There are 13 coins in the first 11 of the lists. The 12th list contains 3 coins. The last list (FAVORITE LIST) is CRYPTOCAP:TOTAL, BINANCE:BTCUSDTPERP, BINANCE:BTCDOMUSDTPERP as standard. You must add 10 coins to the final list.
The lists show data for the time period you selected.
Explanation of the (C/H) header: Close /High takes a maximum value of 1. As long as this value is 1, a price increase is observed.
Explanation of the (C/O) header:
Close /Open can be greater than ,1. In this case, a price increase is observed.
Close /Open can be less than 1. In this case, a price decrease is observed.
The value Close /Open can be equal to 1. In this case, price stability is observed.
Explanation of the (C/L) header: Close /Low takes a minimum value of 1. As long as this value is 1, a price decrease is observed.
Coins with a price decrease are shown in red.
Coins with a price increase will turn green.
***NOTE: For this command to work, you must first add 10 favorite coins to the "FAVORITE LIST".
Baseline Cross Qualifier Volatility Strategy with HMA Trend BiasFor trading ES on 30min Chart
Trading Rules
Post Baseline Cross Qualifier (PBCQ): If price crosses the baseline but the trade is invalid due to additional qualifiers, then the strategy doesn't enter a trade on that candle. This setting allows you override this disqualification in the following manner: If price crosses XX bars ago and is now qualified by other qualifiers, then the strategy enters a trade.
Volatility: If price crosses the baseline, we check to see how far it has moved in terms of multiples of volatility denoted in price (ATR x multiple). If price has moved by at least "Qualifier multiplier" and less than "Range Multiplier", then the strategy enters a trade. This range is shown on the chart with yellow area that tracks price above/blow the baseline. Also, see the dots at the top of the chart. If the dots are green, then price passes the volatility test for a long. If the dots are red, then price passes the volatility test for a short.
Take Profit/Stoploss Quantity Removed
1 Take Profit: 100% of the trade is closed when the profit target or stoploss is reached.
2 Take Profits: Quantity is split 50/50 between Take Profit 1 and Take Profit 2
3 Take Profits: Quantify is split 50/25/25.
Stratgey Inputs
Baseline Length
37
Post Baseline Cross Qualifier Enabled
On
Post Baseline Cross Qualifier Bars Ago
9
ATR Length
9
Volatility Multiplier
0
Volatility Range Multiplier
10
Volatility Qualifier Multiplier
2
Take Profit Type
1 Take Profit
HMA Length
11
ICT MacrosThis script allows traders to visualize the range of time when a macro (an automated series of instructions/trades from large fund traders, executed by an algorithm) will likely occur in the market. It does this by drawing vertical lines and labels on the chart at these specific times:
(Macro Open) - 9:50 AM EST
(Macro Close) - 10:10 AM EST
(Macro Open) - 10:50 AM EST
(Macro Close) - 11:10 AM EST
(Macro Open) - 1:10 PM EST
(Macro Close) - 1:40 PM EST
(Macro Open) - 3:15 PM EST
(Macro Close) - 3:45 PM EST
The theory behind the use of these macros - is that the market will either seek buy side or sell side liquidity, or seek to rebalance price at a point of interest in between the open and close of the macro. Traders who follow this theory can use that information to anticipate how price might behave.
When a macro occurs, the script draws a vertical line on the chart using a dotted line style with a user-defined color. Additionally, a label is placed above the line to indicate whether it is a Macro Open or Macro Close event.
To preserve space, the labels are abbreviated on chart - "Macro Open" (M.O.) and "Macro Close" (M.C.) for both the morning and afternoon trading sessions. The labels may be turned on/off by the user.
The script also includes alerts that can notify traders when a macro occurs. These alerts can be set to go off once per bar close, and the alert message indicates the specific macro type and time.
This script is entirely open-source, meaning that traders can read the code and modify it as needed. Credit to the foundation of this script goes to TradingView user @rickyzcarroll for his open source Strat Assistant Hour Flip script. Important changes include the specific time changes and alert function.
Investments/swing trading strategy for different assetsStop worrying about catching the lowest price, it's almost impossible!: with this trend-following strategy and protection from bearish phases, you will know how to enter the market properly to obtain benefits in the long term.
Backtesting context: 1899-11-01 to 2023-02-16 of SPX by Tvc. Commissions: 0.05% for each entry, 0.05% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 5 indicators are used:
One Ema of 200 periods
Atr Stop loss indicator from Gatherio
Squeeze momentum indicator from LazyBear
Moving average convergence/divergence or Macd
Relative strength index or Rsi
Trade conditions:
There are three type of entries, one of them depends if we want to trade against a bearish trend or not.
---If we keep Against trend option deactivated, the rules for two type of entries are:---
First type of entry:
With the next rules, we will be able to entry in a pull back situation:
Squeeze momentum is under 0 line (red)
Close is above 200 Ema and close is higher than the past close
Histogram from macd is under 0 line and is higher than the past one
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
For closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Second type of entry:
With the next rules, we will not lose a possible bullish movement:
Close is above 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entry, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
---If we keep Against trend option activated, the rules are the same as the ones above, but with one more type of entry. This is more useful in weekly timeframes, but could also be used in daily time frame:---
Third type of entry:
Close is under 200 Ema
Squeeze momentum crosses under 0 line
Once these rules are met, we enter into a buy position. Stop loss will be determined by atr stop loss (white point) and break even(blue point) by a risk/reward ratio of 1:1.
Like in the past type of entries, for closing this position: Squeeze momentum crosses over 0 and, until squeeze momentum crosses under 0, we close the position. Otherwise, we would have closed the position due to break even or stop loss.
Risk management
For calculating the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a buy signal at price of 4,000 usd. The stop loss price from atr stop loss is 3,900. You calculate the distance in percent between 4,000 and 3,900. In this case, that distance would be of 2.50%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(2,5%) = 1000usd. It means, you have to use 1000 usd for risking 2.5% of your account.
We will use this risk management for applying compound interest.
In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, etc.
You will find the settings for risk management at the end of the script if you want to change something. But rebember, do not change values from indicators, the idea is to not over optimize the strategy.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
If you activate break even using rsi, when rsi crosses under overbought zone break even will be activated. This can work in some assets.
---Important: In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital---
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!
Some assets and timeframes where the strategy has also worked:
BTCUSD : 4H, 1D, W
SPX (US500) : 4H, 1D, W
GOLD : 1D, W
SILVER : 1D, W
ETHUSD : 4H, 1D
DXY : 1D
AAPL : 4H, 1D, W
AMZN : 4H, 1D, W
META : 4H, 1D, W
(and others stocks)
BANKNIFTY : 4H, 1D, W
DAX : 1D, W
RUT : 1D, W
HSI : 1D, W
NI225 : 1D, W
USDCOP : 1D, W
Hurst Spectral Analysis Oscillator"It is a true fact that any given time history of any event (including the price history of a stock) can always be considered as reproducible to any desired degree of accuracy by the process of algebraically summing a particular series of sine waves. This is intuitively evident if you start with a number of sine waves of differing frequencies, amplitudes, and phases, and then sum them up to get a new and more complex waveform." (Spectral Analysis chapter of J M Hurst's book, Profit Magic )
Background: A band-pass filter or bandpass filter is a device that passes frequencies within a certain range and rejects (attenuates) frequencies outside that range. Bandpass filters are widely used in wireless transmitters and receivers. Well-designed bandpass filters (having the optimum bandwidth) maximize the number of signal transmitters that can exist in a system while minimizing the interference or competition among signals. Outside of electronics and signal processing, other examples of the use of bandpass filters include atmospheric sciences, neuroscience, astronomy, economics, and finance.
About the indicator: This indicator will accept float/decimal length inputs to display a spectrum of 11 bandpass filters. The trader can select a single bandpass for analysis that includes future high/low predictions. The trader can also select which bandpasses contribute to a composite model of expected price action.
10 Statements to describe the 5 elements of Hurst's price-motion model:
Random events account for only 2% of the price change of the overall market and of individual issues.
National and world historical events influence the market to a negligible degree.
Foreseeable fundamental events account for about 75% of all price motion. The effect is smooth and slow changing.
Unforeseeable fundamental events influence price motion. They occur relatively seldom, but the effect can be large and must be guarded against.
Approximately 23% of all price motion is cyclic in nature and semi-predictable (basis of the "cyclic model").
Cyclicality in price motion consists of the sum of a number of (non-ideal) periodic cyclic "waves" or "fluctuations" (summation principle).
Summed cyclicality is a common factor among all stocks (commonality principle).
Cyclic component magnitude and duration fluctuate slowly with the passage of time. In the course of such fluctuations, the greater the magnitude, the longer the duration and vice-versa (variation principle).
Principle of nominality: an element of commonality from which variation is expected.
The greater the nominal duration of a cyclic component, the larger the nominal magnitude (principle of proportionality).
Shoutouts & Credits for all the raw code, helpful information, ideas & collaboration, conversations together, introductions, indicator feedback, and genuine/selfless help:
🏆 @TerryPascoe
🏅 DavidF at Sigma-L, and @HPotter
👏 @Saviolis, parisboy, and @upslidedown
Strategy Myth-Busting #11 - TrendMagic+SqzMom+CDV - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 11th one is an automated version of the "Magic Trading Strategy : Most Profitable Indicator : 1 Minute Scalping Strategy Crypto" strategy from "Fx MENTOR US" who doesn't make any official claims but given the indicators he was using, it looked like on the surface that this might actually work. The strategy author uses this on the 1 minute and 3 minute timeframes on mostly FOREX and Heiken Ashi candles but as the title of his strategy indicates is designed for Crypto. So who knows..
To backtest this accurately and get a better picture we resolved the Heiken Ashi bars to standard candlesticks . Even so, I was unable to sustain any consistency in my results on either the 1 or 3 min time frames and both FOREX and Crypto. 10000% Busted.
This strategy uses a combination of 3 open-source public indicators:
Trend Magic by KivancOzbilgic
Squeeze Momentum by LazyBear
Cumulative Delta Volume by LonesomeTheBlue
Trend Magic consists of two main indicators to validate momentum and volatility. It uses an ATR like a trailing Stop to determine the overarching momentum and CCI as a means to validate volatility. Together these are used as the primary indicator in this strategy. When the CCI is above 0 this is confirmation of a volatility event is occurring with affirmation based upon current momentum (ATR).
The CCI volatility indicator gets confirmation by the the Cumulative Delta Volume indicator which calculates the difference between buying and selling pressure. Volume Delta is calculated by taking the difference of the volume that traded at the offer price and the volume that traded at the bid price. The more volume that is traded at the bid price, the more likely there is momentum in the market.
And lastly the Squeeze Momentum indicator which uses a combination of Bollinger Bands, Keltner Channels and Momentum are used to again confirm momentum and volatility. During periods of low volatility, Bollinger bands narrow and trade inside Keltner channels. They can only contract so much before it can’t contain the energy it’s been building. When the Bollinger bands come back out, it explodes higher. When we see the histogram bar exploding into green above 0 that is a clear confirmation of increased momentum and volatile. The opposite (red) below 0 is true when there are low periods. This indicator is used as a means to really determine when there is premium selling plays going on leading to big directional movements again confirming the positive or negative momentum and volatility direction.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Trading Rules
1 - 3 min candles
FOREX or Crypto
Stop loss at swing high/low | 1.5 risk/ratio
Long Condition
Trend Magic line is Blue ( CCI is above 0) and above the current close on the bar
Squeeze Momentum's histogram bar is green/lime
Cumulative Delta Volume line is green
Short Condition
Trend Magic line is Red ( CCI is below 0) and below the current close on the bar
Squeeze Momentum's histogram bar is red/maroon
Cumulative Delta Volume line is peach
ATR PivotsThe "ATR Pivots" script is a technical analysis tool designed to help traders identify key levels of support and resistance on a chart. The indicator uses various metrics such as the Average True Range (ATR), Daily True Range ( DTR ), Daily True Range Percentage (DTR%), Average Daily Range (ADR), Previous Day High ( PDH ), and Previous Day Low ( PDL ) to provide a comprehensive picture of the volatility and movement of a security. The script also includes an EMA cloud and 200 EMA for trend identification and a 1-minute ATR scalping strategy for traders to make informed trading decisions.
ATR Detail:-
The ATR is a measure of the volatility of a security over a given period of time. It is calculated by taking the average of the true range (the difference between the high and low of a security) over a set number of periods. The user can input the number of periods (ATR length) to be used for the ATR calculation. The script also allows the user to choose whether to use the current close or not for the calculation. The script calculates various levels of support and resistance based on the relationship between the security's range ( high-low ) and the ATR. The levels are calculated by multiplying the ATR by different Fibonacci ratios (0.236, 0.382, 0.5, 0.618, 0.786, 1.000) and then adding or subtracting the result from the previous close. The script plots these levels on the chart, with the -100 level being the most significant level. The user also has an option to choose whether to plot all Fibonacci levels or not.
DTR and DTR% Detail:-
The Daily True Range Percentage (DTR%) is a metric that measures the daily volatility of a security as a percentage of its previous close. It is calculated by dividing the Daily True Range ( DTR ) by the previous close. DTR is the range between the current period's high and low and gives a measure of the volatility of the security on a daily basis. DTR% can be used as an indicator of the percentage of movement of the security on a daily basis. In this script, DTR% is used in combination with other metrics such as the Average True Range (ATR) and Fibonacci ratios to calculate key levels of support and resistance for the security. The idea behind using DTR% is that it can help traders to better understand the daily volatility of the security and make more informed trading decisions.
For example, if a security has a DTR% of 2%, it suggests that the security has a relatively low level of volatility and is less likely to experience significant price movements on a daily basis. On the other hand, if a security has a DTR% of 10%, it suggests that the security has a relatively high level of volatility and is more likely to experience significant price movements on a daily basis.
ADR:-
The script then calculates the ADR (Average Daily Range) which is the average of the daily range of the security, using the formula (Period High - Period Low) / ATR Length. This gives a measure of the average volatility of the security on a daily basis, which can be useful for determining potential levels of support and resistance .
PDH /PDL:-
The script also calculates PDH (Previous Day High) and PDL (Previous Day Low) which are the High and low of the previous day of the security. This gives a measure of the previous day's volatility and movement, which can be useful for determining potential levels of support and resistance .
EMA Cloud and 200 EMA Detail:-
The EMA cloud is a technical analysis tool that helps traders identify the trend of the market by comparing two different exponential moving averages (EMAs) of different lengths. The cloud is created by plotting the fast EMA and the slow EMA on the chart and filling the space between them. The user can input the length of the fast and slow EMA , and the script will calculate and plot these EMAs on the chart. The space between the two EMAs is then filled with a color that represents the trend, with green indicating a bullish trend and red indicating a bearish trend . Additionally, the script also plots a 200 EMA , which is a commonly used long-term trend indicator. When the fast EMA is above the slow EMA and the 200 EMA , it is considered a bullish signal, indicating an uptrend. When the fast EMA is below the slow EMA and the 200 EMA , it is considered a bearish signal, indicating a downtrend. The EMA cloud and 200 EMA can be used together to help traders identify the overall trend of the market and make more informed trading decisions.
1 Minute ATR Scalping Strategy:-
The script also includes a 1-minute ATR scalping strategy that can be used by traders looking for quick profits in the market. The strategy involves using the ATR levels calculated by the script as well as the EMA cloud and 200 EMA to identify potential buy and sell opportunities. For example, if the 1-minute ATR is above 11 in NIFTY and the EMA cloud is bullish , the strategy suggests buying the security. Similarly, if the 1-minute ATR is above 30 in BANKNIFTY and the EMA cloud is bullish , the strategy suggests buying the security.
Inside Candle:-
The Inside Candle is a price action pattern that occurs when the current candle's high and low are entirely within the range of the previous candle's high and low. This pattern indicates indecision or consolidation in the market and can be a potential sign of a trend reversal. When used in the 15-minute chart, traders can look for Inside Candle patterns that occur at key levels of support or resistance. If the Inside Candle pattern occurs at a key level and the price subsequently breaks out of the range of the Inside Candle, it can be a signal to enter a trade in the direction of the breakout. Traders can also use the Inside Candle pattern to trade in a tight range, or to reduce their exposure to a current trend.
Risk Management:-
As with any trading strategy, it is important to practice proper risk management when using the ATR Pivots script and the 1-minute ATR scalping strategy. This may include setting stop-loss orders, using appropriate position sizing, and diversifying your portfolio. It is also important to note that past performance is not indicative of future results and that the script and strategy provided are for educational purposes only.
In conclusion, the "ATR Pivots" script is a powerful tool that can help traders identify key levels of support and resistance , as well as trend direction. The additional metrics such as DTR , DTR%, ADR, PDH , and PDL provide a more comprehensive picture of the volatility and movement of the security, making it easier for traders to make better trading decisions. The inclusion of the EMA cloud and 200 EMA for trend identification, and the 1-minute ATR scalping strategy for quick profits can further enhance a trader's decision-making process. However, it is important to practice proper risk management and understand that past performance is not indicative of future results.
Special thanks to satymahajan for the idea of clubbing Average True Range with Fibonacci levels.
DR/IDR of Omega by TRSTNThis is an EXPERIMENTAL Script by @TRSTNGLRD derived from the coding of @IAmMas7er's "DR/IDR" Indicator that adds a total of 11 additional DR / IDR Ranges on both lower and higher timeframes.
This script is no-longer being worked on, so I have made it public.
Background:
This Script utilizes the Fibonacci-Doubling Sequence between the range of 18:30pm and 16:55pm NY-Time. Each Cycle is grouped into the following:
Omega/2, Omega/4, Omega/8, and Omega/16
The Mas7er's three original sessions are: Omega/4v1, Omega/4v2, and Omega/8v1
These three Sessions above take rule over all others. If you are looking to back-test this version of the script, please use the Experimental ranges as confirmation for the three above.
Important Notes:
- Please only select Sessions with their respected groups (All of Omega/4, All of Omega/16, etc...) rather than selecting all of them at once.
If you select all of them at once, the ranges will not be correct and cut each other off.
The only exceptions to this rule are the Mas7er's original ranges above.
- If you wish to have multiple groups of Ranges together, please add a second indicator to your chart.
- Omega/16v1 and Omega/16v6 are known to have a high-probability of a Judas Swing (takes out both sides of the range) - Be Cautious!
- Omega/2v1 is a very large DR / IDR range. I am working on shrinking it in size, but have more experimenting to do with different ranges.
- I do not use the experimental ranges with the IDR , only the DR . I have not been able to define probabilities fully yet, but the levels are respected nonetheless.
This script is not supposed to work EXACTLY like the Mas7er's, rather, generally instead.
Please comment and leave your opinion below about which ranges work the best and how you may utilize them.
Thank you!
1st Gray Cross Signals ━ Histogram SQZMOM [whvntr][LazyBear]This is the Histogram Version of one of my other indicators named: SQZ Momentum + 1st Gray Cross Signals (with arrows) Which is a modification of "Squeeze Momentum Indicator" by user: "LazyBear". In that indicator of his he described, and suggested, the use of his gray cross signals to find points of interest for trading based on the direction of momentum when the first gray cross appears... I have programmed these points, and highlighted them, for ease of use. The 1st gray cross strategy, he said , is from John F. Carter's book, Chapter 11, "Mastering the Trade".
Here we have the Histogram version, with background highlights only, and nothing on the chart, in true SQZ Momentum style.
Disclaimer: using this indicator, or any indicator anywhere, involves risk when trading and isn't a guarantee of 100% accurate results.
