Unicorn QuantDeeply customizable trading algorithm with instant backtesting. It emulates real trading and displays all the actions it takes on the chart. For example, it shows when to enter or partially close a position, move Stop-Loss to breakeven, etc. The user can replicate these actions in their trading terminal in real time. The algorithm uses up to three Take-Profit levels, and a Stop-Loss level that can move in a trade to protect the floating profit.
The script can send real-time alerts to the user’s Email and to the cell phone via notifications in the TradingView app.
The indicator is designed to be used on all timeframes, including lower ones for intraday trading and scalping.
HOW TO USE
Set the Stop-Loss and up to three Take-Profit levels. Choose the rules for moving the Stop-Loss level in a trade. Adjust the sensitivity of the trading signals. And check the backtest result in the Instant Backtesting dashboard. If the performance of the strategy satisfies you, proceed with the forward testing or live trading.
When using this script, please, keep in mind that past results do not necessarily reflect future results and there are many factors that influence trading results.
FEATURES
Trading Signals
The feature calculates Buy and Sell signals for trend or swing trading. The user can change the Sensitivity parameter to control the frequency of the signals. This allows them to be adjusted for different markets and timeframes.
Position Manager
To make the Position Manager setup as easy as possible, the algorithm calculates Stop-Loss and Take-Profit levels in Average True Range (ATR) units. They are self-adjusting for any market and timeframe, since they account for its average volatility .
You don't have to worry about what market you are trading - Forex, Stocks, Crypto, etc. With the self-adjusting Stop-Loss and Take-Profit, you can find settings that work for one market and use the same numerical values as a starting point for a completely different market.
Instant Backtesting
After changing any settings, you can immediately see the performance of the strategy on the Instant Backtesting panel. Two metrics are displayed there - the percentage of profitable trades and the total return. This information, as well as the historical trades shown on the chart, will help you quickly and easily evaluate the settings.
SETTINGS
TRADING SIGNALS
Sensitivity - controls the sensitivity of the trading signals algorithm. It determines the frequency of the trading signals. The higher the value of this parameter, the less trading signals you get and the longer trends the algorithm tries to catch. The lower the sensitivity value, the more signals you receive. This can be useful if you want to profit from small price movements.
POSITION MANAGER
SL - sets the Stop-Loss level measured in ATR units.
TP1, TP2, TP3 - set the Take-Profit levels measured in the ATR units.
Close % at TP1, Close % at TP2, Close % at TP3 - set portions of the open position (as a percentage of the initial order size) to close at each of the TP levels.
At TP1 move SL to, At TP2 move SL to - set the rules for moving the Stop-Loss level in an open trade to protect the floating profit.
Show Open Position Dashboard - turns on/off a dashboard that shows the current Stop-Loss and Take-Profit levels for the open position.
BACKTESTING
Use Starting Date - turns on/off the starting date for the strategy and backtests. When off, all available historical data is used.
Starting Date - sets the starting date for the strategy and backtests.
Show Instant Backtesting Dashboard - turns on/off a dashboard that shows the current strategy performance: the percentage of profitable trades and total return.
Leverage - sets the leverage that the strategy uses.
Signals
ADXVMA iTrend [Loxx]ADXVMA iTrend is an iTrend indicator with ADXVMA smoothing. Trend is used to determine where the trend starts and ends. Adjust the period inputs accordingly to suit your backtest requirements. This is also useful for scalping lower timeframes.
What is the ADXvma - Average Directional Volatility Moving Average?
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
Included
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
PPO w/ Discontinued Signal Lines [Loxx]PPO w/ Discontinued Signal Lines is a Percentage Price Oscillator with some upgrades. This indicator has 33 source types and 35+ moving average types as well as Discontinued Signal Lines and divergences. These additions reduce noise and increase hit rate.
What is the Price Percentage Oscillator?
The percentage price oscillator (PPO) is a technical momentum indicator that shows the relationship between two moving averages in percentage terms. The moving averages are a 26-period and 12-period exponential moving average (EMA).
The PPO is used to compare asset performance and volatility, spot divergence that could lead to price reversals, generate trade signals, and help confirm trend direction.
Included:
Bar coloring
3 signal variations w/ alerts
Divergences w/ alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
LabTrend SSL [Loxx]LabTrend SSL is based on the popular ASCTrend. This version adds an SSL channel to show the macro trend.
What is Lab Trend?
LabTrend is a complete trading indicator developed by Igorad and is based on the popular ASC Trend. LabTrend is the market "direction" indicator. It shows trend direction by colors, when the market changes to or stays in an up-trend, the bars become or remain GREEN. When the market changes to or stays in a downtrend, the bars become or remain RED. When the market goes sideways or is not strong on either side, the bars become or remain WHITE. This version adds an SSL channel to show the core major trend while bar coloring changes on the micro trend.
Included:
Bar coloring
Signals
Alerts
Tradesense PremiumTradesense Premium
Tradesense Premium indicator offers a buy & sell signal that is based from our senior analyst who have more than 10years of experience in Forex, Stock and Crypto trading and made it possible by our pine script developers.
Our script can detect market volatility based on the price direction and the absolute value of exponential moving average are multiplied to specific numbers to get a different trading style such as Scalper, Swing Trader and Trend Follower. We also filtered out all the signals using a different known indicators such as RSI, ATR, and ADX, and the results will allow you to enter a trade before the big moves occur. We also included all the important indicator which appears in real-time to get a competitive advantage in any market environment.
If you are a trader for a long time you should know that there is no way to avoid risk in trading. Every single trade could, theoretically at least, end up a loser. That is why our script also provides automatic risk management system which can gives you the ability to know exactly where to take the profit and to stop.
Trading style preset options - Will allows you to get the signals the way you wanted depending on your trading style. Ex. Scalper, Swing Trader or a Trend follower.
Bar color - Our bar colors are based on the price actions which detects the weakness of the bar or if the bar is ranging.
Reversal Zone - This indicator would identify possible price reversal zones.
Support & Resistance - This indicator draw a line at the pivot point to show possible support and resistance area.
Target Profit indicator based on price actions - This indicator will gives you an option to reduce your position or go out of the trade before the reversal happens.
Target Profit / Stop Loss based on ATR - This indicator will gives you a simple but effective risk management system to protect your capital. The TP/SL is based from the ATR.
Alert System - We are giving you an options to customize your alerts.
Our mission is to provide systematic way to build your success.
Release notes: Tradesense Premium V1.1
✅Trading style preset options
✅Bar color
✅Reversal Zone
✅Support & Resistance
✅Target Profit indicator based on price actions
✅Target Profit / Stop Loss based on ATR
✅Alert System
❓Trading style
Currently we have 3 sets of preset options that the user can use.
Scalp - this preset is made for the trader that wants a quick in and out of the trade. The best timeframe to this is 1min to 5mins chart.
Swing - this preset is for the trader who can wait a little bit longer in a trade. The best timeframe to use is 15mins to 1hour chart.
Trend - this preset is made for the busy people that can hold a trade more than a day. The best timeframe to use is 4hours to 1day chart.
❓Bar color
This options will change the color of your bars to lessen the noise of your chart.
Green Color is a bullish indicator
Red Color is a bearish indicator
Orange Color will signify that the trend is weakening
Purple Color is a consolidation/ranging price action
❓Reversal Zone
From the name it self, once the price is already hit the Reversal Zone the price will more likely to reverse or will make a correction.
❓Support & Resistance
When this option is enabled, the support and resistance levels will show up.
❓Target Profit indicator based on price actions
When this option is enabled, you will see a "💰" which means it's time to take profit or reduce your positions.
❓Target Profit / Stop Loss based on ATR
Most of the trader uses ATR as a stop loss level. When this option is enabled, the indicator for Stop Loss and Take Profit will show up and the TP/SL levels can be changed by changing the ATR Multiplier (Default is 1.8).
❓Alert System
Function alert is added and the user can customize it the way they want it.
R-squared Adaptive T3 [Loxx]R-squared Adaptive T3 is an R-squared adaptive version of Tilson's T3 moving average. This adaptivity was originally proposed by mladen on various forex forums. This is considered experimental but shows how to use r-squared adapting methods to moving averages. In theory, the T3 is a six-pole non-linear Kalman filter.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis. Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD, Momentum, Relative Strength Index) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA (simple moving average) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA(n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA.
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE/2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE/2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE/2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA, popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE/2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA(3) has lag 1, and EMA(11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA(3) through itself 5 times than if I just take EMA(11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA(3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA(7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA(n) = EMA(n) + EMA(time series - EMA(n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA. The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA(n) + EMA(time series - EMA(n))*.7;
This is algebraically the same as:
EMA(n)*1.7-EMA(EMA(n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD(n,v) = EMA(n)*(1+v)-EMA(EMA(n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA, and when v=1, GD is DEMA. In between, GD is a cooler DEMA. By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD(GD(GD(n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA(n)) to correct themselves. In Technical Analysis, these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Nyquist Moving Average (NMA) MACD [Loxx]Nyquist Moving Average (NMA) MACD is a MACD indicator using Nyquist Moving Average for its calculation.
What is the Nyquist Moving Average?
A moving average outlined originally developed by Dr . Manfred G. Dürschner in his paper "Gleitende Durchschnitte 3.0".
In signal processing theory, the application of a MA to itself can be seen as a Sampling procedure. The sampled signal is the MA (referred to as MA.) and the sampling signal is the MA as well (referred to as MA). If additional periodic cycles which are not included in the price series are to be avoided sampling must obey the Nyquist Criterion.
It can be concluded that the Moving Averages 3.0 on the basis of the Nyquist Criterion bring about a significant improvement compared with the Moving Averages 2.0 and 1.0. Additionally, the efficiency of the Moving Averages 3.0 can be proven in the result of a trading system with NWMA as basis.
What is the MACD?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence (MACD) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
Included
Bar coloring
2 types of signal output options
Alerts
Loxx's Expanded Source Types
Price-Filtered Spearman Rank Correl. w/ Floating Levels [Loxx]Price-Filtered Spearman Rank Correl. w/ Floating Levels is a Spearman Rank Correlation indicator with optional source filtering and floating levels.
What is Spearman rank correlation?
Spearman rank correlation, also known as Spearman coefficient is a formula used to identify the strength of the link between two datasets. This coefficient is a method that can be used to assess the strength of a relationship apart from the direction it takes. The formula, named after Charles Spearman, a mathematician, can only be used in circumstances where data can be categorized or put in order, for instance, the highest to the lowest.
For a better understanding of Spearman coefficient, it helps to get a sense of what monotonic function means. There’s a monotonic relationship under these circumstances:
– When the variable values rise together.
– When one variable value rises the other variable value lowers.
– The rate of movement of the variables need not necessarily be constant.
The Spearman correlation coefficient or rs, between +1 and -1, where +1 indicates a perfect strength between variables, while zero shows no association and -1 shows a perfect negative strength.
Spearman rank correlation theory:
A nonparametric (distribution-free) rank statistic proposed by Spearman in 1904 as a measure of the strength of the associations between two variables (Lehmann and D'Abrera 1998). The Spearman rank correlation coefficient can be used to give an R-estimate, and is a measure of monotone association that is used when the distribution of the data make Pearson's correlation coefficient undesirable or misleading.
Included:
Zero-line and signal cross options for bar coloring, signals, and alerts
Alerts
3 Signal types
Loxx's Expanded Source Types
Fisher Transform w/ Dynamic Zones [Loxx]What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
3 signal types
Bar coloring
Alerts
Channels fill
Loxx's Expanded Source Types
Dynamic Zone Range on OMA [Loxx]Dynamic Zone Range on OMA is an One More Moving Average oscillator with Dynamic Zones.
What is the One More Moving Average (OMA)?
The usual story goes something like this : which is the best moving average? Everyone that ever started to do any kind of technical analysis was pulled into this "game". Comparing, testing, looking for new ones, testing ...
The idea of this one is simple: it should not be itself, but it should be a kind of a chameleon - it should "imitate" as much other moving averages as it can. So the need for zillion different moving averages would diminish. And it should have some extra, of course:
The extras:
it has to be smooth
it has to be able to "change speed" without length change
it has to be able to adapt or not (since it has to "imitate" the non-adaptive as well as the adaptive ones)
The steps:
Smoothing - compared are the simple moving average (that is the basis and the first step of this indicator - a smoothed simple moving average with as little lag added as it is possible and as close to the original as it is possible) Speed 1 and non-adaptive are the reference for this basic setup.
Speed changing - same chart only added one more average with "speeds" 2 and 3 (for comparison purposes only here)
Finally - adapting : same chart with SMA compared to one more average with speed 1 but adaptive (so this parameters would make it a "smoothed adaptive simple average") Adapting part is a modified Kaufman adapting way and this part (the adapting part) may be a subject for changes in the future (it is giving satisfactory results, but if or when I find a better way, it will be implemented here)
Some comparisons for different speed settings (all the comparisons are without adaptive turned on, and are approximate. Approximation comes from a fact that it is impossible to get exactly the same values from only one way of calculation, and frankly, I even did not try to get those same values).
speed 0.5 - T3 (0.618 Tilson)
speed 2.5 - T3 (0.618 Fulks/Matulich)
speed 1 - SMA , harmonic mean
speed 2 - LWMA
speed 7 - very similar to Hull and TEMA
speed 8 - very similar to LSMA and Linear regression value
Parameters:
Length - length (period) for averaging
Source - price to use for averaging
Speed - desired speed (i limited to -1.5 on the lower side but it even does not need that limit - some interesting results with speeds that are less than 0 can be achieved)
Adaptive - does it adapt or not
Variety Moving Averages w/ Dynamic Zones contains 33 source types and 35+ moving averages with double dynamic zones levels.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
4 signal types
Bar coloring
Alerts
Channels fill
itrade buy/sellThe indicator was written based on several types of other indicators.
I took ema, rsi ema and an augmented version of qqe rsi.
The indicator checks for oversold or overbought on all of these indicators and, based on this, issues a buy or sell signal.
In the indicator, you can adjust the length of each point for yourself, so you can set rsi to 10 or 100, as it suits you.
The indicator works better on higher timeframes 4h-1w
But it can also be used on smaller timeframes, but the lower the timeframe, the higher the risk.
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Индикатор был написан на основе нескольких видов других индикаторов.
Я взял ema,rsi ema идополненую версию qqe rsi.
Индикатор проверяет перепроданость или перекупленость на этих всех индикаторах и изходя из этого выдаёт сигнал на покупку или продажу.
В индикаторе можно настроить длинну каждого пункта под себя,так вы можете поставить rsi на 10 или же на 100,как вам будет удобно.
Индикатор работает лучше на больших таймфреймах 4ч-1w
Но так же его можно использовать на более мелких таймфреймах,но чем ниже таймфрейм,тем выше риск.
Lune Market Analysis Premium- Version 0.9 -
Lune Algo was developed and built by Lune Trading, utilizing years of their trading expertise. This indicator works on all stocks, cryptos, indices, forex, futures , currencies, ETF's, energy and commodities. All the tools and features you need to assist you on your trading journey. Best of all, Lune Algo is easy to use and many of our tools and strategies have been thoroughly backtested thousands of times to ensure that users have the best experience possible.
Overview
Trade Dashboard—Provides information about the current market conditions, Such as if the market is trending up or down, how much volatility is in the market and even displays information about the current signal.
Trade Statistics—This tool gives you a breakdown of the Statistics of the current selected strategy based on backtests. It tells you the percentage of how often a Take Profit or Stop Loss was hit within a specific time period. Risk and Trade management is very important in trading, and can be the difference between a winning and losing strategy. So we believe that this was mandatory.
Current Features:
Advanced Buy and Sell Signals
Exclusive built-in Strategies
Lune Confidence AI
EK Clouds
Reversal Bands
Vray (Volume Ray)
Divergence Signals
Reversal Signals
Support/Resistance Zones
Built-in Themes
Built-in Risk Management system (take profit/stop loss)
Trade Statistics
Trade Assistance
Trade Dashboard
Advanced Settings
+ More coming soon, Big plans!
Features Breakdown:
Lune Confirmation—Used to help you confirm your trades and trend direction. It uses unique calculations, and its settings can be adjusted to allow traders to adapt the settings to fit their trading style.
Lune Confidence AI—All strategies are equipped with our exclusive built-in Confidence AI. This feature tells you how much confluence there is in a trade. It uses a rating system where signals are given a number from 0 to 5. A rating of 0 indicates that there is not a lot of confluence or confidence in the signal, while a rating of 5 indicates that there is a lot of confidence in the trade. This feature is not perfect and will be improved overtime.
Support/Resistance Zones—Calculates the most important support/resistance levels based on how many times a level has been used as support or resistance. Traders also refer to these as supply and demand zones and key levels.
EK Clouds—Used to further help you confirm trend and was optimized to also be used as support and resistance. This feature is powered by custom moving averages.
Reversal Bands—An optimized and improved version of the infamous Bollinger Bands. When price action takes place within the Reversal Bands it usually indicates that the current symbol is overextended and a reversal is possible.
Vray—Also Known as "Volume Ray", Assists you in better visualizing volume. This helps you find key levels and areas of support that you wouldn't be able to see otherwise. It helps you trade like the institutions.
This indicator's signals DO NOT REPAINT.
If you are using this script you acknowledge past performance is not necessarily indicative of future results and there are many more factors that go into being a profitable trader.
Fibonacci Moving AverageFibonacci moving averages are a more reactive form of EMA utilizing the Fibonacci sequence (1 2 3 5 8 13 ... etc) to weight values.
This method gives several advantages of EMAs: they respond much sooner to price action while still weighting for past values and longer MAs (200 candle, 800 candle) etc moving averages can be calculated from candle 1 - handy for newly listed cryptocurrencies, equities, ETFs, etc.
The script allows for up to 5 moving averages. They can also be set as WMAs which weight older values more than recent to create slow/fast MAs.
They can be used the same way regular EMAs/WMAs are used: crossovers give trade entry/exit points, can indicate trend by alignment with other MAs and by their angle up/down, and - less useful for FMAs since no one else uses them - they can provide resistance.
Scot Signal IndicatorThe Scot Signal Indicator is intended as a Scalping Resource. It was designed to work best on the ❗❗ 5 MINUTE CHART with Bitcoin ❗❗ / USD & USDT pairs.
🟡🔼🔽 Yellow Triangles : these are pre-signals. If the triangle is Pointing Down, then look for a possible Short to come, and vice-versa for Upward facing triangles will go Long.
* Be careful, this is a Canary in the Coal Mine, but not the full signal. Going purely on the triangle as a signal could lead to fake-outs more frequently.
🟩 🟥 Green & Red Boxes : these are "Long" & "Short" signals where the indicator feels the time is safe to enter a trade.
❗ EXITING THE TRADE ❗ : this is a scalping indicator, specifically meant for entering trades, NOT EXITING them. An ideal scalp is $100 - $200 Bitcoin move. Though, we run bots using this indicator, taking scalps as little
as $60, performing up to 8 trades a day.
Gucci Sniper Trading Bot [Open]A simple Buy/Sell signal algo designed for a trading bot.
Uses ATR and EMA cross to get signals.
Long and Short Signal_1hours [zavaUnni]This indicator is available in the 1 hour chart.
The Stochastic value of 1 hour of 3 types of length was requested, summed, and then the value was derived.
The blue line is the K and the orange line is D of the Stochastic.
The default is Stochastic, but when RSI is selected in the settings, it can be viewed as the relative strength index of the Stochastic.
If the K value crosses down at 100, a short signal is generated
Cross up below -100 and you'll get a long signal.
You can receive a ready signal by checking Position Ready in Settings.
Short ready signal when the k line goes up to 100.
Long ready signal when the k line goes below -100.
A small spread value of the candle relative to the volume is the principle that resistance has occurred.
Displayed the resistance value based on the average value of the last 100 candles.
The higher the value of the red Histogram, the stronger the selling.
The lower the value of the green Histogram value, the stronger the buying .
The gray histogram is when there's no buying or selling pressure.
Bull/Bear Buy/Bail CandlesBased on BullBearPower indicator, this is a heavily modified version with colored candles to show when bulls or bears are buying or bailing. Includes Fibonacci Levels based on Highest/Lowest value in variable length, along with optional second timeframe and alternative calculation for candles and linear regression curves for increased versatility. Green = bullish /long, Aqua = still-bullish albeit weakening, blue = weak albeit strengthening and red = weak/short. Perfect as a confirmation indicator for those looking to time markets.
Ext/Non EMA SignalsThis allows for one EMA to reference the regular session well the other references the extended session. A green arrow will appear above a bear candle closing above both the EMAs and a Red arrow on bull candles closing below both.
This saves me time from jumping back and forth from extended sessions and regular session.
Let me know if you have any questions, I just recently started using Pine Editor to build indicators I was not able to find in the library.
SP IndicatorSP Indicator - One of the best indicators for scalping trading on any timeframes. The best readings are given on 5, 15 and 30 minute frames.
For readings, several indicators are combined into one, which allows you to get a more accurate forecast, which is more than 90%.
Instruction.
The indicator is easy to use. Just install it and follow the arrows to go long or short. Stop loss set small, about 1-2%. In most cases, this is sufficient.
Good luck in bidding!
Phoenix Ascending SignalsThis is an overlay script for Phoenix Ascending Oscillator. This indicator will signal entries (red/green triangles) and bounces (yellow triangles). In settings select "Phoenix Ascending: Red RSI". You can overlay on the oscillator or over the chart (choose above and below bars in style settings)
Wizard AlgoWizard Algo:
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Features of the indicator:
- BULL/BEAR Signals
- TP (Take-Profit) and Exit System
- Possible Reversal Signals
- Reversal Scalper
- Reversal Bands
- Trend Bar Colors
- Auto Support/Resistance Levels
- Auto Trend-Lines
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Description:
1. Signals: The signals consists of 2 different approaches and the users can choose which signal type they want to use. The indicator gives bull/bear signals based on certain condition, such as trend and momentum. The "TP" signals stands for "Take Profit." These signals help users to decide when to take profits or liquidate all position. The Indicator includes an exit system that can used as another means of closing a position. The exit system uses a 1.5x risk to reward ratio to determine where to keep the take profit and stop loss target.
2.Reversal Scalper: Reversal scalpers are the tiny up(aqua) and down(fuchsia) triangles on the chart. These signals a possible reversal in the price and they can be used to enter a scalping trade. The signals uses mainly momentum and candle price action to determine when there could be a possible reversal in price.
3. Reversal Bands: The reversal band is the green/red cloud like indicator. This can help determine when a price is oversold and therefore, it could reverse. Same goes for the short side, if price is in the overbought territory, then it could reverse to the downside. The reversal bands uses mainly volatility. This is not the same thing as Bollinger bands.
4. Bar Colors: The candle bar colors helps to determine the current trend. The colors are given based on the current trend. The colors lime/red shows strong trend, and orange/cyan/blue shows weak trend.
5. Auto S/R and Auto trendlines: These indicators can be used for determining price actions. Both of these work in similar manner. They mainly look at the previous pivots and draws a line connecting the pivots. S/R are the horizontal lines and the trendline have angles to them.
Trend & Momentum V2Declutter your charts. Simple indicator combining trend and momentum using Moving Average (currently default to 9-day EMA) and RSI (default length of 8). A long signal is generated when the price closes above the moving average and the moving average color turns red to green which indicated that the momentum measured using RSI is greater than 50. A short signal is generated when the price closes below the moving average and the moving average color turns green to red indicating RSI is below 50. Confirmation is done if there is no reversal on the next candle. For best results use multiple timeframe charts to trade on the right side of trend and momentum.
Boom Hunter XL SignalsThis is the alerts script for Boom Hunter XL and overlays on top of your chart or over your indicator. Alerts are provided for common Boom Hunter XL signals such as breakouts, first pullbacks, pumps, dumps, overbought and oversold.
Small Triangle = First pullback entry
Triangle = Breakout
Square = Overbought/Oversold
Circle = Pump and Dump
Bar Colors can be turned on in the settings. Colors are available for signalling pressure, channel pressure and trend.
