[blackcat] L2 Ehlers Adaptive Jon Andersen R-Squared IndicatorLevel: 2
Background
@pips_v1 has proposed an interesting idea that is it possible to code an "Adaptive Jon Andersen R-Squared Indicator" where the length is determined by DCPeriod as calculated in Ehlers Sine Wave Indicator? I agree with him and starting to construct this indicator. After a study, I found "(blackcat) L2 Ehlers Autocorrelation Periodogram" script could be reused for this purpose because Ehlers Autocorrelation Periodogram is an ideal candidate to calculate the dominant cycle. On the other hand, there are two inputs for R-Squared indicator:
Length - number of bars to calculate moment correlation coefficient R
AvgLen - number of bars to calculate average R-square
I used Ehlers Autocorrelation Periodogram to produced a dynamic value of "Length" of R-Squared indicator and make it adaptive.
Function
One tool available in forecasting the trendiness of the breakout is the coefficient of determination (R-squared), a statistical measurement. The R-squared indicates linear strength between the security's price (the Y - axis) and time (the X - axis). The R-squared is the percentage of squared error that the linear regression can eliminate if it were used as the predictor instead of the mean value. If the R-squared were 0.99, then the linear regression would eliminate 99% of the error for prediction versus predicting closing prices using a simple moving average.
When the R-squared is at an extreme low, indicating that the mean is a better predictor than regression, it can only increase, indicating that the regression is becoming a better predictor than the mean. The opposite is true for extreme high values of the R-squared.
To make this indicator adaptive, the dominant cycle is extracted from the spectral estimate in the next block of code using a center-of-gravity ( CG ) algorithm. The CG algorithm measures the average center of two-dimensional objects. The algorithm computes the average period at which the powers are centered. That is the dominant cycle. The dominant cycle is a value that varies with time. The spectrum values vary between 0 and 1 after being normalized. These values are converted to colors. When the spectrum is greater than 0.5, the colors combine red and yellow, with yellow being the result when spectrum = 1 and red being the result when the spectrum = 0.5. When the spectrum is less than 0.5, the red saturation is decreased, with the result the color is black when spectrum = 0.
Construction of the autocorrelation periodogram starts with the autocorrelation function using the minimum three bars of averaging. The cyclic information is extracted using a discrete Fourier transform (DFT) of the autocorrelation results. This approach has at least four distinct advantages over other spectral estimation techniques. These are:
1. Rapid response. The spectral estimates start to form within a half-cycle period of their initiation.
2. Relative cyclic power as a function of time is estimated. The autocorrelation at all cycle periods can be low if there are no cycles present, for example, during a trend. Previous works treated the maximum cycle amplitude at each time bar equally.
3. The autocorrelation is constrained to be between minus one and plus one regardless of the period of the measured cycle period. This obviates the need to compensate for Spectral Dilation of the cycle amplitude as a function of the cycle period.
4. The resolution of the cyclic measurement is inherently high and is independent of any windowing function of the price data.
Key Signal
DC --> Ehlers dominant cycle.
AvgSqrR --> R-squared output of the indicator.
Remarks
This is a Level 2 free and open source indicator.
Feedbacks are appreciated.
Cerca negli script per "algo"
Fibonacci Extension / Retracement / Pivot Points by DGTFɪʙᴏɴᴀᴄᴄɪ Exᴛᴇɴᴛɪᴏɴ / Rᴇᴛʀᴀᴄᴍᴇɴᴛ / Pɪᴠᴏᴛ Pᴏɪɴᴛꜱ
This study combines various Fibonacci concepts into one, and some basic volume and volatility indications
█ Pɪᴠᴏᴛ Pᴏɪɴᴛꜱ — is a technical indicator that is used to determine the levels at which price may face support or resistance. The Pivot Points indicator consists of a pivot point (PP) level and several support (S) and resistance (R) levels. PP, resistance and support values are calculated in different ways, depending on the type of the indicator, this study implements Fibonacci Pivot Points
The indicator resolution is set by the input of the Pivot Points TF (Timeframe). If the Pivot Points TF is set to AUTO (the default value), then the increased resolution is determined by the following algorithm:
for intraday resolutions up to and including 5 min, 4HOURS (4H) is used
for intraday resolutions more than 5 min and up to and including 45 min, DAY (1D) is used
for intraday resolutions more than 45 min and up to and including 4 hour, WEEK (1W) is used
for daily resolutions MONTH is used (1M)
for weekly resolutions, 3-MONTH (3M) is used
for monthly resolutions, 12-MONTH (12M) is used
If the Pivot Points TF is set to User Defined, users may choose any higher timeframe of their preference
█ Fɪʙ Rᴇᴛʀᴀᴄᴇᴍᴇɴᴛ — Fibonacci retracements is a popular instrument used by technical analysts to determine support and resistance areas. In technical analysis, this tool is created by taking two extreme points (usually a peak and a trough) on the chart and dividing the vertical distance by the key Fibonacci coefficients equal to 23.6%, 38.2%, 50%, 61.8%, and 100%. This study implements an automated method of identifying the pivot lows/highs and automatically draws horizontal lines that are used to determine possible support and resistance levels
█ Fɪʙᴏɴᴀᴄᴄɪ Exᴛᴇɴꜱɪᴏɴꜱ — Fibonacci extensions are a tool that traders can use to establish profit targets or estimate how far a price may travel AFTER a retracement/pullback is finished. Extension levels are also possible areas where the price may reverse. This study implements an automated method of identifying the pivot lows/highs and automatically draws horizontal lines that are used to determine possible support and resistance levels.
IMPORTANT NOTE: Fibonacci extensions option may require to do further adjustment of the study parameters for proper usage. Extensions are aimed to be used when a trend is present and they aim to measure how far a price may travel AFTER a retracement/pullback. I will strongly suggest users of this study to check the education post for further details, where to use extensions and where to use retracements
Important input options for both Fibonacci Extensions and Retracements
Deviation, is a multiplier that affects how much the price should deviate from the previous pivot in order for the bar to become a new pivot. Increasing its value is one way to get higher timeframe Fib Retracement Levels
Depth, affects the minimum number of bars that will be taken into account when building
█ Volume / Volatility Add-Ons
High Volatile Bar Indication
Volume Spike Bar Indication
Volume Weighted Colored Bars
This study benefits from build-in auto fib retracement tv study and modifications applied to get extentions and also to fit this combo
Disclaimer:
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
(IK) Base Break BuyThis strategy first calculates areas of support (bases), and then enters trades if that support is broken. The idea is to profit off of retracement. Dollar-cost-averaging safety orders are key here. This strategy takes into account a .1% commission, and tests are done with an initial capital of 100.00 USD. This only goes long.
The strategy is highly customizable. I've set the default values to suit ETH/USD 15m. If you're trading this on another ticker or timeframe, make sure to play around with the settings. There is an explanation of each input in the script comments. I found this to be profitable across most 'common sense' values for settings, but tweaking led to some pretty promising results. I leaned more towards high risk/high trade volume.
Always remember though: historical performance is no guarantee of future behavior . Keep settings within your personal risk tolerance, even if it promises better profit. Anyone can write a 100% profitable script if they assume price always eventually goes up.
Check the script comments for more details, but, briefly, you can customize:
-How many bases to keep track of at once
-How those bases are calculated
-What defines a 'base break'
-Order amounts
-Safety order count
-Stop loss
Here's the basic algorithm:
-Identify support.
--Have previous candles found bottoms in the same area of the current candle bottom?
--Is this support unique enough from other areas of support?
-Determine if support is broken.
--Has the price crossed under support quickly and with certainty?
-Enter trade with a percentage of initial capital.
-Execute safety orders if price continues to drop.
-Exit trade at profit target or stop loss.
Take profit is dynamic and calculated on order entry. The bigger the 'break', the higher your take profit percentage. This target percentage is based on average position size, so as safety orders are filled, and average position size comes down, the target profit becomes easier to reach.
Stop loss can be calculated one of two ways, either a static level based on initial entry, or a dynamic level based on average position size. If you use the latter (default), be aware, your real losses will be greater than your stated stop loss percentage . For example:
-stop loss = 15%, capital = 100.00, safety order threshold = 10%
-you buy $50 worth of shares at $1 - price average is $1
-you safety $25 worth of shares at $0.9 - price average is $0.966
-you safety $25 worth of shares at $0.8. - price average is $0.925
-you get stopped out at 0.925 * (1-.15) = $0.78625, and you're left with $78.62.
This is a realized loss of ~21.4% with a stop loss set to 15%. The larger your safety order threshold, the larger your real loss in comparison to your stop loss percentage, and vice versa.
Indicator plots show the calculated bases in white. The closest base below price is yellow. If that base is broken, it turns purple. Once a trade is entered, profit target is shown in silver and stop loss in red.
(IK) Grid ScriptThis is my take on a grid trading strategy. From Investopedia:
"Grid trading is most commonly associated with the foreign exchange market. Overall the technique seeks to capitalize on normal price volatility in an asset by placing buy and sell orders at certain regular intervals above and below a predefined base price."
This strategy is best used on sideways markets, without a definitive up or down major trend. Because it doesn't rely on huge vertical movement, this strategy is great for small timeframes. It only goes long. I've set initial_capital to 100 USD. default_qty_value should be your initial capital divided by your amount of grid lines. I'm also assuming a 0.1% commission per trade.
Here's the basic algorithm:
- Create a grid based on an upper-bound (strong resistance) and a lower-bound (strong support)
- Grid lines are spaced evenly between these two bounds. (I recommend anywhere between 5-10 grid lines, but this script lets you use up to 15. More gridlines = more/smaller trades)
- Identify nearest gridline above and below current price (ignoring the very closest grid line)
- If price crosses under a near gridline, buy and recalculate near gridlines
- If price crosses over a near gridline, sell and recalculate near gridlines
- Trades are entered and exited based on a FIFO system. So if price falls 3 grid lines (buy-1, buy-2, buy-3), and subsequently crosses above one grid line, only the first trade will exit (sell-1). If it falls again, it will enter a new trade (buy-4), and if it crosses above again it will sell the original second trade (sell-2). The amount of trades you can be in at once are based on the amount of grid lines you have.
This strategy has no built-in stop loss! This is not a 'set-it-and-forget-it" script. Make sure that price remains within the bounds of your grid. If prices exits above the grid, you're in the money, but you won't be making any more trades. If price exits below the grid, you're 100% staked in whatever you happen to be trading.
This script is more complicated than my last one, but should be more user friendly. Make sure to correctly set your lower-bound and upper-bound based on strong support and resistance (the default values for these are probably going to be meaningless). If you change your "Grid Quantity" (amount of grid lines) make sure to also change your 'Order Size' property under settings for proper test results (or default_qty_value in the strategy() declaration).
Repeated Median Regression ChannelThis script uses the Repeated Median (RM) estimator to construct a linear regression channel and thus offers an alternative to the available codes based on ordinary least squares.
The RM estimator is a robust linear regression algorithm. It was proposed by Siegel in 1982 (1) and has since found many applications in science and engineering for linear trend estimation and data filtering.
The key difference between RM and ordinary least squares methods is that the slope of the RM line is significantly less affected by data points that deviate strongly from the established trend. In statistics, these points are usually called outliers, while in the context of price data, they are associated with gaps, reversals, breaks from the trading range. Thus, robustness to outlier means that the nascent deviation from a predetermined trend will be more clearly seen in the RM regression compared to the least-squares estimate. For the same reason, the RM model is expected to better depict gaps and trend changes (2).
Input Description
Length : Determines the length of the regression line.
Channel Multiplier : Determines the channel width in units of root-mean-square deviation.
Show Channel : If switched off , only the (central) regression line is displayed.
Show Historical Broken Channel : If switched on , the channels that were broken in the past are displayed. Note that a certain historical broken channel is shown only when at least Length / 2 bars have passed since the last historical broken channel.
Print Slope : Displays the value of the current RM slope on the graph.
Method
Calculation of the RM regression line is done as follows (1,3):
For each sample point ( t (i), y (i)) with i = 1.. Length , the algorithm calculates the median of all the slopes of the lines connecting this point to the other Length -1 points.
The regression slope is defined as the median of the set of these median slopes.
The regression intercept is defined as the median of the set { y (i) – m * t (i)}.
Computational Time
The present implementation utilizes a brute-force algorithm for computing the RM-slope that takes O ( Length ^2) time. Therefore, the calculation of the historical broken channels might take a relatively long time (depending on the Length parameter). However, when the Show Historical Broken Channel option is off, only the real-time RM channel is calculated, and this is done quite fast.
References
1. A. F. Siegel (1982), Robust regression using repeated medians, Biometrika, 69 , 242–244.
2. P. L. Davies, R. Fried, and U. Gather (2004), Robust signal extraction for on-line monitoring data, Journal of Statistical Planning and Inference 122 , 65-78.
3. en.wikipedia.org
Tic Tac Toe (For Fun)Hello All,
I think all of you know the game "Tic Tac Toe" :) This time I tried to make this game, and also I tried to share an example to develop a game script in Pine. Just for fun ;)
Tic Tac Toe Game Rules:
1. The game is played on a grid that's 3 squares by 3 squares.
2. You are "O", the computer is X. Players take turns putting their marks in empty squares.
3. if a player makes 3 of her marks in a row (up, down, across, or diagonally) the he is the winner.
4. When all 9 squares are full, the game is over (draw)
So, how to play the game?
- The player/you can play "O", meaning your mark is "O", so Xs for the script. please note that: The script plays with ONLY X
- There is naming for all squears, A1, A2, A3, B1, B2, B3, C1, C2, C3. you will see all these squares in the options.
- also You can set who will play first => "Human" or "Computer"
if it's your turn to move then you will see "You Move" text, as seen in the following screenshot. for example you want to put "O" to "A1" then using options set A1 as O
How the script play?
it uses MinMax algorithm with constant depth = 4. And yes we don't have option to make recursive functions in Pine at the moment so I made four functions for each depth. this idea can be used in your scripts if you need such an algorithm. if you have no idea about MinMax algorithm you can find a lot of articles on the net :)
The script plays its move automatically if its turn to play. you will just need to set the option that computer played (A1, C3, etc)
if it's computer turn to play then it calculates and show the move it wants to play like "My Move : B3 <= X" then using options you need to set B3 as X
Also it checks if the board is valid or not:
I have tested it but if you see any bug let me know please
Enjoy!
[blackcat] L2 Ehlers Autocorrelation PeriodogramLevel: 2
Background
John F. Ehlers introduced Autocorrelation Periodogram in his "Cycle Analytics for Traders" chapter 8 on 2013.
Function
Construction of the autocorrelation periodogram starts with the autocorrelation function using the minimum three bars of averaging. The cyclic information is extracted using a discrete Fourier transform (DFT) of the autocorrelation results. This approach has at least four distinct advantages over other spectral estimation techniques. These are:
1. Rapid response. The spectral estimates start to form within a half-cycle period of their initiation.
2. Relative cyclic power as a function of time is estimated. The autocorrelation at all cycle periods can be low if there are no cycles present, for example, during a trend. Previous works treated the maximum cycle amplitude at each time bar equally.
3. The autocorrelation is constrained to be between minus one and plus one regardless of the period of the measured cycle period. This obviates the need to compensate for Spectral Dilation of the cycle amplitude as a function of the cycle period.
4. The resolution of the cyclic measurement is inherently high and is independent of any windowing function of the price data.
The dominant cycle is extracted from the spectral estimate in the next block of code using a center-of-gravity (CG) algorithm. The CG algorithm measures the average center of two-dimensional objects. The algorithm computes the average period at which the powers are centered. That is the dominant cycle. The dominant cycle is a value that varies with time. The spectrum values vary between 0 and 1 after being normalized. These values are converted to colors. When the spectrum is greater than 0.5, the colors combine red and yellow, with yellow being the result when spectrum = 1 and red being the result when the spectrum = 0.5. When the spectrum is less than 0.5, the red saturation is decreased, with the result the color is black when spectrum = 0.
Key Signal
DominantCycle --> Dominant Cycle
Period --> Autocorrelation Periodogram Array
Pros and Cons
100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style.
Remarks
The 49th script for Blackcat1402 John F. Ehlers Week publication.
Courtesy of @RicardoSantos for RGB functions.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Trend-Range IdentifierTrend trading algorithms fail in ranging market and Swing trading algorithm fail in trending market. Purpose of this indicator is to identify if the instrument is trending or ranging so that you can apply appropriate trading algorithm for the market.
Process:
ATR is calculated based on the input parameter atrLength
Range/Channel containing upLine and downLine is calculated by adding/subtracting atrMultiplier * atr to close price.
This range/channel will remain same until the price breaks either upLine or downLine.
Once price crosses one among upLine and downLine, then new upLine/downLine is calculated based on latest close price.
If price breaks upLine, the trend is considered to be up until the next line break or no lines are broken for rangeLength bars. During this state, candles are colored in lime and upLine/downLine are colored in green.
If price breaks downLine, the trend is considered to be down until the next line break or no lines are broken for rangeLength bars. During this state, candles are colored in orange and upLine/downLine are colored in red.
If close price does not break either upLine or downLine for rangeLength bars, then the instrument is considered to be in range. During this state, candles are colored in silver and upLine/downLine are colored in purple.
In ranging duration, we display one among Keltner Channel, Bollinger Band or Donchian Band as per input parameter : rangeChannel . Other parameters used for calculation are rangeLength and stdDev
I have not fully optimized parameters. Suggestions and feedback welcome.
Dynamic Dots Dashboard (a Cloud/ZLEMA Composite)The purpose of this indicator is to provide an easy-to-read binary dashboard of where the current price is relative to key dynamic supports and resistances. The concept is simple, if a dynamic s/r is currently acting as a resistance, the indicator plots a dot above the histogram in the red box. If a dynamic s/r is acting as support, a dot is plotted in the green box below.
There are some additional features, but the dot graphs are king.
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KEY:
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Currently the dynamic s/r's being used in the dot plots are:
Ichimoku Cloud:
Tenkan (blue)
Kijun (pink)
Senkou A (red)
Senkou B (green)
ZLEMA (Zero Lag Exponential Moving Average)
99 ZLEMA (lavender)
200 ZLEMA (salmon)
You'll see a dashed line through the middle of the resistances section (red) and supports section (green). Cloud indicators are plotted above the dashed line, and ZLEMA's are below.
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How it Works - Visual
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As stated in the intro - if a dynamic s/r is currently above the current price and acting as a resistance, the indicator plots a dot above the histogram in the red box. If a dynamic s/r is acting as support, a dot is plotted in the green box below. Additionally, there is an optional histogram (default is on) that will further visualize this relationship. The histogram is a simple summation of the resistances above and the supports below.
Here's a visual to assist with what that means. This chart includes all of those dynamic s/r's in the dynamic dot dashboard (the on-chart parts are individually added, not part of this tool).
You can see that as a dynamic support is lost, the corresponding dot is moved from the supports section at the bottom (green), to the resistances section at the top (red). The opposite being true as resistances are being overtaken (broken resistances are moved to the support section (red)). You can see that the raw chart is just... a mess. Which kinda of accentuates one of the key goals of this indicator: to get all that dynamic support info without a mess of a chart like that.
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How To Use It
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There are a lot of ways to use this information, but the most notable of which is to detect shifts in the market cycle.
For this example, take a look at the dynamic s/r dots in the resistances category (red background). You can see clearly that there are distinctive blocks of high density dots that have clear beginnings and ends. When we transition from a high density of dots to none in resistances, that means we are flipping them as support and entering a bull cycle. On the other hand, when we go from low density of dots as resistances to high density, we're pivoting to a bear cycle. Easy as that, you can quickly detect when market cycles are beginning or ending.
Alternatively, you can add your preferred linear SR's, fibs, etc. to the chart and quickly glance at the dashboard to gauge how dynamic SR's may be contributing to the risk of your trade.
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Who It's For
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New traders: by looking at dot density alone, you can use Dot Dynamics to spot transitionary phases in market cycles.
Experienced traders: keep your charts clean and the information easy to digest.
Developers: I created this originally as a starting point for more complex algos I'm working on. One algo is reading this dot dashboard and taking a position size relative to the s/r's above and below. Another cloud algo is using the results as inputs to spot good setups.
Colored Bars
There is an option (off by default, shown in the headline image above) to fill the bar colors based on how many dynamic s/r's are above or below the current price. This can make things easier for some users, confusing for others. I defaulted them to off as I don't want colors to confuse the primary value proposition of the indicators, which is the dot heat map. You can turn on colored bars in the settings.
One thing to note with the colored bars: they plot the color purely by the dot densities. Random spikes in the gradient colors (i.e. red to lime or green) can be a useful thing to notice, as they commonly occur at places where the price is bouncing between dynamic s/r's and can indicate a paradigm shift in the market cycle.
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Timeframes and Assets
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This can be used effectively on all assets (stocks, crypto, forex, etc) and all time frames. As always with any indicator, the higher TF's are generally respected more than lower TF's.
Thanks for checking it out! I've been trading crypto for years and am just now beginning to publish my ideas, secret-sauce scripts and handy tools (like this one). If you enjoyed this indicator and would like to see more, a like and a follow is greatly appreciated 😁.
Price levelsThanks to the developers for adding arrays to TradingView. This gives you more freedom in Pine Script coding.
I have created an algorithm that draws support and resistance levels on a chart. The algorithm can be easily customized as you need.
This algorithm can help both intuitive and system traders. Intuitive traders just look at the drawn lines. For system traders, the "levels" array stores all level values. Thus, you can use these values for algorithmic trading.
McGinley Dynamic (Improved) - John R. McGinley, Jr.For all the McGinley enthusiasts out there, this is my improved version of the "McGinley Dynamic", originally formulated and publicized in 1990 by John R. McGinley, Jr. Prior to this release, I recently had an encounter with a member request regarding the reliability and stability of the general algorithm. Years ago, I attempted to discover the root of it's inconsistency, but success was not possible until now. Being no stranger to a good old fashioned computational crisis, I revisited it with considerable contemplation.
I discovered a lack of constraints in the formulation that either caused the algorithm to implode to near zero and zero OR it could explosively enlarge to near infinite values during unusual price action volatility conditions, occurring on different time frames. A numeric E-notation in a moving average doesn't mean a stock just shot up in excess of a few quintillion in value from just "10ish" moments ago. Anyone experienced with the usual McGinley Dynamic, has probably encountered this with dynamically dramatic surprises in their chart, destroying it's usability.
Well, I believe I have found an answer to this dilemma of 'susceptibility to miscalculation', to provide what is most likely McGinley's whole hearted intention. It required upgrading the formulation with two constraints applied to it using min/max() functions. Let me explain why below.
When using base numbers with an exponent to the power of four, some miniature numbers smaller than one can numerically collapse to near 0 values, or even 0.0 itself. A denominator of zero will always give any computational device a horribly bad day, not to mention the developer. Let this be an EASY lesson in computational division, I often entertainingly express to others. You have heard the terminology "$#|T happens!🙂" right? In the programming realm, "AnyNumber/0.0 CAN happen!🤪" too, and it happens "A LOT" unexpectedly, even when it's highly improbable. On the other hand, numbers a bit larger than 2 with the power of four can tremendously expand rapidly to the numeric limits of 64-bit processing, generating ginormous spikes on a chart.
The ephemeral presence of one OR both of those potentials now has a combined satisfactory remedy, AND you as TV members now have it, endowed with the ever evolving "Power of Pine". Oh yeah, this one plots from bar_index==0 too. It also has experimental settings tweaks to play with, that may reveal untapped potential of this formulation. This function now has gain of function capabilities, NOT to be confused with viral gain of function enhancements from reckless BSL-4 leaking laboratories that need to be eternally abolished from this planet. Although, I do have hopes this imd() function has the potential to go viral. I believe this improved function may have utility in the future by developers of the TradingView community. You have the source, and use it wisely...
I included an generic ema() plot for a basic comparison, ultimately unveiling some of this algorithm's unique characteristics differing on a variety of time frames. Also another unconstrained function is included to display some the disparities of having no limitations on a divisor in the calculation. I strongly advise against the use of umd() in any published script. There is simply just no reason to even ponder using it. I also included notes in the script to warn against this. It's funny now, but some folks don't always read/understand my advisories... You have been warned!
NOTICE: You have absolute freedom to use this source code any way you see fit within your new Pine projects, and that includes TV themselves. You don't have to ask for my permission to reuse this improved function in your published scripts, simply because I have better things to do than answer requests for the reuse of this simplistic imd() function. Sufficient accreditation regarding this script and compliance with "TV's House Rules" regarding code reuse, is as easy as copying the entire function as is. Fair enough? Good! I have a backlog of "computational crises" to contend with, including another one during the writing of this elaborate description.
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
RenkoNow you can plot a "Renko" chart on any timeframe for free! As with my previous algorithm, you can plot the "Linear Break" chart on any timeframe for free!
I again decided to help TradingView programmers and wrote code that converts a standard candles / bars to a "Renko" chart. The built-in renko() and security() functions for constructing a "Renko" chart are working wrong. Do not try to write strategies based on the built-in renko() function! The developers write in the manual: "Please note that you cannot plot Renko bricks from Pine script exactly as they look. You can only get a series of numbers similar to OHLC values for Renko bars and use them in your algorithms". However, it is possible to build a "Renko" chart exactly like the "Renko" chart built into TradingView. Personally, I had enough Pine Script functionality.
For a complete understanding of how such a chart is built, you can read to Steve Nison's book "BEYOND JAPANESE CANDLES" and see the instructions for creating a "Renko" chart:
Rule 1: one white brick (or series) is built when the price rises above the base price by a fixed threshold value or more.
Rule 2: one black brick (or series) is built when the price falls below the base price by a fixed threshold or more.
Rule 3: if the rise or fall of the price is less than the minimum fixed value, then new bricks are not drawn.
Rule 4: if today's closing price is higher than the maximum of the last brick (white or black) by a threshold or more, move to the column to the right and build one or more white bricks of equal height. A new brick begins with the maximum of the previous brick.
Rule 5: if today's closing price is below the minimum of the last brick (white or black) by a threshold or more, move to the column to the right and build one or more black bricks of equal height. A new brick begins with the minimum of the previous brick.
Rule 6: if the price is below the maximum or above the minimum, then new bricks are not drawn on the chart.
So my algorithm can to plot Traditional Renko with a fixed box size. I want to note that such a "Renko" chart is slightly different from the "Renko" chart built into TradingView, because as a base price I use (by default) close of first candle. How the developers of TradingView calculate the base price I don’t know. Personally, I do as written in the book of Steve Neeson.
The algorithm is very complicated and I do not want to explain it in detail. I will explain very briefly. The first part of the get_renko () function — // creating lists — creates two lists that record how many green bricks should be and how many red bricks. The second part of the get_renko () function — // creating open and close series — creates open and close series to plot bricks. So, this is a white box - study it!
As you understand, one green candle can create a condition under which it will be necessary to plot, for example, 10 green bricks. So the smaller the box size you make, the smaller the portion of the chart you will see.
I stuffed all the logic into a wrapper in the form of the get_renko() function, which returns a tuple of OHLC values. And these series with the help of the plotcandle() annotation can be converted to the "Renko" chart. I also want to note that with a large number of candles on the chart, outrages about the buffer size uncertainty are heard from the TradingView blackbox. Because of it, in the annotation study() set the value of the max_bars_back parameter.
In general, use this script (for example, to write strategies)!
Many Moving AveragesThis script allows you to add two moving averages to a chart, where the type of moving average can be chosen from a collection of 15 different moving average algorithms. Each moving average can also have different lengths and crossovers/unders can be displayed and alerted on.
The supported moving average types are:
Simple Moving Average ( SMA )
Exponential Moving Average ( EMA )
Double Exponential Moving Average ( DEMA )
Triple Exponential Moving Average ( TEMA )
Weighted Moving Average ( WMA )
Volume Weighted Moving Average ( VWMA )
Smoothed Moving Average ( SMMA )
Hull Moving Average ( HMA )
Least Square Moving Average/Linear Regression ( LSMA )
Arnaud Legoux Moving Average ( ALMA )
Jurik Moving Average ( JMA )
Volatility Adjusted Moving Average ( VAMA )
Fractal Adaptive Moving Average ( FRAMA )
Zero-Lag Exponential Moving Average ( ZLEMA )
Kauman Adaptive Moving Average ( KAMA )
Many of the moving average algorithms were taken from other peoples' scripts. I'd like to thank the authors for making their code available.
JayRogers
Alex Orekhov (everget)
Alex Orekhov (everget)
Joris Duyck (JD)
nemozny
Shizaru
KobySK
Jurik Research and Consulting for inventing the JMA.
BitradertrackerEste Indicador ya no consiste en líneas móviles que se cruzan para dar señales de entrada o salida, si no que va más allá e interpreta gráficamente lo que está sucediendo con el valor.
Es un algoritmo potente, que incluye 4 indicadores de tendencia y 2 indicadores de volumen.
Con este indicador podemos movernos con las "manos fuertes" del mercado, rastrear sus intenciones y tomar decisiones de compra y venta.
Diseñado para operar en criptomonedas.
En cuanto a qué temporalidad usar, cuanto más grande mejor, ya que al final lo que estamos haciendo es el análisis de datos y, por lo tanto, cuanto más datos, mejor. Personalmente recomiendo usarlo en velas de 30 minutos, 1 hora y 4 horas.
Recuerde, ningún indicador es 100% efectivo.
Este indicador nos muestra en las áreas de color púrpura (manos fuertes) y en las áreas de color verde (manos débiles) y al mostrármelo gráficamente ya el indicador vale la pena.
El mercado está impulsado por dos tipos de inversores, que se denominan manos fuertes o ballenas (agencias, fondos, empresas, bancos, etc.) y manos débiles o peces pequeños (es decir, nosotros).
No tenemos la capacidad de manipular un valor, ya que nuestra cartera es limitada, pero podemos ingresar y salir de los valores fácilmente ya que no tenemos mucho dinero.
Las ballenas pueden manipular un valor ya que tienen muchos bitcoins y / o dinero, sin embargo, no pueden moverse fácilmente.
Entonces, ¿como pueden comprar o vender sus monedas las ballenas? Bueno, ellos hacen su juego: Tratan de hacernos creer que la moneda esta barata cuando nos quieren vender sus monedas o hacernos creer que la moneda es cara cuando quieren comprar nuestras monedas. Esta manipulación se realiza de muchas maneras, la mayoría por noticias.
Nosotros, los pequeños peces, no podemos competir contra las ballenas, pero podemos descubrir qué están haciendo (recuerde, son lentas, mueven sus monstruosas cantidades de dinero) debemos movernos con ellas e imitarlas. Mejor estar bajo la ballena que delante de ella.
Con este indicador puedes ver cuando las ballenas están operando y reaccionar ; porque el enfoque matemático que los sustenta ha demostrado ser bastante exitoso.
Cuando las manos fuertes están por debajo de cero, se dice que están comprando. Lo mismo ocurre con las manos débiles. Generalmente, si las manos fuertes están comprando o vendiendo, el precio está lateralizado. El movimiento del precio está asociado con las compras y ventas realizadas por la mano débil.
Espero que les sea de mucha utilidad.
Bitrader4.0
This indicator no longer consists of mobile lines that intersect to give input or output signals, but it goes further and graphically interprets what is happening with the value.
It is a powerful algorithm, which includes 4 trend indicators and 2 volume indicators.
With this indicator we can move with the "strong hands" of the market, track their intentions and make buying and selling decisions.
Designed to operate in cryptocurrencies.
As for what temporality to use, the bigger the better, since in the end what we are doing is the analysis of data and, therefore, the more data, the better. Personally I recommend using it in candles of 30 minutes, 1 hour and 4 hours.
Remember, no indicator is 100% effective.
This indicator shows us in the areas of color purple (strong hands) and in the areas of color green (weak hands) and by showing it graphically and the indicator is worth it.
The market is driven by two types of investors, which are called strong hands or whales (agencies, funds, companies, banks, etc.) and weak hands or small fish (that is, us).
We do not have the ability to manipulate a value, since our portfolio is limited, but we can enter and exit the securities easily since we do not have much money.
Whales can manipulate a value since they have many bitcoins and / or money, however, they can not move easily.
So, how can whales buy or sell their coins? Well, they make their game: They try to make us believe that the currency is cheap when they want to sell their coins or make us believe that the currency is expensive when they want to buy our coins. This manipulation is done in many ways, most by news.
We, small fish, can not compete against whales, but we can find out what they are doing (remember, they are slow, move their monstrous amounts of money) we must move with them and imitate them. Better to be under the whale than in front of her.
With this indicator you can see when the whales are operating and reacting; because the mathematical approach that sustains them has proven to be quite successful.
When strong hands are below zero, they say they are buying. The same goes for weak hands. Generally, if strong hands are buying or selling, the price is lateralized. The movement of the price is associated with the purchases and sales made by the weak hand.
I hope you find it very useful.
Bitrader4.0
META: STDEV Study (Scripting Exercise)While trying to figure out how to make the STDEV function use an exponential moving average instead of simple moving average , I discovered the builtin function doesn't really use either.
Check it out, it's amazing how different the two-pass algorithm is from the builtin!
Eventually I reverse-engineered and discovered that STDEV uses the Naiive algorithm and doesn't apply "Bessel's Correction". K can be 0, it doesn't seem to change the data although having it included should make it a little more precise.
en.wikipedia.org
Acc/DistAMA with FRACTAL DEVIATION BANDS by @XeL_ArjonaACCUMULATION/DISTRIBUTION ADAPTIVE MOVING AVERAGE with FRACTAL DEVIATION BANDS
Ver. 2.5 @ 16.09.2015
By Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the
author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by:
Stocks & Commodities V. 21:10 (68-72): "Bull And Bear Balance Indicator by Vadim Gimelfarb"
Fractal Deviation Bands by @XeL_Arjona.
Color Cloud Fill by @ChrisMoody
CHANGE LOG:
Following a "Fractal Approach" now the lookback window is hardcode correlated with a given timeframe. (Default @ 126 days as Half a Year / 252 bars)
Clean and speed up of Adaptive Moving Average Algo.
Fractal Deviation Band Cloud coloring smoothed.
>
ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingVew accounts at: @XeL_Arjona
Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. Copyright 2015
Volume Pressure Composite Average with Bands by @XeL_ArjonaVOLUME PRESSURE COMPOSITE AVERAGE WITH BANDS
Ver. 1.0.beta.10.08.2015
By Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm" by :
Stocks & Commodities V. 21:10 (68-72):
"Bull And Bear Balance Indicator by Vadim Gimelfarb"
Adjusted Exponential Adaptation from original Volume Weighted Moving Average (VEMA) by @XeL_Arjona with help given at the @pinescript chat room with special mention to @RicardoSantos
Color Cloud Fill Condition algorithm by @ChrisMoody
WHAT IS THIS?
The following indicators try to acknowledge in a K-I-S-S approach to the eye (Keep-It-Simple-Stupid), the two most important aspects of nearly every trading vehicle: -- PRICE ACTION IN RELATION BY IT'S VOLUME --
A) My approach is to make this indicator both as a "Trend Follower" as well as a Volatility expressed in the Bands which are the weighting basis of the trend given their "Cross Signal" given by the Buy & Sell Volume Pressures algorithm. >
B) Please experiment with lookback periods against different timeframes. Given the nature of the Volume Mathematical Monster this kind of study is and in concordance with Price Action; at first glance I've noted that both in short as in long term periods, the indicator tends to adapt quite well to general price action conditions. BE ADVICED THIS IS EXPERIMENTAL!
C) ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingVew accounts at: @XeL_Arjona
Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. --- All Authorship Rights RESERVED 2015 ---
Quicksilver Institutional Trend [1H] The "God Candle" Catcher Most retail traders fail because they lack institutional tooling.
The Quicksilver Institutional Trend is designed to keep you in the trade during massive expansion moves and keep you out during the chop. It replaces "guessing" with a structured, math-based Trend Cloud.
THE LOGIC (Institutional Engine):
Visual Trend Cloud: A dynamic ribbon that identifies the dominant 1H market regime.
Momentum Filter (ADX): The bars change color based on Trend Strength.
Bright Green/Red: High Momentum (Institutional Volume). Stay in the trade.
Dark Green/Red: Low Momentum. Prepare to exit.
Liquidity Zones: Automatically draws Support & Resistance lines at recent institutional pivot points.
👨💻 NEED A CUSTOM BOT?
Stop trading manually. We can convert YOUR specific strategy into an automated algorithm.
Quicksilver Algo Systems specializes in building custom solutions for:
TradeLocker Studio (Python)
TradingView (Pine Script)
cTrader (C#)
MetaTrader 4/5 (MQL)
We don't just sell indicators; we engineer automated execution systems tailored to your exact risk parameters.
🚀 HOW TO HIRE US:
If you have a strategy you want automated, we are currently accepting new custom development projects.
Contact the Lead Developer directly:
📧 Email: quicksilveralgo@gmail.com
(Include "Custom Bot Request" in the subject line for priority review).
🔥 UNLOCK THE NEXT INDICATOR:
We are releasing our "Sniper Scalper" logic next week.
Hit the BOOST (Rocket) Button 🚀 above.
Click FOLLOW on our profile.
Comment "QAS" below if you want to be notified.
Disclaimer: Trading involves substantial risk. Educational purposes only.
CEF (Chaos Theory Regime Oscillator)Chaos Theory Regime Oscillator
This script is open to the community.
What is it?
The CEF (Chaos Entropy Fusion) Oscillator is a next-generation "Regime Analysis" tool designed to replace traditional, static momentum indicators like RSI or MACD. Unlike standard oscillators that only look at price changes, CEF analyzes the "character" of the market using concepts from Chaos Theory and Information Theory.
It combines advanced mathematical engines (Hurst Exponent, Entropy, VHF) to determine whether a price movement is a real trend or just random noise. It uses a novel "Adaptive Normalization" technique to solve scaling problems common in advanced indicators, ensuring the oscillator remains sensitive yet stable across all assets (Crypto, Forex, Stocks).
What It Promises:
Intelligent Filtering: Filters out false signals in sideways (volatile) markets using the Hurst Base to measure trend continuity.
Dynamic Adaptation: Automatically adapts to volatility. Thanks to trend memory, it doesn't get stuck at the top during uptrends or at the bottom during downtrends.
No Repainting: All signals are confirmed at the close of the bar. They don't repaint or disappear.
What It Doesn't Promise:
Magic Wand: It's a powerful analytical tool, not a crystal ball. It determines the regime, but risk management is up to the investor.
Late-Free Holy Grail: It deliberately uses advanced correction algorithms (WMA/SMA) to provide stability and filter out noise. Speed is sacrificed for accuracy.
Which Concepts Are Used for Which Purpose?
CEF is built on proven mathematical concepts while creating a unique "Fusion" mechanism. These are not used in their standard forms, but are remixed to create a consensus engine:
Hurst Exponent: Used to measure the "memory" of the time series. Tells the oscillator whether there is a probability of the trend continuing or reversing to the mean.
Vertical Horizontal Filter (VHF): Determines whether the market is in a trend phase or a congestion phase.
Shannon Entropy: Measures the "irregularity" or "unpredictability" of market data to adjust signal sensitivity.
Adaptive Normalization (Key Innovation): Instead of fixed limits, the oscillator dynamically scales itself based on recent historical performance, solving the "flat line" problem seen in other advanced scripts.
Original Methodology and Community Contribution
This algorithm is a custom synthesis of public domain mathematical theories. The author's unique contribution lies in the "Adaptive Normalization Logic" and the custom weighting of Chaos components to filter momentum.
Why Public Domain? Standard indicators (RSI, MACD) were developed for the markets of the 1970s. Modern markets require modern mathematics. This script is presented to the community to demonstrate how Regime Analysis can improve trading decisions compared to static tools.
What Problems Does It Solve?
Problem 1: The "Stagnant Market" Trap
CEF Solution: While the RSI gives false signals in a sideways market, CEF's Hurst/VHF filter suppresses the signal, essentially making the histogram "off" (or weak) during noise.
Problem 2: The "Overbought" Fallacy
CEF Solution: In a strong trend (Pump/Dump), traditional oscillators get stuck at 100 or 0. CEF uses "Trend Memory" to understand that an overbought price is not a reversal signal but a sign of trend strength, and keeps the signal green/red instead of reversing it prematurely. Problem 3: Visual Confusion
CEF Solution: Instead of multiple lines, it presents a single, color-coded histogram featuring only prominent "Smart Circles" at high-probability reversal points.
Automation Ready: Custom Alerts
CEF is designed for both manual trading and automation.
Smart Buy/Sell Circles: Visual signals that only appear when trend filters are aligned with momentum reversals.
Deviation Labels: Automatically detects and labels structural divergences between price and entropy.
Disclaimer: This indicator is for educational purposes only. Past performance does not guarantee future results. Always practice appropriate risk management.
Gyspy Bot Trade Engine - V1.2B - Alerts - 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Alerts & Visualization
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script V6 environment. While most tools rely on a single dominant indicator to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
Note: This is the Indicator / Alerts version of the engine. It is designed for visual analysis and generating live alert signals for automation. If you wish to see Backtest data (Equity Curves, Drawdown, Profit Factors), please use the Strategy version of this script.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only fires a signal plot when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to signal forced exits, preserving capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the charts look perfect in hindsight, only to have the signals fail in live markets because they were tuned to historical noise rather than market structure.
To use this engine successfully:
Visual Verification: Do not just look for "green arrows." Look for signals that occur at logical market structure points.
Stability: Ensure signals are not flickering. This script uses closed-candle logic for key decisions to ensure that once a signal plots, it remains painted.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Gypsy Bot settings should be reviewed and adjusted at regular intervals to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY plot a Buy Signal if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the signal is rejected.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: Filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold.
Module 2: Correlation Trend Indicator (CTI)
Logic: Measures how closely the current price action correlates to a straight line (a perfect trend).
Function: Ensures that we are moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A spectral filter combining High-Pass (trend removal) and Super Smoother (noise removal).
Function: Isolates the "Roof" of price action to catch cyclical turning points before standard moving averages.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: Signals when the regression trend flips. Offers "Aggressive" and "Conservative" calculation modes.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from extremes.
Function: Used as an entry filter. If price is above the Chandelier line, the trend is Bullish.
Module 6: Crypto Market Breadth (CMB)
Logic: Pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts).
Function: Calculates "Market Health." If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator using Advance/Decline and Volume data.
Function: One of the most powerful modules. Confirms that price movement is supported by actual volume flow. Recommended setting: "SSMA" (Super Smoother).
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis.
Function: Checks for a "Kumo Breakout." Price must be fully above/below the Cloud to confirm entry.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes harmonic wave properties to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector.
Module 11: HSRS Compression / Super AO
Logic: Detects volatility compression (HSRS) or Momentum/Trend confluence (Super AO).
Function: Great for catching explosive moves resulting from consolidation.
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. Uses Multi-Timeframe (MTF) logic to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors.
Bitcoin Halving Logic: Prevents trading during chaotic weeks surrounding Halving events (dates projected through 2040).
Miner Capitulation: Uses Hash Rate Ribbons to identify bearish regimes when miners are shutting down.
ADX Filter: Prevents trading in "Flat/Choppy" markets (Low ADX).
CryptoCap Trend: Checks the total Crypto Market Cap chart for broad market alignment.
6. Risk Management & The Dump Protection Team (DPT)
Even in this Indicator version, the RM logic runs to generate Exit Signals.
Dump Protection Team (DPT): Detects "Nuke" (Crash) or "Moon" (Pump) volatility signatures. If triggered, it plots an immediate Exit Signal (Yellow Plot).
Advanced Adaptive Trailing Stop (AATS): Dynamically tightens stops in low volatility ("Dungeon") and loosens them in high volatility ("Penthouse").
Staged Take Profits: Plots TP1, TP2, and TP3 events on the chart for visual confirmation or partial exit alerts.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These filter out bad signals during high volatility.
Tune Module 8 (MTI): Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders to filter out noise.
Alert Setup: Once visually satisfied, use the "Any Alert Function Call" option when creating an alert in TradingView to capture all Buy/Sell/Close events generated by the engine.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This indicator uses Closed Candle data for all Risk Management and Entry decisions. This ensures that signals do not vanish after the candle closes.
Visuals:
Blue Plot: Buy/Sell Signal.
Yellow Plot: Risk Management (RM) / DPT Close Signal.
Green/Lime/Olive Plots: Take Profit hits.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Cryptocurrency trading involves substantial risk of loss. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure.
To use this engine successfully, you must adopt a specific optimization mindset:
Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless.
Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the trade is rejected.
This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal.
Module 2: Correlation Trend Indicator (CTI)
Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend).
Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise).
Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts).
Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support.
Module 6: Crypto Market Breadth (CMB)
Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges.
Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data.
Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart.
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen.
Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up.
Module 11: HSRS Compression / Super AO
Logic: Two options in one.
HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands.
Super AO: A combination of the Awesome Oscillator and SuperTrend logic.
Function: Great for catching explosive moves that result from periods of low volatility (consolidation).
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked.
Bitcoin Halving Logic:
Hardcoded dates for past and projected future Bitcoin halvings (up to 2040).
Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes.
Miner Capitulation:
Uses Hash Rate Ribbons (Moving averages of Hash Rate).
If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat.
ADX Filter (Flat Market Protocol):
If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market.
CryptoCap Trend:
Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins.
6. Risk Management & The Dump Protection Team (DPT)
Gypsy Bot separates "Entry Logic" from "Risk Management Logic."
Dump Protection Team (DPT)
This is a specialized logic branch designed to save the account during Black Swan events.
Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit.
Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction.
Advanced Adaptive Trailing Stop (AATS)
Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic.
Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks.
Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital.
Staged Take Profits
TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win.
TP2: Take the bulk of profit.
TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance.
Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative).
Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals).
Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
ICT Fair Value Gap Detector [Eˣ]⚡ Fair Value Gap Detector
Overview
The Fair Value Gap Detector automatically identifies price imbalances on your charts - the inefficiencies left behind when price moves too quickly. This indicator reveals where price is likely to return for "rebalancing", based on ICT (Inner Circle Trader) concepts of market efficiency.
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🎯 What This Indicator Does
Detects Fair Value Gaps:
• 🟢 Bullish FVG - Gap left below during aggressive upward move
• 🔴 Bearish FVG - Gap left above during aggressive downward move
• Automatically identifies 3-candle price inefficiencies
• Works on all timeframes and instruments
Smart Fill Tracking:
• Full Fill - Price completely fills the gap
• 50% Fill - Price fills half the gap (critical level)
• Partial Fill - Price touches gap edge
• Real-time fill percentage tracking
• Auto-removes filled gaps (optional)
Professional Features:
• Active Gap Highlighting - Shows nearest unfilled gap
• Distance Calculator - Displays how far price is from gaps
• Market Bias - Analysis based on gap balance
• Size Filtering - Minimum gap size to avoid noise
• Visual Clarity - Clean boxes with color-coding
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📚 Understanding Fair Value Gaps
What Are Fair Value Gaps?
Fair Value Gaps (FVGs), also known as imbalances or inefficiencies, are zones where price moved so quickly that normal trading didn't occur. They represent:
• Price Imbalance - One-sided aggressive buying or selling
• Unfair Pricing - Some participants didn't get to trade at these levels
• Market Inefficiency - Supply/demand equilibrium was disrupted
• Rebalancing Zones - Price often returns to "fill" these gaps
The ICT Concept:
Markets constantly seek equilibrium (fair value). When price moves too fast:
1. It leaves gaps where normal trading didn't happen
2. These gaps represent unfair/inefficient pricing
3. Market has a tendency to return and "rebalance"
4. Smart money knows this and trades the fills
Why FVGs Work:
• Unfilled Orders - Traders who missed the move have pending orders in the gap
• Algorithmic Trading - Algos programmed to exploit inefficiencies
• Market Psychology - Traders notice gaps and place orders there
• Institutional Behavior - Smart money uses gaps for entries/exits
FVG vs Regular Gaps:
• Regular Gaps - Occur at market open, between daily closes
• Fair Value Gaps - Occur intraday, between 3 consecutive candles
• FVGs happen more frequently and on all timeframes
• FVGs are more tradeable for intraday/swing traders
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🟢 Bullish Fair Value Gaps Explained
How They Form:
Bullish FVG requires 3 candles:
1. Candle 1 - Any candle (sets the high reference)
2. Candle 2 - Strong bullish candle (aggressive buying)
3. Candle 3 - Continuation candle
The Gap: Candle 3's LOW is above Candle 1's HIGH = Gap left unfilled
Visual Example:
```
Candle 3: Low at $105 ──────────┐
│ ← GAP (Bullish FVG)
Candle 2: Strong bullish │
│
Candle 1: High at $100 ──────────┘
```
What It Means:
• Price jumped from $100 to $105+ so fast, no trading occurred in between
• This $100-$105 zone is "unfair" - buyers/sellers didn't get to trade there
• Market may return to this zone to "rebalance"
• When price returns, it often acts as support
Trading Bullish FVGs:
Strategy:
• Wait for price to retrace down into the bullish FVG (green box)
• Look for rejection/bounce from the gap zone
• Enter long when price respects the FVG as support
• Stop loss: Below the FVG
• Target: Previous high or opposite FVG
Best Entry Points:
• 50% Fill: Price enters middle of gap (highest probability)
• Full Fill: Price touches bottom of gap (aggressive entry)
• Tap & Reject: Price quickly enters and exits gap (strong signal)
Example Trade:
• Bullish FVG forms: $50,000 - $50,500 (500 point gap)
• Price rallies to $52,000 then retraces
• Price drops to $50,250 (50% of gap filled)
• Bullish reversal candle appears
• Enter long at $50,500, stop at $49,800
• Target: $52,000+
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🔴 Bearish Fair Value Gaps Explained
How They Form:
Bearish FVG requires 3 candles:
1. Candle 1 - Any candle (sets the low reference)
2. Candle 2 - Strong bearish candle (aggressive selling)
3. Candle 3 - Continuation candle
The Gap: Candle 3's HIGH is below Candle 1's LOW = Gap left unfilled
Visual Example:
```
Candle 1: Low at $100 ───────────┐
│ ← GAP (Bearish FVG)
Candle 2: Strong bearish │
│
Candle 3: High at $95 ───────────┘
```
What It Means:
• Price dropped from $100 to $95 so fast, no trading occurred in between
• This $95-$100 zone is "unfair" - buyers/sellers didn't get to trade there
• Market may return to this zone to "rebalance"
• When price returns, it often acts as resistance
Trading Bearish FVGs:
Strategy:
• Wait for price to retrace up into the bearish FVG (red box)
• Look for rejection/reversal from the gap zone
• Enter short when price respects the FVG as resistance
• Stop loss: Above the FVG
• Target: Previous low or opposite FVG
Best Entry Points:
• 50% Fill: Price enters middle of gap (highest probability)
• Full Fill: Price touches top of gap (aggressive entry)
• Tap & Reject: Price quickly enters and exits gap (strong signal)
Example Trade:
• Bearish FVG forms: $48,000 - $48,500 (500 point gap)
• Price drops to $46,000 then retraces
• Price rallies to $48,250 (50% of gap filled)
• Bearish reversal candle appears
• Enter short at $48,000, stop at $48,700
• Target: $46,000-
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📊 How To Use This Indicator
Strategy 1: FVG Rebalancing (Classic)
Best For: Swing trading, reversal trading
Timeframes: 15min, 1H, 4H
Win Rate: 65-75%
Entry Rules:
1. Identify unfilled FVG (bright color, not gray)
2. Wait for price to return to the gap
3. Best entry: 50% fill of the gap
4. Look for reversal confirmation:
• Bullish FVG: Pin bar, engulfing, hammer
• Bearish FVG: Shooting star, bearish engulfing
5. Enter when price bounces/rejects from FVG
6. Stop: Beyond opposite side of FVG
7. Target: 2-3R or previous high/low
Why It Works: 70%+ of FVGs get filled, and 60%+ show reaction
Strategy 2: FVG + Order Block Confluence
Best For: High-probability setups
Timeframes: 1H, 4H
Win Rate: 75-85%
Entry Rules:
1. Find FVG that overlaps with Order Block
2. This creates a "super zone" of confluence
3. Wait for price to return to this zone
4. Enter on first touch of confluence zone
5. Stop: Beyond the confluence zone
6. Target: 3-4R
Why It Works: Double institutional concepts = highest probability
Strategy 3: Multi-Timeframe FVG
Best For: Position trading, major moves
Timeframes: Combine Daily + 4H or 4H + 1H
Win Rate: 70-80%
Entry Rules:
1. Identify large FVG on higher timeframe (Daily/4H)
2. Wait for price to enter this HTF FVG
3. Switch to lower timeframe (4H/1H)
4. Look for LTF FVG within HTF FVG in same direction
5. Trade the LTF FVG fill
6. Stop: Below LTF FVG
7. Target: Exit HTF FVG or beyond
Why It Works: Timeframe alignment = institutional consensus
Strategy 4: FVG Rejection Trade
Best For: Quick scalps, day trading
Timeframes: 5min, 15min
Win Rate: 60-70%
Entry Rules:
1. Price enters FVG zone
2. Immediate rejection (strong reversal candle)
3. Enter on close of rejection candle
4. Tight stop beyond FVG
5. Quick target: 1-2R
Why It Works: Strong rejection = institutional defense of level
Strategy 5: FVG-to-FVG Trading
Best For: Momentum trading
Timeframes: 15min, 1H
Win Rate: 55-65%
Entry Rules:
1. Identify bullish FVG below and bearish FVG above
2. Enter long at bullish FVG, target bearish FVG
3. Or enter short at bearish FVG, target bullish FVG
4. Price often moves from one imbalance to another
5. Stop: Beyond trading FVG
6. Target: Opposite FVG
Why It Works: Price rebalances from one inefficiency to another
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⚙️ Settings Explained
Display Settings
Show Bullish/Bearish FVG
• Toggle each type on/off independently
• Customize colors for each FVG type
• Default: Green (bullish), Red (bearish)
• Tip: Use colors that contrast with your chart
Max FVG to Display (Default: 20)
• Limits how many gaps are shown at once
• Lower (10-15): Cleaner chart, recent gaps only
• Higher (30-50): More historical context
• Recommended: 15-25 for most trading
Show FVG Labels (Default: ON)
• Displays "FVG+" and "FVG-" text on gaps
• Shows 🎯 on active (nearest) gap
• Shows fill percentage (e.g., "FVG+ 35%")
• Turn OFF for minimal appearance
• Recommended: Keep ON for clarity
Extend Gaps (bars) (Default: 50)
• How far to extend gap boxes to the right
• Lower (20-30): Shorter boxes
• Higher (100+): Longer boxes, easier to see
• Gaps auto-extend until filled or limit reached
• Recommended: 40-60 bars
Filters
Min Gap Size % (Default: 0.05)
• Minimum gap size as percentage of price
• Filters out tiny, insignificant gaps
• Crypto: 0.05-0.15% (high volatility)
• Forex: 0.03-0.10% (moderate volatility)
• Stocks: 0.05-0.20% (varies by stock)
• Indices: 0.05-0.15%
• Adjust based on instrument's average move
Show Filled Gaps (Default: OFF)
• When ON: Shows gray boxes for filled gaps
• When OFF: Gaps disappear after mitigation
• Use ON: For learning and backtesting
• Use OFF: For clean, active trading view
Advanced Settings
Auto-Detect Mitigation (Default: ON)
• Automatically tracks when gaps are filled
• Updates fill percentage in real-time
• Marks gaps as "mitigated" when filled
• Recommended: Keep ON
Mitigation Type (Default: Full)
• Full: Gap considered filled when price closes through entire gap
• 50%: Gap considered filled at 50% (critical level)
• Partial: Gap considered filled on first touch
• For learning: Use "Full"
• For aggressive trading: Use "50%"
• For conservative trading: Use "Partial"
Highlight Nearest Gap (Default: ON)
• Highlights the closest unfilled gap to current price
• Active gap shown with 🎯 emoji and brighter color
• Helps focus on most relevant opportunity
• Recommended: Keep ON
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📱 Info Panel Guide
Bullish FVG Count
• Number of active (unfilled) bullish fair value gaps
• Higher number = More potential support zones below
• Multiple bullish FVGs = Strong rebalancing demand
Bearish FVG Count
• Number of active (unfilled) bearish fair value gaps
• Higher number = More potential resistance zones above
• Multiple bearish FVGs = Strong rebalancing supply
Bias Indicator
• ⬆ Bullish: More bullish FVGs than bearish
• ⬇ Bearish: More bearish FVGs than bullish
• ↔ Neutral: Equal FVGs on both sides
• Market tends to fill nearby gaps first
Target Indicator
• Shows nearest unfilled gap and distance
• Example: "Bull FVG -1.25%" = Bullish gap is 1.25% below price
• Example: "Bear FVG +0.85%" = Bearish gap is 0.85% above price
• Watch for price to reach these targets
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📱 Alert Setup
This indicator includes 4 alert types:
1. Price Entering Bullish FVG
• Fires when price drops into a bullish gap
• Action: Watch for bounce/reversal
• High-probability long setup developing
2. Price Entering Bearish FVG
• Fires when price rallies into a bearish gap
• Action: Watch for rejection/reversal
• High-probability short setup developing
3. New Bullish FVG Detected
• Fires when a new bullish gap forms
• Action: Mark zone for future fill
• New rebalancing target below identified
4. New Bearish FVG Detected
• Fires when a new bearish gap forms
• Action: Mark zone for future fill
• New rebalancing target above identified
To Set Up Alerts:
1. Click "Alert" button (clock icon)
2. Select "Fair Value Gap Detector"
3. Choose your alert condition
4. Configure notification method
5. Click "Create"
Pro Tip: Set "Price Entering" alerts to catch fills in real-time
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💎 Pro Tips & Best Practices
✅ DO:
• Wait for 50% fill - Middle of gap has highest win rate (65-70%)
• Use confirmation - Don't trade just because price touched gap
• Combine with structure - FVG + support/resistance = high probability
• Trade first fill - Unfilled gaps have better success rate than refilled
• Respect full fills - Once fully filled, gap is less reliable
• Use multiple timeframes - HTF FVGs are stronger than LTF
• Check session timing - FVGs work best during London/NY sessions
• Follow the bias - More bullish FVGs = favor longs
⚠️ DON'T:
• Don't blindly fade gaps - Wait for price action confirmation
• Don't ignore momentum - Strong trends can blow through FVGs
• Don't trade every gap - Quality over quantity
• Don't assume all gaps fill - About 70-80% fill, 20-30% don't
• Don't use tight stops - Allow room for wick into gap
• Don't overtrade - Wait for confluence and confirmation
• Don't fight trends - Best FVG trades are with higher TF trend
• Don't ignore fill percentage - 50% is often the sweet spot
🎯 Best Timeframes:
• Scalpers: 1min, 5min (many gaps, quick fills)
• Day Traders: 5min, 15min, 1H (balanced)
• Swing Traders: 1H, 4H, Daily (larger, more reliable gaps)
• Position Traders: 4H, Daily, Weekly (major imbalances)
🔥 Best Instruments:
• Excellent: BTC, ETH, ES, NQ, Forex majors (clean price action)
• Good: Gold, Oil, Major indices, Large-cap stocks
• Moderate: Altcoins, small-cap stocks (more noise)
• Best Markets: Trending markets with clear swings
⏰ Best Times for FVG Trading:
• London Session: High volume = reliable gap fills
• NY Session: Strong moves create quality gaps
• London-NY Overlap: Best time for gap creation and fills
• Asian Session: Lower probability, wait for London
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🎓 Advanced FVG Concepts
FVG Mitigation Levels
Understanding fill percentages:
• 0-25% Fill: Gap barely touched, often continues without fill
• 25-50% Fill: Partial rebalancing, may reverse here
• 50% Fill: CRITICAL LEVEL - Highest probability reversal zone
• 50-75% Fill: Deep rebalancing, strong reversal likely
• 75-100% Fill: Full rebalancing, gap's purpose fulfilled
Why 50% Matters: Market seeks equilibrium, and 50% represents perfect balance
FVG Inversions
When price breaks through a gap completely:
• Bullish FVG that's broken becomes bearish (support → resistance)
• Bearish FVG that's broken becomes bullish (resistance → support)
• Inverted gaps are weaker than fresh gaps
• Trading: Can fade the inverted gap but with caution
FVG Confluence Zones
Multiple FVGs at similar level:
• Creates "super gap" or confluence zone
• Much higher probability of reaction
• Wider zone for entries (more room for stops)
• Often aligns with other institutional concepts
FVG + Order Block Combo
When FVG overlaps with Order Block:
• Double institutional concept
• Extremely high probability setup (75-85% win rate)
• Price drawn to fill gap AND test order block
• Use tight stops, generous targets (3-5R possible)
Nested FVGs (Multi-Timeframe)
Small FVG inside larger FVG:
• Daily FVG contains 4H FVG contains 1H FVG
• Trade the smallest FVG in direction of larger ones
• Highest probability when all aligned
• Progressive targets: Fill small → medium → large gaps
FVG Exhaustion
When price creates multiple FVGs in same direction:
• Indicates strong momentum/impulsive move
• Each gap represents acceleration
• Last gap often signals exhaustion
• Watch for reversal after filling final gap
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📈 Common FVG Patterns
Pattern 1: The Perfect Rebalance
• FVG forms during strong move
• Price continues 100+ pips
• Clean return to 50% of gap
• Immediate reversal
• Textbook setup, 70%+ win rate
Pattern 2: The Double Fill
• Price partially fills gap (25%)
• Weak reaction, continues
• Returns again for deeper fill (75%)
• Strong reversal on second fill
• Second fill often better entry
Pattern 3: The Blow-Through
• Price approaches gap
• Completely ignores it, no reaction
• Keeps going in same direction
• Sign of very strong momentum
Pattern 4: The Magnet Effect
• Price slowly grinds toward gap
• Accelerates as it gets close
• Quickly fills and reverses
• Common in ranging markets
Pattern 5: The False Fill
• Price wicks into gap briefly
• Immediately reverses without filling
• "Stop hunt" or liquidity grab
• Gap remains unfilled
• Often precedes strong move
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🚀 What Makes This Different?
Unlike basic gap indicators, Fair Value Gap Detector:
• ICT Methodology - Based on proven institutional concepts
• Real-Time Fill Tracking - Shows percentage filled as it happens
• 3 Mitigation Types - Full, 50%, Partial for different strategies
• Active Gap Highlighting - Shows most relevant opportunity
• Smart Filtering - Minimum size to avoid noise
• Visual Clarity - Clean, professional appearance
• Auto-Management - Removes filled gaps automatically
• Distance Tracking - Know exactly where price needs to go
Based On Professional Concepts:
• ICT Fair Value Gap theory
• Market efficiency principles
• Price rebalancing dynamics
• Institutional order flow analysis
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📈 FVG Statistics & Probabilities
Based on ICT concepts and trader observations:
Gap Fill Rates:
• 70-80% of FVGs get filled eventually
• 60-70% show some reaction when filled
• 50% fill level has ~65% reversal rate
• Full fills have ~55% reversal rate
Timeframe Reliability:
• Daily FVGs: ~75-85% fill rate, strongest reactions
• 4H FVGs: ~70-80% fill rate, strong reactions
• 1H FVGs: ~65-75% fill rate, good reactions
• 15min FVGs: ~60-70% fill rate, moderate reactions
• 5min FVGs: ~55-65% fill rate, weaker reactions
Best Practices:
• First touch of gap = 65-70% win rate
• 50% fill = 65% win rate
• FVG + Order Block = 75-85% win rate
• Multi-timeframe aligned FVG = 70-80% win rate
• FVG in trending market = 60-70% win rate
Common Failures:
• Strong momentum blows through gaps (20-30% of time)
• Gaps in low-volume periods less reliable
• Very small gaps (<0.05%) often ignored
• Counter-trend gaps have lower success rate
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Questions about Fair Value Gaps? Feel free to ask in the comments.
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Version History
• v1.0 - Initial release with 3-candle FVG detection and real-time fill tracking
AlphaNatt | FINAL REVELATION [Visual God]AlphaNatt | The Final Revelation
"Where Information Theory meets Market Geometery."
The AlphaNatt is a comprehensive market structure and volumetric analysis suite designed for the institutional-grade trader. It merges advanced quantitative concepts—specifically Shannon Entropy and Neural Pattern Filtering—with a "Holographic" visual interface that prioritizes clarity over clutter.
This is not just an indicator; it is a complete decision-support system that answers three critical questions:
Is the market chaotic or ordered? (Entropy Engine)
Where is the liquidity? (Volumetric Heatmap)
What is the true structure? (Fractal Geometry)
🌌 The Gen 100 Math Engine
At the core of this script lies a unique implementation of Information Theory.
1. Shannon Entropy (The Chaos Filter)
Most indicators fail because they try to predict "Noise". This script calculates the Entropy (in Bits) of the recent price action.
High Entropy: The market is in a "Random Walk" state. Visuals fade out, transparency increases, and signals are suppressed.
Low Entropy: The market is "Ordered" and approaching a singularity/decision point. Visuals glow brightly to indicate a high-probability environment.
2. Neural Pattern Recognition
The diamond signals (Cyan/Magenta) are not simple simple crossovers. They are driven by a composite logic simulating a neural filter:
Inputs: Normalised RSI + Momentum Divergence + Volatility State.
Logic: Signals only trigger when the market is statistically overextended AND showing signs of momentum decay.
💎 Holographic Features
🔥 Volumetric Heatmap
The script scans historical price action to build a Volume Profile Heatmap on the right side of the chart.
Purple/Blue Zones: These represent High Volume Nodes (HVNs). These act as "Gravity Wells" for price—often stopping trends or acting as launchpads for reversals.
POC (Point of Control): The bright green line indicates the price level with the absolute highest volume in the lookback period.
🌀 Fractal Structure Lines
Price action is often noisy. The script uses a Fractal Pivot Algorithm (Length 5) to identify the "True Highs" and "True Lows".
It connects these points with dashed "Neural Lines" to show the naked market skeleton.
This instantly reveals if you are in a trend of Higher Highs or a breakdown of Lower Lows.
🖥️ The Heads-Up Display (HUD)
A minimalist dashboard keeps you informed of the math underneath:
ENTROPY: The raw bit-score of market chaos.
REGIME: Tells you instantly if you are in "ORDER" (Tradeable) or "CHAOS" (Sit out).
STRUCT: Real-time status of the fractal structure (Breakout/Breakdown/Ranging).
⚙️ Settings & Configuration
Theme: Choose between "Cyber" (Neon), "Aeon" (Deep Blue), or "Gold" (Luxury).
Max Entropy: Adjust the sensitivity of the Chaos Filter. Lower values = stricter filtering (fewer trades).
Heatmap Depth: Control how far back the volume profile scans.
⚠️ Disclaimer
This tool is designed for educational market analysis. "Entropy" and "Neural" refer to the mathematical algorithms used to process price data and do not guarantee future performance. Always manage risk responsible.
