iBagging Multi-IndicatorHello traders!
You know, machine learning is a very popular theme nowadays. The best tricks and methods were borrowed from Math and Computer Science to improve and create ML algorithms. As you know, one of our analysts is a great fan of ML, thus he decided to borrow on very powerful method from ML.
We have taken 5 indicators, tuned them a bit and make them to vote. If the number of voters is more than the threshold the the bullish/bearish signal shows. It's called Bagging, when some algorithms are voting to classify or to regress. We use EMA Cross with NATR filter, BB Width, divergency detector and bull bear power. This bundle in my opinion is one of the best to define entries. Check it up in you daily trading staff. You shouldn't forget about tuning the parameters on different coins and timeframes. We checked it on 1H BTCUSDT and default parameters are for this combination. I hope you'll enjoy my masterpiece.
How to use it?
Just add it to the chart and check up signals.
在腳本中搜尋"algo"
Trend Follow SystemTrend following algorithm:
We take 1- 5 Fibonacci Ema values. 21, 34, 55, 89, 144
2- We normalize the changes of these values over time between 1-100.
3- We take the ema value of 1 length so that it does not follow a horizontal course after the normalization process.
4- In order not to experience too much change, we take the value of sma with a length of 5.
5-We think that when all values are 100, the trend is up, when all values are 0, the trend is down, otherwise the trend is horizontal.
[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.
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 ---
VRVP Clone + Multi-POC -- PerroGordoVRVP Clone + Multi-POC
Overview
VRVP Clone + Multi-POC replicates TradingView's native Visible Range Volume Profile with several practical enhancements. The indicator displays volume distribution across price levels for the visible chart range, which is useful for identifying high-volume nodes, support/resistance zones, and areas of price acceptance.
The main differentiator from the built-in VRVP is support for multiple Point of Control (POC) lines with an intelligent peak detection algorithm. Instead of just showing the single highest-volume level, you can identify distinct volume clusters across different price zones.
Features
Dynamic Visible Range
Recalculates automatically on scroll or zoom
Analyzes only visible bars
Profile width scales proportionally to view
Multiple POC Detection (1-8 levels)
Volume Nodes Mode: Peak detection algorithm finds local volume maxima across distinct price clusters
Highest Rows Mode: Traditional approach - top N rows by raw volume
Configurable minimum separation between nodes to prevent bunching
Individual colors for each POC level
Volume Display Modes
Up/Down: Split bars showing buy vs. sell volume with black outlines for visual separation
Total: Single bar colored by dominant direction
Delta: Net volume (buy minus sell)
Delta Intensity: Gradient coloring indicating buyer/seller dominance strength per row
Value Area
Configurable percentage (default 70%)
VAH and VAL lines with customizable styles
Separate colors for volume inside vs. outside the Value Area
Positioning Options
Left or Right placement
Adjustable profile width as percentage of visible range
Row configuration via "Number of Rows" or "Ticks Per Row"
Additional Features
Statistics table showing bars analyzed, total volume, up/down percentages, price vs POC
POC price labels on chart
Line style options (Solid, Dashed, Dotted)
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How It Works
Volume from each bar is distributed across price rows based on the bar's high-low range. The allocation is proportional - if a bar spans 3 rows with 60% overlap on one row, that row receives 60% of the bar's volume.
Volume Nodes Mode identifies local peaks in the distribution (rows where volume exceeds both neighbors), then selects the highest peaks while enforcing minimum separation. This surfaces distinct support/resistance clusters rather than stacking all POC lines in a single high-volume area.
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Settings
Inputs
Setting - Description
Rows Layout - "Number of Rows" or "Ticks Per Row"
Row Size - Number of rows (24-200) or ticks per row
Volume - "Up/Down", "Total", "Delta", or source selection
Value Area % - Percentage of volume for Value Area (default 70%)
Profile Width % - Width as percentage of visible bars
Placement - "Right" or "Left" side of chart
Enhancements
Setting - Description
Number of POCs | 1-8 POC lines |
POC Mode - "Volume Nodes" (peak detection) or "Highest Rows" (traditional)
Min Node Separation - Minimum rows between nodes (0 = auto-calculate)
Delta Intensity Mode - Gradient coloring by dominance
Show Stats Table - Display analysis statistics
Style
Setting - Description
Up/Down Volume Colors - Buy/sell volume colors
Value Area Colors - Colors for VA regions
POC/VAH/VAL Colors - Line colors and styles
POC 2-8 Colors - Colors for additional POC levels
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Applications
Support/Resistance Identification
High-volume nodes tend to act as price magnets. Multiple POCs reveal layered S/R zones that aren't visible with a single POC.
Fair Value Reference
The Value Area represents where 70% of volume traded. Price tends to revert to this zone.
Volume Gap Analysis
Low-volume areas between POCs indicate prices that were rejected quickly - potential breakout or breakdown levels.
Market Structure
Multiple POCs across price levels show where the market has found acceptance, useful for distinguishing range-bound conditions from trending moves.
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Practical Notes
Volume Nodes mode with 3-5 POCs works well for identifying distinct S/R clusters
Higher row counts give more granular analysis on lower timeframes
Delta Intensity mode quickly shows buyer/seller dominance at each level without the visual noise of split bars
If POCs are too clustered, increase Min Node Separation; if too spread out, decrease it or set to 0 for auto
The stats table vs POC comparison is useful for quick directional bias assessment
+++++
Requirements
Any instrument with volume data
Works well on futures, forex, and liquid equities
Pine Script v6
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Version History
v1.1
- Added Volume Nodes mode with peak detection
- Expanded to 8 POC levels
- Added Min Node Separation setting
- Fixed POC label positioning for left placement
- Added black outlines to Up/Down volume bars
v1.0
- Initial release replicating VRVP with multi-POC enhancement
- Delta Intensity mode
- Statistics table
Liquidity Trap Detector Pro [PyraTime]The Problem: Why You Get Stopped Out
90% of retail traders place their stop-losses at obvious swing highs and lows. Institutional algorithms ("Smart Money") are programmed to push price through these levels to trigger liquidity, fill their heavy orders, and then immediately reverse the market.
If you have ever had your stop hit right before the market moves exactly where you predicted—you were the victim of a Liquidity Trap.
The Solution: Visualizing the "Stop Hunt"
Liquidity Trap Detector Pro is not just a support/resistance indicator. It is a comprehensive Reversal Scoring Engine.
Unlike standard indicators that spam signals on every wick, this tool uses a proprietary 5-Star Scoring System to analyze the quality of the trap. It validates every signal using Wick Symmetry, RSI Divergence, and Volume Analysis to separate a true reversal from a trend continuation.
Key Features (USP)
- 5-Star Scoring Engine: Every signal is rated from 1 to 5 stars. Stop guessing if a signal is valid; let the algorithm check the confluence for you.
- Glassmorphism Visuals: Gone are the messy lines. We use modern, semi-transparent "Liquidity Zones" that keep your chart clean and professional.
- Smart Terminology: Automatically identifies Bull Traps (Buyers trapped at highs) and Bear Traps (Sellers trapped at lows).
- Heads-Up Display (HUD): A professional dashboard monitors the market state, active filters, and recent trap statistics in real-time.
- Strict Non-Repainting: (Technical Note) This script uses strict non-repainting logic. All Higher Timeframe (HTF) data is confirmed and closed before a signal is generated, ensuring historical accuracy.
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Tutorial: How to Trade This Indicator
1. Understanding the Signals
We use correct institutional terminology to describe the market mechanics:
GREEN Signal (BEAR TRAP):
- What happened: Price swept a Swing Low, enticing sellers (Bears) to enter. The candle then reversed and closed back inside the range, trapping those sellers.
- The Trade: This is a Bullish Reversal setup (Long).
RED Signal (BULL TRAP):
- What happened: Price swept a Swing High, enticing buyers (Bulls) to breakout. The candle reversed and closed lower, trapping the buyers.
- The Trade: This is a Bearish Reversal setup (Short).
2. The 5-Star Scoring System
Not all traps are created equal. The stars tell you how much "Confluence" exists:
- 1 Star: A basic structure sweep. Risky.
- 3 Stars: A solid setup backed by either Volume or Divergence.
- 5 Stars: The "Perfect" Trap. Structure Sweep + RSI Divergence + Volume Spike + Wick Symmetry. High Probability.
3. The Strategy
- Wait for the Zone: Watch price approach a coloured Liquidity Zone.
- Observe the Reaction: Do not trade blindly. Wait for the candle to close.
- Check the Stars: Look for at least 3 Stars before considering an entry.
- Confirm with HUD: Glance at the Dashboard to ensure the "RSI Filter" and "Vol Filter" agree with your analysis.
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Settings Guide
Structure Settings:
- Pivot Lookback: Adjusts how sensitive the zones are (Default: 10/5).
- HTF Confirmation: Optional filter to only show traps that align with Higher Timeframe structure (e.g., 1H or 4H).
Quality Filters:
- RSI Divergence: Requires momentum to disagree with price (classic reversal sign).
- Volume Spike: Requires volume to be higher than average (Smart Money footprint).
Visuals:
- Clean Mode: A presenter-favorite feature. Hides all historical zones and leaves only the active setup—perfect for taking screenshots or sharing analysis.
Disclaimer
This tool is designed to assist with technical analysis and identifying potential areas of interest. It does not guarantee profits. Trading involves significant risk; always use proper risk management.
Auto-Anchored Fibonacci Volume Profile [Custom Array Engine]Description:
1. The Theoretical Foundation: Structure vs. Participation In professional technical analysis, traders often struggle to reconcile two distinct datasets: Price Geometry (where price should go) and Market Participation (where money actually went).
Why Fibonacci? (The Structure) Fibonacci Retracements map the mathematical structure of a trend. They identify psychological and algorithmic "interest zones" (0.382, 0.5, 0.618) where a correction is statistically likely to terminate. However, Fibonacci levels are theoretical—they are "lines in the sand" that do not guarantee liquidity or reaction.
Why Volume Profile? (The Verification) Volume Profile maps the historical exchange of shares at specific price levels. It reveals "fair value" (High Volume Nodes) and "market imbalance" (Low Volume Nodes). It is the only tool that verifies if a specific price level was actually accepted by institutional participants.
2. Underlying Calculations (The Custom Engine) This script operates on a custom-built calculation engine that bypasses standard built-in functions entirely. It uses Pine Script Arrays to build a Volume Profile from scratch. Here is the breakdown of the proprietary code logic:
A. The "Smart-Fill" Distribution Algorithm (Solves Gapping)
The Problem: Standard volume scripts often assign a candle's entire volume to a single price row. In volatile markets or steep trends, this creates visual "gaps" or a "barcode" effect because price moved too fast to register on every row.
My Solution: I wrote a custom loop that calculates the vertical overlap of every candle against the profile grid.
The Math: Volume Per Bin = Total Candle Volume / Bins Touched.
The Result: If a single volatile candle spans 10 price rows (bins), the script mathematically divides that volume and distributes it equally into all 10 array indices. This generates a solid, continuous distribution curve that accurately reflects price action through the entire candle range, not just the close.
B. Dynamic Arrays & Split-Volume Logic The script initializes two separate floating-point arrays (buyVolArray and sellVolArray) sized to the user's resolution (up to 300 rows). It iterates through the specific time-window of the swing:
If Close >= Open, the calculated volume slice is injected into the Buy Array.
If Close < Open, it is injected into the Sell Array.
These arrays are then visually stacked to render the dual-color profile, allowing traders to see the "Delta" (Buyer vs. Seller aggression) at key structural levels.
C. Custom Garbage Collection (Performance) To enable the "Auto-Anchoring" feature without causing chart lag or visual artifacts ("ghosting"), the script includes a Garbage Collection System. Before drawing a new profile, the script iterates through a tracking array of all existing objects (box.delete, line.delete) and clears them from memory. This ensures the indicator remains lightweight and responsive even when dragging chart margins or switching timeframes.
3. The Synthesis: Why Combine Them? The core philosophy of this script is Confluence . A Fibonacci level without volume is merely a suggestion; a Fibonacci level backed by volume is a defensive wall. By algorithmically anchoring a Volume Profile to the exact coordinates of a Fibonacci swing, this tool allows traders to instantly answer critical questions:
"Is the Golden Pocket (0.618) supported by a High Volume Node (HVN), or is it a Low Volume Node (LVN) that price might slice through?"
"Is the Shallow Retracement (0.382) holding because of structural support, or just a lack of selling pressure?"
4. How to Read the Indicator
The Geometry: The script automatically detects the trend and draws standard Fib levels (0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0).
The Confluence Check: Look for the Point of Control (Red Line). If this High Volume Node aligns with a key Fib level (e.g., the 0.618), the probability of a reversal increases significantly.
The Imbalance Check: Look for "Valleys" in the profile (Low Volume Nodes). These gaps often act as "slippage zones" where price travels quickly between structural levels.
Buy/Sell Splits: The dual-color bars (Teal/Red) reveal the composition of the volume. A 0.618 level held up by dominant Buy Volume is a stronger bullish signal than one with mixed volume.
5. Settings & Customization
Lookback Length: Sensitivity of the swing detection (Default: 200 bars).
Resolution: Granularity of the profile rows (Default: 100). Higher values provide smoother definition.
Width (%): Responsive sizing that scales the profile relative to the trend's duration.
Extend Lines: Option to project structural levels infinitely to the right.
Disclaimer This script is an analytical tool for visualizing historical market data. It does not provide trade signals or financial advice.
X-Trend Macro Command CenterX-Trend Macro Command Center (MCC) | Institutional Grade Dashboard
📝 Description Body
The Invisible Engine of the Market Revealed.
Traders often focus solely on Price Action, ignoring the massive underwater currents that actually drive trends: Global Liquidity, Inflation, and Central Bank Policy. We created X-Trend Macro Command Center (MCC) to solve this problem.
This is not just an indicator. It is a fundamental heads-up display that bridges the gap between technical charts and macroeconomic reality.
💡 The Idea & Philosophy
Markets don't move in a vacuum. Bull runs are fueled by M2 Money Supply expansion and negative real yields. Crashes are triggered by liquidity crunches and aggressive rate hikes. X-Trend MCC was built to give retail traders the same "Macro Awareness" that institutional desks possess. It aggregates fragmented economic data from Federal Reserve databases (FRED) directly onto your chart in real-time.
🚀 Application & Logic
This tool is designed for Trend Traders, Crypto Investors, and Macro Analysts.
Identify the Regime: Instantly see if the environment is "RISK ON" (High Liquidity, Low Real Rates) or "RISK OFF" (Monetary Tightening).
Validate the Trend: Don't buy the dip if Liquidity (M2) is crashing. Don't short the rally if Real Yields are negative.
Multi-Region Analysis: Switch instantly between economic powerhouses (US, China, Japan) to see where the capital is flowing.
📊 Dashboard Metrics Explained
Every row in the Command Center tells a specific story about the economy:
Interest Rate: The "Gravity" of finance. Higher rates weigh down risk assets (Stocks/Crypto).
Inflation (YoY): The erosion of purchasing power. We calculate this dynamically based on CPI data.
Real Yield (The "Golden" Metric): Calculated as Interest Rate - Inflation.
Green: Real Yield is low/negative. Cash is trash, assets fly.
Red: Real Yield is high. Cash is King, assets struggle.
US Debt & GDP: Fiscal health indicators formatted in Trillions ($T). Watch the Debt-to-GDP ratio—if it spikes >120%, expect currency debasement.
M2 Money Supply: The fuel tank of the market. Tracks the total amount of money in circulation.
↗ Trend: Liquidity is entering the system (Bullish).
↘ Trend: Liquidity is drying up (Bearish).
🧩 The X-Trend Ecosystem
X-Trend MCC is just the tip of the iceberg. This module is part of the larger X-Trend Project — a comprehensive suite of algorithmic tools being developed to quantify market chaos. While our Price Action algorithms (Lite/Pro/Ultra) handle the Micro, the MCC handles the Macro.
Technical Note:
Data Sources: Direct connection to FRED (Federal Reserve Economic Data).
Zero Repainting: Historical data is requested strictly using closed bars to ensure accuracy.
Open Source: We believe in transparency. The code is open for study under MPL 2.0.
Build by Dev0880 | X-Trend © 2025
