Price Displacement - Candlestick (OHLC) CalculationsA Magical little helper friend for Candle Math.
When composing scripts, it is often necessary to manipulate the math around the OHLC. At times, you want a scalar (absolute) value others you want a vector (+/-). Sometimes you want the open - close and sometimes you want just the positive number of the body size. You might want it in ticks or you might want it in points or you might want in percentages. And every time you try to put it together you waste precious time and brain power trying to think about how to properly structure what you're looking for. Not to mention it's normally not that aesthetically pleasing to look at in the code.
So, this fixes all of that.
Using this library. A function like 'pd.pt(_exp)' can call any kind of candlestick math you need. The function returns the candlestick math you define using particular expressions.
Candle Math Functions Include:
Points:
pt(_exp) Absolute Point Displacement. Point quantity of given size parameters according to _exp.
vpt(_exp) Vector Point Displacement. Point quantity of given size parameters according to _exp.
Ticks:
tick(_exp) Absolute Tick Displacement. Tick quantity of given size parameters according to _exp.
vtick(_exp) Vector Tick Displacement. Tick quantity of given size parameters according to _exp.
Percentages:
pct(_exp, _prec) Absolute Percent Displacement. (w/rounding overload). Percent quantity of bar range of given size parameters according to _exp.
vpct(_exp, _prec) Vector Percent Displacement (w/rounding overload). Percent quantity of bar range of given size parameters according to _exp.
Expressions You Can Use with Formulas:
The expressions are simple (simple strings that is) and I did my best to make them sensible, generally using just the ohlc abreviations. I also included uw, lw, bd, and rg for when you're just trying to pull a candle component out. That way you don't have to think about which of the ohlc you're trying to get just use pd.tick("uw") and now the variable is assigned the length of the upper wick, absolute value, in ticks. If you wanted the vector in pts its pd.vpt("uw"). It also makes changing things easy too as I write it out.
Expression List:
Combinations
"oh" = open - high
"ol" = open - low
"oc" = open - close
"ho" = high - open
"hl" = high - low
"hc" = high - close
"lo" = low - open
"lh" = low - high
"lc" = low - close
"co" = close - open
"ch" = close - high
"cl" = close - low
Candle Components
"uw" = Upper Wick
"bd" = Body
"lw" = Lower Wick
"rg" = Range
Pct() Only
"scp" = Scalar Close Position
"sop" = Scalar Open Position
"vcp" = Vector Close Position
"vop" = Vector Open Position
The attributes are going to be available in the pop up dialogue when you mouse over the function, so you don't really have to remember them. I tried to make that look as efficient as possible. You'll notice it follows the OHLC pattern. Thus, "oh" precedes "ho" (heyo) because "O" would be first in the OHLC. Its a way to help find the expression you're looking for quickly. Like looking through an alphabetized list for traders.
There is a copy/paste console friendly helper list in the script itself.
Additional Notes on the Pct() Only functions:
This is the original reason I started writing this. These concepts place a rating/value on the bar based on candle attributes in one number. These formulas put a open or close value in a percentile of the bar relative to another aspect of the bar.
Scalar - Non-directional. Absolute Value.
Scalar Position: The position of the price attribute relative to the scale of the bar range (high - low)
Example: high = 100. low = 0. close = 25.
(A) Measure price distance C-L. How high above the low did the candle close (e.g. close - low = 25)
(B) Divide by bar range (high - low). 25 / (100 - 0) = .25
Explaination: The candle closed at the 25th percentile of the bar range given the bar range low = 0 and bar range high = 100.
Formula: scp = (close - low) / (high - low)
Vector = Directional.
Vector Position: The position of the price attribute relative to the scale of the bar midpoint (Vector Position at hl2 = 0)
Example: high = 100. low = 0. close = 25.
(A) Measure Price distance C-L: How high above the low did the candle close (e.g. close - low = 25)
(B) Measure Price distance H-C: How far below the high did the candle close (e.g. high - close = 75)
(C) Take Difference: A - B = C = -50
(D) Divide by bar range (high - low). -50 / (100 - 0) = -0.50
Explaination: Candle close at the midpoint between hl2 and the low.
Formula: vcp = { / (high - low) }
Thank you for checking this out. I hope no one else has already done this (because it took half the day) and I hope you find value in it. Be well. Trade well.
Library "PD"
Price Displacement
pt(_exp) Absolute Point Displacement. Point quantity of given size parameters according to _exp.
Parameters:
_exp : (string) Price Parameter
Returns: Point size of given expression as an absolute value.
vpt(_exp) Vector Point Displacement. Point quantity of given size parameters according to _exp.
Parameters:
_exp : (string) Price Parameter
Returns: Point size of given expression as a vector.
tick(_exp) Absolute Tick Displacement. Tick quantity of given size parameters according to _exp.
Parameters:
_exp : (string) Price Parameter
Returns: Tick size of given expression as an absolute value.
vtick(_exp) Vector Tick Displacement. Tick quantity of given size parameters according to _exp.
Parameters:
_exp : (string) Price Parameter
Returns: Tick size of given expression as a vector.
pct(_exp, _prec) Absolute Percent Displacement (w/rounding overload). Percent quantity of bar range of given size parameters according to _exp.
Parameters:
_exp : (string) Expression
_prec : (int) Overload - Place value precision definition
Returns: Percent size of given expression as decimal.
vpct(_exp, _prec) Vector Percent Displacement (w/rounding overload). Percent quantity of bar range of given size parameters according to _exp.
Parameters:
_exp : (string) Expression
_prec : (int) Overload - Place value precision definition
Returns: Percent size of given expression as decimal.
"bar" için komut dosyalarını ara
ConditionalAverages█ OVERVIEW
This library is a Pine Script™ programmer’s tool containing functions that average values selectively.
█ CONCEPTS
Averaging can be useful to smooth out unstable readings in the data set, provide a benchmark to see the underlying trend of the data, or to provide a general expectancy of values in establishing a central tendency. Conventional averaging techniques tend to apply indiscriminately to all values in a fixed window, but it can sometimes be useful to average values only when a specific condition is met. As conditional averaging works on specific elements of a dataset, it can help us derive more context-specific conclusions. This library offers a collection of averaging methods that not only accomplish these tasks, but also exploit the efficiencies of the Pine Script™ runtime by foregoing unnecessary and resource-intensive for loops.
█ NOTES
To Loop or Not to Loop
Though for and while loops are essential programming tools, they are often unnecessary in Pine Script™. This is because the Pine Script™ runtime already runs your scripts in a loop where it executes your code on each bar of the dataset. Pine Script™ programmers who understand how their code executes on charts can use this to their advantage by designing loop-less code that will run orders of magnitude faster than functionally identical code using loops. Most of this library's function illustrate how you can achieve loop-less code to process past values. See the User Manual page on loops for more information. If you are looking for ways to measure execution time for you scripts, have a look at our LibraryStopwatch library .
Our `avgForTimeWhen()` and `totalForTimeWhen()` are exceptions in the library, as they use a while structure. Only a few iterations of the loop are executed on each bar, however, as its only job is to remove the few elements in the array that are outside the moving window defined by a time boundary.
Cumulating and Summing Conditionally
The ta.cum() or math.sum() built-in functions can be used with ternaries that select only certain values. In our `avgWhen(src, cond)` function, for example, we use this technique to cumulate only the occurrences of `src` when `cond` is true:
float cumTotal = ta.cum(cond ? src : 0) We then use:
float cumCount = ta.cum(cond ? 1 : 0) to calculate the number of occurrences where `cond` is true, which corresponds to the quantity of values cumulated in `cumTotal`.
Building Custom Series With Arrays
The advent of arrays in Pine has enabled us to build our custom data series. Many of this library's functions use arrays for this purpose, saving newer values that come in when a condition is met, and discarding the older ones, implementing a queue .
`avgForTimeWhen()` and `totalForTimeWhen()`
These two functions warrant a few explanations. They operate on a number of values included in a moving window defined by a timeframe expressed in milliseconds. We use a 1D timeframe in our example code. The number of bars included in the moving window is unknown to the programmer, who only specifies the period of time defining the moving window. You can thus use `avgForTimeWhen()` to calculate a rolling moving average for the last 24 hours, for example, that will work whether the chart is using a 1min or 1H timeframe. A 24-hour moving window will typically contain many more values on a 1min chart that on a 1H chart, but their calculated average will be very close.
Problems will arise on non-24x7 markets when large time gaps occur between chart bars, as will be the case across holidays or trading sessions. For example, if you were using a 24H timeframe and there is a two-day gap between two bars, then no chart bars would fit in the moving window after the gap. The `minBars` parameter mitigates this by guaranteeing that a minimum number of bars are always included in the calculation, even if including those bars requires reaching outside the prescribed timeframe. We use a minimum value of 10 bars in the example code.
Using var in Constant Declarations
In the past, we have been using var when initializing so-called constants in our scripts, which as per the Style Guide 's recommendations, we identify using UPPER_SNAKE_CASE. It turns out that var variables incur slightly superior maintenance overhead in the Pine Script™ runtime, when compared to variables initialized on each bar. We thus no longer use var to declare our "int/float/bool" constants, but still use it when an initialization on each bar would require too much time, such as when initializing a string or with a heavy function call.
Look first. Then leap.
█ FUNCTIONS
avgWhen(src, cond)
Gathers values of the source when a condition is true and averages them over the total number of occurrences of the condition.
Parameters:
src : (series int/float) The source of the values to be averaged.
cond : (series bool) The condition determining when a value will be included in the set of values to be averaged.
Returns: (float) A cumulative average of values when a condition is met.
avgWhenLast(src, cond, cnt)
Gathers values of the source when a condition is true and averages them over a defined number of occurrences of the condition.
Parameters:
src : (series int/float) The source of the values to be averaged.
cond : (series bool) The condition determining when a value will be included in the set of values to be averaged.
cnt : (simple int) The quantity of last occurrences of the condition for which to average values.
Returns: (float) The average of `src` for the last `x` occurrences where `cond` is true.
avgWhenInLast(src, cond, cnt)
Gathers values of the source when a condition is true and averages them over the total number of occurrences during a defined number of bars back.
Parameters:
src : (series int/float) The source of the values to be averaged.
cond : (series bool) The condition determining when a value will be included in the set of values to be averaged.
cnt : (simple int) The quantity of bars back to evaluate.
Returns: (float) The average of `src` in last `cnt` bars, but only when `cond` is true.
avgSince(src, cond)
Averages values of the source since a condition was true.
Parameters:
src : (series int/float) The source of the values to be averaged.
cond : (series bool) The condition determining when the average is reset.
Returns: (float) The average of `src` since `cond` was true.
avgForTimeWhen(src, ms, cond, minBars)
Averages values of `src` when `cond` is true, over a moving window of length `ms` milliseconds.
Parameters:
src : (series int/float) The source of the values to be averaged.
ms : (simple int) The time duration in milliseconds defining the size of the moving window.
cond : (series bool) The condition determining which values are included. Optional.
minBars : (simple int) The minimum number of values to keep in the moving window. Optional.
Returns: (float) The average of `src` when `cond` is true in the moving window.
totalForTimeWhen(src, ms, cond, minBars)
Sums values of `src` when `cond` is true, over a moving window of length `ms` milliseconds.
Parameters:
src : (series int/float) The source of the values to be summed.
ms : (simple int) The time duration in milliseconds defining the size of the moving window.
cond : (series bool) The condition determining which values are included. Optional.
minBars : (simple int) The minimum number of values to keep in the moving window. Optional.
Returns: (float) The sum of `src` when `cond` is true in the moving window.
Overnight Gap AnalysisThere is a wide range of opinion on holding positions overnight due to gap risk. So, out of curiosity, I coded this analysis as a strategy to see what the result of only holding a position overnight on an asset would be. The results really surprised me. The script backtests 10+ years, and here are the findings:
Holding a position for 1 hour bar overnight on QQQ since January 2010 results in a 545% return. QQQ's entire return holding through the same period is 643%
The max equity drawdown on holding that position overnight is lower then the buy/hold drawdown on the underlying asset.
It doesn't matter if the last bar of the day is green or red, the results are similar.
It doesn't matter if it is a bull or bear market. Filtering the script to only trade when the price is above the 200-day moving average actually reduces its return from 545% to 301%, though it does also reduce drawdown.
I see similar patterns when applying the script to other index ETFs. Applying it to leveraged index ETFs can end up beating buy/hold of the underlying index.
Since this script holds through the 1st bar of the day, this could also speak to a day-opening price pattern
The default inputs are for the script to be applied to 1 hour charts only that have 7 bars on the chart per day. You can apply it to other chart types, but must follow the instructions below for it to work properly.
What the script is doing :
This script is buying the close of the last bar of the day and closing the trade at the close of the next bar. So, all trades are being held for 1 bar. By default, the script is setup for use on a 1hr chart that has 7 bars per day. If you try to apply it to a different timeframe, you will need to adjust the count of the last bar of the day with the script input. I.e. There are 7 bars per day on an hour chart on US Stocks/ETFs, so the input is set to 7 by default.
Other ways this script can be used :
This script can also test the result of holding a position over any 1 bar in the day using that same input. For instance, on an hour chart you can input 6 on the script input, and it will model buying the close of the 6th bar of the day while selling on the close of the next bar. I used this out of curiosity to model what only holding the last bar of the day would result in. On average, you lose money on the last bar every day.
The irony here is that the root cause of this last bar of the day losing may be people selling their positions at the end of day so that they aren't exposed to overnight gap risk.
Disclaimer: This is not financial advice. Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Bjorgum SuperScript
Bjorgum Reversal
Bj Reversal uses Tilson moving averages to identify trend changes
Bars change to yellow as bar close crosses the Tilson moving averages. Blue or red is confirmed as the two Tilson averages themselves cross.
Reversal is great for pinpointing trend change often giving the absolute best entry or exit
Its sensitive nature can mean more false signals on some assets
Be sure to use other indicators from the Bjorgum Collection to confirm signals, or use another strategy that fits the asset or time frame being viewed
Bjorgum HEMA Strategy
Hema uses HA smoothed EMAs to identify trend direction
Default EMA lengths are 5,9, and 21 period
Bar Color will change Malibu or Ruby on a cross of BOTH 5 and 9 EMA
The lengths are customizable to whatever lengths the user desires
Rolando Santos True Relative Movement (TRM)
This underrated momentum strategy conceptualized by Rolando Santos uses 2 indicators to give a 3 color scheme
A leading indicator (RSI) is combined with a lagging indicator (TSI) to produce bar colors based on the condition of each indicator
Both indicators in positive territory produce blue bars
Both indicators in negative bias produce yellow bars
If signals are mixed (one up one down) bars become grey
Speed Selection
The Bjorgum speed selector optimizes the strategy based on the users desires or trading style at the touch of a button
Fast setting is better for swing trades - more timely signals, more whipsaw
Slow setting is better for longer holds or more volatile assets - slower signals, smooths out whipsaw
RSI Bar Color
RSI color changes bar color based on user defined RSI values
Buy/ sell signals are typically given on a cross of the 50 level
Speed selector (fast/Slow) automatically changes lengths between Bj RSI (5 period) and a standard RSI (14 period)
Additional capabilities can be mixed and matched from strategies in the "Strategy Override" section
Add-ons include:
Tilson - The moving average system from Bjorgum Reversal can be toggled to couple with another bar color strategy by clicking this button
PSAR - Parabolic Stop and Reverse indicator can help with trend direction, volatility, and stop losses
HEMA - The 3 moving average system from the HEMA strategy can be coupled with any of the other strategies by clicking "Show HEMA"
Bj Arrows - These arrows plot at the bar level to draw attention to when the BJ TSI is "curling" (See profile for Bjorgum TSI and download today)
-Optional "Plotbar Overlay" plots bars with Heikin-Ashi Inputs when toggled
-This allows for the benefits of price smoothing without sacrificing moving average and indicator performance as real close value is still used
-This can also help on short time frames and improve results with crypto! The user must "mute" the main series candles when in use to avoid candle overlap.
-Optional price line as muting main bars will disable the TradingView default price line. The horizontal plot will track the real closing price while in HA mode!
Historic VPoCs and pseudo VPVRThis study tries to recreate session based historic VPoCs
and VPVR Volume Profile
as they are used by
TradingLatino TradingView user.
It's aimed at BTCUSDT pair and 4h timeframe.
HOW IT WORKS
HOW IT WORKS - VPVR Profile Block
It gathers volume from the last chosen Bars
in order to draw the vpvr profile block
Volume that intersects with current level range
being studied is added to its value.
Additionally the current level price is modified
so that it matches the level price where most
of the volume has concentrated
So you get a pretty accurate price for drawn volume
while at the same time the levels are not stuck
to arbitrary level prices.
HOW IT WORKS - VPoC
It calculates a Volume Profile for the
given historic session but then
it only outputs that Volume Profile VPoC.
SETTINGS
Show VPVR Volume Profile {True}.
Show Historic VPoC lines {True}.
Show Historic VPoC labels {True}.
Extend Historic VPoC lines {True}: If this option is turned off the VPoC lines are only shown during the session duration.
Show tick difference from current price {False}: BETA. Feedback is needed because I'm not sure how it should work this setting.
VPVR Number of bars {100}: Define the Visible Range in number of bars so that its Volume Profile can be shown.
VPVR Profile width (in bars) {15}: VPVR Profile can be make larger or smaller in width thanks to this option.
VPVR Profile offset (in bars) {15}: VPVR Profile can be shown more to the left or to the right if the defaults do not suit you.
Historic Session Volume Profile timeframe {1D}: Historic VPoC use 1 day as their timeframe reference by default.
Number of decimal digits {2}: How many decimal digits are shown in label prices.
Number of previous sessions to print VPoC {5}: How many previous sessions VPoCs are to be printed. The maximum for this setting is 20.
Historic VPoC lines width (in pixels) {2}.
Historic VPoC labels size {small}.
History VPoC line offset (in bars) {5}: How far to the right VPoCs lines are to be extended. Note: This setting does not apply when 'Extend Historic VPoC lines' is set to 'False'.
WARNING
Please be aware that VPoC from the first previous session might not be accurate due to Pine Script limitations.
VPVR USAGE
This is not a VPVR like the official TradingView indicator.
This is a pseudo VPVR and that means it needs some manual input from you.
But, don't worry it's quite easy to do and if you always use the same number
of bars to calculate your VPVR then you might even just set it up once.
In order to show the VPVR (or Volume Profile on the Visible Range):
Rescale your chart so that you see all the bars for your Visible Range.
Click on the ruler tool.
Click on the last bar (far to the right) shown on the screen
Drag the ruler to first bar (far to the left) shown on the screen
Check what the ruler says
E.g. it says: 101 bars
Open this study settings
Modify: 'VPVR Number of bars ' setting
So that its value matches your measured number of bars (101)
Press OK to confirm and wait for the indicator to refresh.
STRATEGY USAGE
If your strategy uses VPoC
to define your resistances
or supports
you can check the VPoCs shown here.
FEEDBACK
I have only used this identifier in BTCUSDT 4h timeframe.
I'm interested to know what needs to be tweaked
in other securities and timeframes.
PINE STUDY TRICK
This study let's you choose the number of decimals the label will use.
CREDITS
I have reused and adapted some code from
'Poor man's volume profile' study
which it's from TradingView IldarAkhmetgaleev user.
I also wanted to thank him for helping me understanding his study.
I have reused some code from
'MTF Selection Framework - PineCoders FAQ' study
which it's from TradingView PineCoders user.
Ultimate VolumeThis script can display a lot of different volume statistics. It also colours bars depending on a chosen, customisable criterion. Most options are disabled by default and can be reenabled in the settings menu.
FAQ
Why are the bars slightly higher than the default volume bars?
Due to the limitations of Pinescript.
What are the two last values (including the one in white?)
They're there due to the limitations of Pinescript. It used to be possible to prevent certain values from being plotted, but still display them as indicator values, but the functionality of that option was changed and is now WIP so until it's restored, these values are necessary to scale the bars properly.
Why are the percentages formatted as volume?
Due to the limitations of Pinescript.
Why are there so many options?
I don't know. They sort of happened. But you don't have to switch them on.
What is money volume?
It's an average of the bar price multiplied by the bar volume .
Why does the daily average volume display different values than the standard sma volume?
Because mine doesn't take into account the current day. So it doesn't fluctuate intraday. Which, I think, makes more sense.
What is total volume?
It's a sum of the total volume for that day and is reset on the next. This option only works with intraday timeframes.
What is average 1 bar intraday volume?
It's the average volume for 1 intraday bar, based on the current day's values only. Obviously, it only works intraday and changes dynamically. It's not an SMA , it's a simple average of all bars for a given day.
What is all-time 1 bar intraday volume?
It's the average volume for 1 intraday bar, but based on the whole chart's history. It's impossible to select a length for this, again, because of certain limitations.
What is short volume?
It is approximately 1/3rd of the actual short volume , due to the limitations of FINRA. It's multiplied by 3 in the script and it may be not entirely accurate. The short volume % is calculated differently, using the 1/3rd of short and total volume from FINRA.
What are the default threshold values?
They are 150%, 200%, 1000% of the average for the average bar volume and all-time average bar volume options, 10%, 50%, 100% for the average daily volume option and 100K, 500K and 1M for the volume option.
RedK_Supply/Demand Volume Viewer v1Background
============
VolumeViewer is a volume indicator, that offers a simple way to estimate the movement and balance (or lack of) of supply & demand volume based on the shape of the price bar. i put this together few years ago and i have a version of this published for another platform under different names (Directional Volume, BetterVolume) in case you come across them
what is V.Viewer
=====================
The idea here is to find a "simple proxy" for estimating the demand or supply portions of a volume bar - these 2 forces have the potential to affect the current price trend so we want an easy way to track them - or to understand if a stock is in accumulation or distribution - we want to do this without having access to Level II or bid/ask data, and without having to get into the complexity of exploring the lower timeframe price & volume data
- to achieve that, we depend on a simple assumption, that the volume associated with an up move is "demand" and the volume associated with a down move is "Supply". so we basically extrapolate these supply and demand values based on how the bar looks like - a full "green" price bar / candle will be considered 100% demand, and a full "red" price bar will be considered 100% supply - a bar that opens and closes at the same level will be 50/50 split between supply & demand.
- you may say this is a "too simple" of an assumption to make, but believe me, it works :) at least at the basic scenario we need here: i'm just exploring the volume movement and finding key levels - and it provides a good improvement compared to the classic way we see volume on a chart - which is still available here in VolumeViewer.
in all cases, i consider this to be work in progress, so i'd welcome any ideas to improve (without getting too complicated) - there's already a host of great volume-based indicators that will do the multi timeframe drill down, but that's not my scope here.
Technical Jargon & calculation
===========================
1. first we calculate a score % for the volume portion that is considered demand based on the bar shape
skip this part if it sounds too technical => if you're into coding indicators, you would probably know there are couple of different concepts for that algorithm - for example, the one used in Balance Of Power formula - which i'm a big fan of - but the one i use here is different. (how?) this is my own, ant it simply applies double weight for the "wick" parts of a price bar compared to the "body of the bar" -- i did some side-by-side comparison in past and decided this one works better. you can change it in the code if you like
2. after calculating the Bull vs Bears portion of volume, we take a moving average of both for the length you set, to come up with what we consider to be the Demand vs Supply - as usual, i use a weighted moving average (WMA) here.
3. the balance or net volume between these 2 lines is calculated, then we apply a final smoothing and that's the main plot we will get
4. being a very visual person, i did my best to build up the visuals in the correct order - then also to ensure the "study title" bar is properly organized and is simple and useful (Full Volume, Supply, Demand, Net Volume).
- i wish there was a way in Pine to hide a value that i still need to visually plot but don't want it showing its value on the study title bar, but couldn't find it. so the last plot value is repeated twice.
How to use
===========
- V.Viewer is set up to show the simplified view by default for simplicity. so when you first add it to a chart, you will get only the supply vs demand view you can see in the middle pane in the above chart
- Optional / detailed mode: go into the settings, and expose all other plots, you will be able to add the classic volume histogram, and the Supply / Demand lines - note these 2 lines will be overlay-ed on top of each other - this provides an easy way to see who is in control - especially if you change the display of these 2 lines into "area" style. This is what is showing in the lower pane in the above chart.
** Exploring Key Price Levels
- the premise is, at spots where there's big lack of balance, that's where to expect to find key price levels (support / resistance) and these price levels will come into play in future so can be used to set entry / exit targets for our trades - see the example in the AAPL chart where you can easily locate these "balance or reversal levels" using the tops/bottoms/zero-crossings from the Net Volume line
** Use for longer-term Price Analysis
- we can also use this simple indicator to gain more insights (at a high level) of the price in terms of accumulation vs distribution and if the sellers or buyers are in control - for example, in the above AAPL chart, V.Viewer tells us that buyers have been in control since October 19 - even during the recent drop, demand continued to be in play - compare that to DIS chart below for the same period, where it shows that the market was dumping DIS thru the weakness. DIS was bleeding red most of the time
Final thoughts
=============
- V.Viewer is an attempt to enhance the way we see and use Volume by leveraging the shape of the price bar to estimate volume supply & demand - and the Net between the 2
- it will work for stocks and other instruments as long as there's volume data
- note that V.Viewer does not track trend. each bar is taken in isolation of prior bars - the price may be going down and V.Viewer is showing supply going up (absorption scenario?) - so i suggest you do not use it to make decisions without consulting other trend / momentum indicators - of course this is a possible improvement idea, or can be implemented in another indicator, add in trend somehow, or maybe think of making this a +100 / -100 Oscillator .. feel free to play with these thoughts
- all thoughts welcome - if this is useful to you in your trading, please share with other trades here to learn from each other
- the code is commented - please feel free to use it as you like, or build things on top of it - but please continue to credit the author of this code :)
good luck!
-
Pivots MTF [LucF]Pivots detected at higher timeframes are more significant because more market activity—or work—is required to produce them. This indicator displays pivots calculated on the higher timeframe of your choice.
Features
► Timeframe selection
— The higher timeframe (HTF) can be selected in 3 different ways:
• By steps (15 min., 60 min., 4H, 1D, 3D, 1W, 1M, 1Y). This setting is the default.
• As a multiple of the current chart's resolution, which can be fractional, so 3.5 will work.
• Fixed.
— The HTF used can be displayed near the last bar (default).
— Note that using the HTF is not mandatory. If it is disabled, the indicator will calculate on the chart's resolution.
— Non-repainting or repainting mode can be selected. This has no impact on the display of historical bars, but when no repainting is selected, pivot detection in the realtime bar will be delayed by one chart bar (not one bar at the HTF).
► Pivots
— Three color schemes are provided: green/red, aqua/pink and coral/violet (the default).
— Both the thickness and brightness of lines can be controlled separately for the hi and lo pivots.
— The visibility of the last hi/lo pivots can be enhanced.
— Prices can be displayed on pivot lines and the text's size and color can be adjusted.
— The number of bars required for the left/right pivot legs can be controlled (the default is 4).
— The source can be selected individually for hi and lo pivots (the default is hlc3 and low .
— The mean of the hi/lo pivot values of the last few thousand chart bars can be displayed. Pivots having lasted longer during the mean's period will weigh more in the calculation. The mean can be displayed in running mode and/or only showing its last level as a long horizontal line. I don't find it very useful; maybe others will.
► Markers and Alerts
— Markers can be configured on breaches of either the last hi/lo pivot levels, or the hi/lo mean. Crossovers and crossunders are controlled separately.
— Alerts can be configured using any of the marker combinations. As is usual for my indicators, only one alert is used. It will trigger on the markers that are active when you create your alert. Once your markers are set up the way you want, create your alert from the chart/timeframe you want the alert to run on, and be sure to use the “Once Per Bar Close” triggering condition. Use an alert message that will remind you of the combination of markers used when creating the alert. If you use multiple markers to trigger one alert, then having the indicator show those markers will be important to help you figure out which marker triggered the alert when it fired.
A quick look at the pattern of these markers will hopefully convince you that using them as entry/exit signals would be perilous, as they are prone to whipsaw. I have included them because some traders may use the markers as reminders.
Using Pivots
These pivots can be used in a few different ways:
— When using the high / low sources they will show extreme levels, breaches of which should be more significant.
— Another way to use them is with hlc3 (the average of the high , low and close ) for hi pivots and low for the lo pivots. This accounts for my personal mythology to the effect that drops typically reach previous lows more easily than rallies make newer highs.
— Using low for hi pivots and high for lo pivots (so backward) can be a useful way to set stops or to detect weakness in movements.
You will usually be better served by pivots if you consider them as denoting regions rather than precise levels. The flexibility in the display options of this indicator will help you adapt it to the way you use your pivots. To indicate areas rather than levels, for example, try using a brightness of 1 with a line thickness of 30. The cloud effect generated this way will show areas better than fine lines.
Realize that these pivot lines are positioned in the past, and so they are drawn after the fact because a given number of bars need to elapse before calculations determine a pivot has occurred. You will thus never see a pivot top, for example, identified on the realtime bar. To detect a pivot, it takes a number of bars corresponding to the dilation of the higher timeframe in the current one, multiplied by the number of bars you use for your pivots' right leg. Also note that the Pine native function used to detect pivots in this indicator considers a summit to be a top when the number of bars in each leg are lower or equal to that top. Bars in legs do not need to be progressively lower on each side of the pivot for a pivot to be detected.
If you program in Pine
— See the Pinecoders MTF Selection Framework for an explanation of the functions used in this script to provide the selection mechanism for the higher timeframe.
— This code uses the Pine Script Coding Conventions .
Thanks
— To the Pine coders asking questions in the Pine Script chat on TV ; your questions got me to write this indicator.
Leledc Exhaustion V4This is one of my fav script (Leledec Exhaustion). The original script was written in V2 by Glaz here
All I did is to convert this to Version 4 of Pine Scripting language.
An Exhaustion Bar is a bar which signals the exhaustion of the trend in the current direction. In other words, an exhaustion bar is “A bar of the last seller” in case of a downtrend and “A bar of
last buyer” in case of an uptrend.
Having said that when a party cannot take the price further in their direction, naturally the other party comes in, takes charge and reverses the direction of the trend.
The Psychology
Let's assume that we have a group of people, say 100 people who decide to go for a casual running. After running for a few KM's few of them will say “I am exhausted. I cannot run further”. They will quit running. After running further, another bunch of runners will say “I am exhausted. I can’t run further” and they also will quit running. This goes on and on and then there will be a stage where only a few will be left in the running. Now a stage will come where the last person left in the running will say “ am exhausted” and he stops running. That means no one is left now in the
running. This means all are exhausted in the running.
The same way an exhaustion bar works. The reason is an exhaustion bar sometimes formed at almost tops and bottoms.
Timeframe
The exhaustion bars are found on all Time frames as a trend also exists on all Timeframes. However, as a thumb rule “Higher the Time frame, higher will be the accuracy as well as the profitability”.
Trading the Leledec Exhaustion Bars
I may trade as soon as it is shown on the chart.
I may trade when price breaks the high/low of the bar depending on whether I am getting bullish or bearish signal
I may trade when price breaks the high/low of the bar depending on whether I am getting bullish or bearish signal. I may also be looking to ensure the current volume is higher than the previous few
(? how many?) bar volumes.
Backtesting & Trading Engine [PineCoders]The PineCoders Backtesting and Trading Engine is a sophisticated framework with hybrid code that can run as a study to generate alerts for automated or discretionary trading while simultaneously providing backtest results. It can also easily be converted to a TradingView strategy in order to run TV backtesting. The Engine comes with many built-in strats for entries, filters, stops and exits, but you can also add you own.
If, like any self-respecting strategy modeler should, you spend a reasonable amount of time constantly researching new strategies and tinkering, our hope is that the Engine will become your inseparable go-to tool to test the validity of your creations, as once your tests are conclusive, you will be able to run this code as a study to generate the alerts required to put it in real-world use, whether for discretionary trading or to interface with an execution bot/app. You may also find the backtesting results the Engine produces in study mode enough for your needs and spend most of your time there, only occasionally converting to strategy mode in order to backtest using TV backtesting.
As you will quickly grasp when you bring up this script’s Settings, this is a complex tool. While you will be able to see results very quickly by just putting it on a chart and using its built-in strategies, in order to reap the full benefits of the PineCoders Engine, you will need to invest the time required to understand the subtleties involved in putting all its potential into play.
Disclaimer: use the Engine at your own risk.
Before we delve in more detail, here’s a bird’s eye view of the Engine’s features:
More than 40 built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
By combining your own strats to the built-in strats supplied with the Engine, and then tuning the numerous options and parameters in the Inputs dialog box, you will be able to play what-if scenarios from an infinite number of permutations.
USE CASES
You have written an indicator that provides an entry strat but it’s missing other components like a filter and a stop strategy. You add a plot in your indicator that respects the Engine’s External Signal Protocol, connect it to the Engine by simply selecting your indicator’s plot name in the Engine’s Settings/Inputs and then run tests on different combinations of entry stops, in-trade stops and profit taking strats to find out which one produces the best results with your entry strat.
You are building a complex strategy that you will want to run as an indicator generating alerts to be sent to a third-party execution bot. You insert your code in the Engine’s modules and leverage its trade management code to quickly move your strategy into production.
You have many different filters and want to explore results using them separately or in combination. Integrate the filter code in the Engine and run through different permutations or hook up your filtering through the external input and control your filter combos from your indicator.
You are tweaking the parameters of your entry, filter or stop strat. You integrate it in the Engine and evaluate its performance using the Engine’s statistics.
You always wondered what results a random entry strat would yield on your markets. You use the Engine’s built-in random entry strat and test it using different combinations of filters, stop and exit strats.
You want to evaluate the impact of fees and slippage on your strategy. You use the Engine’s inputs to play with different values and get immediate feedback in the detailed numbers provided in the Data Window.
You just want to inspect the individual trades your strategy generates. You include it in the Engine and then inspect trades visually on your charts, looking at the numbers in the Data Window as you move your cursor around.
You have never written a production-grade strategy and you want to learn how. Inspect the code in the Engine; you will find essential components typical of what is being used in actual trading systems.
You have run your system for a while and have compiled actual slippage information and your broker/exchange has updated his fees schedule. You enter the information in the Engine and run it on your markets to see the impact this has on your results.
FEATURES
Before going into the detail of the Inputs and the Data Window numbers, here’s a more detailed overview of the Engine’s features.
Built-in strats
The engine comes with more than 40 pre-coded strategies for the following standard system components:
Entries,
Filters,
Entry stops,
2 stage in-trade stops with kick-in rules,
Pyramiding rules,
Hard exits.
While some of the filter and stop strats provided may be useful in production-quality systems, you will not devise crazy profit-generating systems using only the entry strats supplied; that part is still up to you, as will be finding the elusive combination of components that makes winning systems. The Engine will, however, provide you with a solid foundation where all the trade management nitty-gritty is handled for you. By binding your custom strats to the Engine, you will be able to build reliable systems of the best quality currently allowed on the TV platform.
On-chart trade information
As you move over the bars in a trade, you will see trade numbers in the Data Window change at each bar. The engine calculates the P&L at every bar, including slippage and fees that would be incurred were the trade exited at that bar’s close. If the trade includes pyramided entries, those will be taken into account as well, although for those, final fees and slippage are only calculated at the trade’s exit.
You can also see on-chart markers for the entry level, stop positions, in-trade special events and entries/exits (you will want to disable these when using the Engine in strategy mode to see TV backtesting results).
Customization
You can couple your own strats to the Engine in two ways:
1. By inserting your own code in the Engine’s different modules. The modular design should enable you to do so with minimal effort by following the instructions in the code.
2. By linking an external indicator to the engine. After making the proper selections in the engine’s Settings and providing values respecting the engine’s protocol, your external indicator can, when the Engine is used in Indicator mode only:
Tell the engine when to enter long or short trades, but let the engine’s in-trade stop and exit strats manage the exits,
Signal both entries and exits,
Provide an entry stop along with your entry signal,
Filter other entry signals generated by any of the engine’s entry strats.
Conversion from strategy to study
TradingView strategies are required to backtest using the TradingView backtesting feature, but if you want to generate alerts with your script, whether for automated trading or just to trigger alerts that you will use in discretionary trading, your code has to run as a study since, for the time being, strategies can’t generate alerts. From hereon we will use indicator as a synonym for study.
Unless you want to maintain two code bases, you will need hybrid code that easily flips between strategy and indicator modes, and your code will need to restrict its use of strategy() calls and their arguments if it’s going to be able to run both as an indicator and a strategy using the same trade logic. That’s one of the benefits of using this Engine. Once you will have entered your own strats in the Engine, it will be a matter of commenting/uncommenting only four lines of code to flip between indicator and strategy modes in a matter of seconds.
Additionally, even when running in Indicator mode, the Engine will still provide you with precious numbers on your individual trades and global results, some of which are not available with normal TradingView backtesting.
Post-Exit Analysis for alternate outcomes (PEA)
While typical backtesting shows results of trade outcomes, PEA focuses on what could have happened after the exit. The intention is to help traders get an idea of the opportunity/risk in the bars following the trade in order to evaluate if their exit strategies are too aggressive or conservative.
After a trade is exited, the Engine’s PEA module continues analyzing outcomes for a user-defined quantity of bars. It identifies the maximum opportunity and risk available in that space, and calculates the drawdown required to reach the highest opportunity level post-exit, while recording the number of bars to that point.
Typically, if you can’t find opportunity greater than 1X past your trade using a few different reasonable lengths of PEA, your strategy is doing pretty good at capturing opportunity. Remember that 100% of opportunity is never capturable. If, however, PEA was finding post-trade maximum opportunity of 3 or 4X with average drawdowns of 0.3 to those areas, this could be a clue revealing your system is exiting trades prematurely. To analyze PEA numbers, you can uncomment complete sets of plots in the Plot module to reveal detailed global and individual PEA numbers.
Statistics
The Engine provides stats on your trades that TV backtesting does not provide, such as:
Average Profitability Per Trade (APPT), aka statistical expectancy, a crucial value.
APPT per bar,
Average stop size,
Traded volume .
It also shows you on a trade-by-trade basis, on-going individual trade results and data.
In-trade events
In-trade events can plot reminders and trigger alerts when they occur. The built-in events are:
Price approaching stop,
Possible tops/bottoms,
Large stop movement (for discretionary trading where stop is moved manually),
Large price movements.
Slippage and Fees
Even when running in indicator mode, the Engine allows for slippage and fees to be included in the logic and test results.
Alerts
The alert creation mechanism allows you to configure alerts on any combination of the normal or pyramided entries, exits and in-trade events.
Backtesting results
A few words on the numbers calculated in the Engine. Priority is given to numbers not shown in TV backtesting, as you can readily convert the script to a strategy if you need them.
We have chosen to focus on numbers expressing results relative to X (the trade’s risk) rather than in absolute currency numbers or in other more conventional but less useful ways. For example, most of the individual trade results are not shown in percentages, as this unit of measure is often less meaningful than those expressed in units of risk (X). A trade that closes with a +25% result, for example, is a poor outcome if it was entered with a -50% stop. Expressed in X, this trade’s P&L becomes 0.5, which provides much better insight into the trade’s outcome. A trade that closes with a P&L of +2X has earned twice the risk incurred upon entry, which would represent a pre-trade risk:reward ratio of 2.
The way to go about it when you think in X’s and that you adopt the sound risk management policy to risk a fixed percentage of your account on each trade is to equate a currency value to a unit of X. E.g. your account is 10K USD and you decide you will risk a maximum of 1% of it on each trade. That means your unit of X for each trade is worth 100 USD. If your APPT is 2X, this means every time you risk 100 USD in a trade, you can expect to make, on average, 200 USD.
By presenting results this way, we hope that the Engine’s statistics will appeal to those cognisant of sound risk management strategies, while gently leading traders who aren’t, towards them.
We trade to turn in tangible profits of course, so at some point currency must come into play. Accordingly, some values such as equity, P&L, slippage and fees are expressed in currency.
Many of the usual numbers shown in TV backtests are nonetheless available, but they have been commented out in the Engine’s Plot module.
Position sizing and risk management
All good system designers understand that optimal risk management is at the very heart of all winning strategies. The risk in a trade is defined by the fraction of current equity represented by the amplitude of the stop, so in order to manage risk optimally on each trade, position size should adjust to the stop’s amplitude. Systems that enter trades with a fixed stop amplitude can get away with calculating position size as a fixed percentage of current equity. In the context of a test run where equity varies, what represents a fixed amount of risk translates into different currency values.
Dynamically adjusting position size throughout a system’s life is optimal in many ways. First, as position sizing will vary with current equity, it reproduces a behavioral pattern common to experienced traders, who will dial down risk when confronted to poor performance and increase it when performance improves. Second, limiting risk confers more predictability to statistical test results. Third, position sizing isn’t just about managing risk, it’s also about maximizing opportunity. By using the maximum leverage (no reference to trading on margin here) into the trade that your risk management strategy allows, a dynamic position size allows you to capture maximal opportunity.
To calculate position sizes using the fixed risk method, we use the following formula: Position = Account * MaxRisk% / Stop% [, which calculates a position size taking into account the trade’s entry stop so that if the trade is stopped out, 100 USD will be lost. For someone who manages risk this way, common instructions to invest a certain percentage of your account in a position are simply worthless, as they do not take into account the risk incurred in the trade.
The Engine lets you select either the fixed risk or fixed percentage of equity position sizing methods. The closest thing to dynamic position sizing that can currently be done with alerts is to use a bot that allows syntax to specify position size as a percentage of equity which, while being dynamic in the sense that it will adapt to current equity when the trade is entered, does not allow us to modulate position size using the stop’s amplitude. Changes to alerts are on the way which should solve this problem.
In order for you to simulate performance with the constraint of fixed position sizing, the Engine also offers a third, less preferable option, where position size is defined as a fixed percentage of initial capital so that it is constant throughout the test and will thus represent a varying proportion of current equity.
Let’s recap. The three position sizing methods the Engine offers are:
1. By specifying the maximum percentage of risk to incur on your remaining equity, so the Engine will dynamically adjust position size for each trade so that, combining the stop’s amplitude with position size will yield a fixed percentage of risk incurred on current equity,
2. By specifying a fixed percentage of remaining equity. Note that unless your system has a fixed stop at entry, this method will not provide maximal risk control, as risk will vary with the amplitude of the stop for every trade. This method, as the first, does however have the advantage of automatically adjusting position size to equity. It is the Engine’s default method because it has an equivalent in TV backtesting, so when flipping between indicator and strategy mode, test results will more or less correspond.
3. By specifying a fixed percentage of the Initial Capital. While this is the least preferable method, it nonetheless reflects the reality confronted by most system designers on TradingView today. In this case, risk varies both because the fixed position size in initial capital currency represents a varying percentage of remaining equity, and because the trade’s stop amplitude may vary, adding another variability vector to risk.
Note that the Engine cannot display equity results for strategies entering trades for a fixed amount of shares/contracts at a variable price.
SETTINGS/INPUTS
Because the initial text first published with a script cannot be edited later and because there are just too many options, the Engine’s Inputs will not be covered in minute detail, as they will most certainly evolve. We will go over them with broad strokes; you should be able to figure the rest out. If you have questions, just ask them here or in the PineCoders Telegram group.
Display
The display header’s checkbox does nothing.
For the moment, only one exit strategy uses a take profit level, so only that one will show information when checking “Show Take Profit Level”.
Entries
You can activate two simultaneous entry strats, each selected from the same set of strats contained in the Engine. If you select two and they fire simultaneously, the main strat’s signal will be used.
The random strat in each list uses a different seed, so you will get different results from each.
The “Filter transitions” and “Filter states” strats delegate signal generation to the selected filter(s). “Filter transitions” signals will only fire when the filter transitions into bull/bear state, so after a trade is stopped out, the next entry may take some time to trigger if the filter’s state does not change quickly. When you choose “Filter states”, then a new trade will be entered immediately after an exit in the direction the filter allows.
If you select “External Indicator”, your indicator will need to generate a +2/-2 (or a positive/negative stop value) to enter a long/short position, providing the selected filters allow for it. If you wish to use the Engine’s capacity to also derive the entry stop level from your indicator’s signal, then you must explicitly choose this option in the Entry Stops section.
Filters
You can activate as many filters as you wish; they are additive. The “Maximum stop allowed on entry” is an important component of proper risk management. If your system has an average 3% stop size and you need to trade using fixed position sizes because of alert/execution bot limitations, you must use this filter because if your system was to enter a trade with a 15% stop, that trade would incur 5 times the normal risk, and its result would account for an abnormally high proportion in your system’s performance.
Remember that any filter can also be used as an entry signal, either when it changes states, or whenever no trade is active and the filter is in a bull or bear mode.
Entry Stops
An entry stop must be selected in the Engine, as it requires a stop level before the in-trade stop is calculated. Until the selected in-trade stop strat generates a stop that comes closer to price than the entry stop (or respects another one of the in-trade stops kick in strats), the entry stop level is used.
It is here that you must select “External Indicator” if your indicator supplies a +price/-price value to be used as the entry stop. A +price is expected for a long entry and a -price value will enter a short with a stop at price. Note that the price is the absolute price, not an offset to the current price level.
In-Trade Stops
The Engine comes with many built-in in-trade stop strats. Note that some of them share the “Length” and “Multiple” field, so when you swap between them, be sure that the length and multiple in use correspond to what you want for that stop strat. Suggested defaults appear with the name of each strat in the dropdown.
In addition to the strat you wish to use, you must also determine when it kicks in to replace the initial entry’s stop, which is determined using different strats. For strats where you can define a positive or negative multiple of X, percentage or fixed value for a kick-in strat, a positive value is above the trade’s entry fill and a negative one below. A value of zero represents breakeven.
Pyramiding
What you specify in this section are the rules that allow pyramiding to happen. By themselves, these rules will not generate pyramiding entries. For those to happen, entry signals must be issued by one of the active entry strats, and conform to the pyramiding rules which act as a filter for them. The “Filter must allow entry” selection must be chosen if you want the usual system’s filters to act as additional filtering criteria for your pyramided entries.
Hard Exits
You can choose from a variety of hard exit strats. Hard exits are exit strategies which signal trade exits on specific events, as opposed to price breaching a stop level in In-Trade Stops strategies. They are self-explanatory. The last one labelled When Take Profit Level (multiple of X) is reached is the only one that uses a level, but contrary to stops, it is above price and while it is relative because it is expressed as a multiple of X, it does not move during the trade. This is the level called Take Profit that is show when the “Show Take Profit Level” checkbox is checked in the Display section.
While stops focus on managing risk, hard exit strategies try to put the emphasis on capturing opportunity.
Slippage
You can define it as a percentage or a fixed value, with different settings for entries and exits. The entry and exit markers on the chart show the impact of slippage on the entry price (the fill).
Fees
Fees, whether expressed as a percentage of position size in and out of the trade or as a fixed value per in and out, are in the same units of currency as the capital defined in the Position Sizing section. Fees being deducted from your Capital, they do not have an impact on the chart marker positions.
In-Trade Events
These events will only trigger during trades. They can be helpful to act as reminders for traders using the Engine as assistance to discretionary trading.
Post-Exit Analysis
It is normally on. Some of its results will show in the Global Numbers section of the Data Window. Only a few of the statistics generated are shown; many more are available, but commented out in the Plot module.
Date Range Filtering
Note that you don’t have to change the dates to enable/diable filtering. When you are done with a specific date range, just uncheck “Date Range Filtering” to disable date filtering.
Alert Triggers
Each selection corresponds to one condition. Conditions can be combined into a single alert as you please. Just be sure you have selected the ones you want to trigger the alert before you create the alert. For example, if you trade in both directions and you want a single alert to trigger on both types of exits, you must select both “Long Exit” and “Short Exit” before creating your alert.
Once the alert is triggered, these settings no longer have relevance as they have been saved with the alert.
When viewing charts where an alert has just triggered, if your alert triggers on more than one condition, you will need the appropriate markers active on your chart to figure out which condition triggered the alert, since plotting of markers is independent of alert management.
Position sizing
You have 3 options to determine position size:
1. Proportional to Stop -> Variable, with a cap on size.
2. Percentage of equity -> Variable.
3. Percentage of Initial Capital -> Fixed.
External Indicator
This is where you connect your indicator’s plot that will generate the signals the Engine will act upon. Remember this only works in Indicator mode.
DATA WINDOW INFORMATION
The top part of the window contains global numbers while the individual trade information appears in the bottom part. The different types of units used to express values are:
curr: denotes the currency used in the Position Sizing section of Inputs for the Initial Capital value.
quote: denotes quote currency, i.e. the value the instrument is expressed in, or the right side of the market pair (USD in EURUSD ).
X: the stop’s amplitude, itself expressed in quote currency, which we use to express a trade’s P&L, so that a trade with P&L=2X has made twice the stop’s amplitude in profit. This is sometimes referred to as R, since it represents one unit of risk. It is also the unit of measure used in the APPT, which denotes expected reward per unit of risk.
X%: is also the stop’s amplitude, but expressed as a percentage of the Entry Fill.
The numbers appearing in the Data Window are all prefixed:
“ALL:” the number is the average for all first entries and pyramided entries.
”1ST:” the number is for first entries only.
”PYR:” the number is for pyramided entries only.
”PEA:” the number is for Post-Exit Analyses
Global Numbers
Numbers in this section represent the results of all trades up to the cursor on the chart.
Average Profitability Per Trade (X): This value is the most important gauge of your strat’s worthiness. It represents the returns that can be expected from your strat for each unit of risk incurred. E.g.: your APPT is 2.0, thus for every unit of currency you invest in a trade, you can on average expect to obtain 2 after the trade. APPT is also referred to as “statistical expectancy”. If it is negative, your strategy is losing, even if your win rate is very good (it means your winning trades aren’t winning enough, or your losing trades lose too much, or both). Its counterpart in currency is also shown, as is the APPT/bar, which can be a useful gauge in deciding between rivalling systems.
Profit Factor: Gross of winning trades/Gross of losing trades. Strategy is profitable when >1. Not as useful as the APPT because it doesn’t take into account the win rate and the average win/loss per trade. It is calculated from the total winning/losing results of this particular backtest and has less predictive value than the APPT. A good profit factor together with a poor APPT means you just found a chart where your system outperformed. Relying too much on the profit factor is a bit like a poker player who would think going all in with two’s against aces is optimal because he just won a hand that way.
Win Rate: Percentage of winning trades out of all trades. Taken alone, it doesn’t have much to do with strategy profitability. You can have a win rate of 99% but if that one trade in 100 ruins you because of poor risk management, 99% doesn’t look so good anymore. This number speaks more of the system’s profile than its worthiness. Still, it can be useful to gauge if the system fits your personality. It can also be useful to traders intending to sell their systems, as low win rate systems are more difficult to sell and require more handholding of worried customers.
Equity (curr): This the sum of initial capital and the P&L of your system’s trades, including fees and slippage.
Return on Capital is the equivalent of TV’s Net Profit figure, i.e. the variation on your initial capital.
Maximum drawdown is the maximal drawdown from the highest equity point until the drop . There is also a close to close (meaning it doesn’t take into account in-trade variations) maximum drawdown value commented out in the code.
The next values are self-explanatory, until:
PYR: Avg Profitability Per Entry (X): this is the APPT for all pyramided entries.
PEA: Avg Max Opp . Available (X): the average maximal opportunity found in the Post-Exit Analyses.
PEA: Avg Drawdown to Max Opp . (X): this represents the maximum drawdown (incurred from the close at the beginning of the PEA analysis) required to reach the maximal opportunity point.
Trade Information
Numbers in this section concern only the current trade under the cursor. Most of them are self-explanatory. Use the description’s prefix to determine what the values applies to.
PYR: Avg Profitability Per Entry (X): While this value includes the impact of all current pyramided entries (and only those) and updates when you move your cursor around, P&L only reflects fees at the trade’s last bar.
PEA: Max Opp . Available (X): It’s the most profitable close reached post-trade, measured from the trade’s Exit Fill, expressed in the X value of the trade the PEA follows.
PEA: Drawdown to Max Opp . (X): This is the maximum drawdown from the trade’s Exit Fill that needs to be sustained in order to reach the maximum opportunity point, also expressed in X. Note that PEA numbers do not include slippage and fees.
EXTERNAL SIGNAL PROTOCOL
Only one external indicator can be connected to a script; in order to leverage its use to the fullest, the engine provides options to use it as either an entry signal, an entry/exit signal or a filter. When used as an entry signal, you can also use the signal to provide the entry’s stop. Here’s how this works:
For filter state: supply +1 for bull (long entries allowed), -1 for bear (short entries allowed).
For entry signals: supply +2 for long, -2 for short.
For exit signals: supply +3 for exit from long, -3 for exit from short.
To send an entry stop level with an entry signal: Send positive stop level for long entry (e.g. 103.33 to enter a long with a stop at 103.33), negative stop level for short entry (e.g. -103.33 to enter a short with a stop at 103.33). If you use this feature, your indicator will have to check for exact stop levels of 1.0, 2.0 or 3.0 and their negative counterparts, and fudge them with a tick in order to avoid confusion with other signals in the protocol.
Remember that mere generation of the values by your indicator will have no effect until you explicitly allow their use in the appropriate sections of the Engine’s Settings/Inputs.
An example of a script issuing a signal for the Engine is published by PineCoders.
RECOMMENDATIONS TO ASPIRING SYSTEM DESIGNERS
Stick to higher timeframes. On progressively lower timeframes, margins decrease and fees and slippage take a proportionally larger portion of profits, to the point where they can very easily turn a profitable strategy into a losing one. Additionally, your margin for error shrinks as the equilibrium of your system’s profitability becomes more fragile with the tight numbers involved in the shorter time frames. Avoid <1H time frames.
Know and calculate fees and slippage. To avoid market shock, backtest using conservative fees and slippage parameters. Systems rarely show unexpectedly good returns when they are confronted to the markets, so put all chances on your side by being outrageously conservative—or a the very least, realistic. Test results that do not include fees and slippage are worthless. Slippage is there for a reason, and that’s because our interventions in the market change the market. It is easier to find alpha in illiquid markets such as cryptos because not many large players participate in them. If your backtesting results are based on moving large positions and you don’t also add the inevitable slippage that will occur when you enter/exit thin markets, your backtesting will produce unrealistic results. Even if you do include large slippage in your settings, the Engine can only do so much as it will not let slippage push fills past the high or low of the entry bar, but the gap may be much larger in illiquid markets.
Never test and optimize your system on the same dataset , as that is the perfect recipe for overfitting or data dredging, which is trying to find one precise set of rules/parameters that works only on one dataset. These setups are the most fragile and often get destroyed when they meet the real world.
Try to find datasets yielding more than 100 trades. Less than that and results are not as reliable.
Consider all backtesting results with suspicion. If you never entertained sceptic tendencies, now is the time to begin. If your backtest results look really good, assume they are flawed, either because of your methodology, the data you’re using or the software doing the testing. Always assume the worse and learn proper backtesting techniques such as monte carlo simulations and walk forward analysis to avoid the traps and biases that unchecked greed will set for you. If you are not familiar with concepts such as survivor bias, lookahead bias and confirmation bias, learn about them.
Stick to simple bars or candles when designing systems. Other types of bars often do not yield reliable results, whether by design (Heikin Ashi) or because of the way they are implemented on TV (Renko bars).
Know that you don’t know and use that knowledge to learn more about systems and how to properly test them, about your biases, and about yourself.
Manage risk first , then capture opportunity.
Respect the inherent uncertainty of the future. Cleanse yourself of the sad arrogance and unchecked greed common to newcomers to trading. Strive for rationality. Respect the fact that while backtest results may look promising, there is no guarantee they will repeat in the future (there is actually a high probability they won’t!), because the future is fundamentally unknowable. If you develop a system that looks promising, don’t oversell it to others whose greed may lead them to entertain unreasonable expectations.
Have a plan. Understand what king of trading system you are trying to build. Have a clear picture or where entries, exits and other important levels will be in the sort of trade you are trying to create with your system. This stated direction will help you discard more efficiently many of the inevitably useless ideas that will pop up during system design.
Be wary of complexity. Experienced systems engineers understand how rapidly complexity builds when you assemble components together—however simple each one may be. The more complex your system, the more difficult it will be to manage.
Play! . Allow yourself time to play around when you design your systems. While much comes about from working with a purpose, great ideas sometimes come out of just trying things with no set goal, when you are stuck and don’t know how to move ahead. Have fun!
@LucF
NOTES
While the engine’s code can supply multiple consecutive entries of longs or shorts in order to scale positions (pyramid), all exits currently assume the execution bot will exit the totality of the position. No partial exits are currently possible with the Engine.
Because the Engine is literally crippled by the limitations on the number of plots a script can output on TV; it can only show a fraction of all the information it calculates in the Data Window. You will find in the Plot Module vast amounts of commented out lines that you can activate if you also disable an equivalent number of other plots. This may be useful to explore certain characteristics of your system in more detail.
When backtesting using the TV backtesting feature, you will need to provide the strategy parameters you wish to use through either Settings/Properties or by changing the default values in the code’s header. These values are defined in variables and used not only in the strategy() statement, but also as defaults in the Engine’s relevant Inputs.
If you want to test using pyramiding, then both the strategy’s Setting/Properties and the Engine’s Settings/Inputs need to allow pyramiding.
If you find any bugs in the Engine, please let us know.
THANKS
To @glaz for allowing the use of his unpublished MA Squize in the filters.
To @everget for his Chandelier stop code, which is also used as a filter in the Engine.
To @RicardoSantos for his pseudo-random generator, and because it’s from him that I first read in the Pine chat about the idea of using an external indicator as input into another. In the PineCoders group, @theheirophant then mentioned the idea of using it as a buy/sell signal and @simpelyfe showed a piece of code implementing the idea. That’s the tortuous story behind the use of the external indicator in the Engine.
To @admin for the Volatility stop’s original code and for the donchian function lifted from Ichimoku .
To @BobHoward21 for the v3 version of Volatility Stop .
To @scarf and @midtownsk8rguy for the color tuning.
To many other scripters who provided encouragement and suggestions for improvement during the long process of writing and testing this piece of code.
To J. Welles Wilder Jr. for ATR, used extensively throughout the Engine.
To TradingView for graciously making an account available to PineCoders.
And finally, to all fellow PineCoders for the constant intellectual stimulation; it is a privilege to share ideas with you all. The Engine is for all TradingView PineCoders, of course—but especially for you.
Look first. Then leap.
Tick-Based Delta Volume BubblesTICK-BASED DELTA VOLUME BUBBLES
OVERVIEW
A real-time order flow indicator that displays volume delta at the tick level, helping traders identify buying and selling pressure as it develops during live market hours. Unlike traditional volume delta indicators that rely on bar close data, this indicator captures actual tick-by-tick volume changes and directional bias, providing granular insight into market dynamics.
HOW IT WORKS
The indicator monitors live tick data during real-time trading by tracking volume increases between consecutive price updates. Each time volume increments, the script calculates the volume delta, determines price direction, assigns directional bias to the volume, and accumulates net delta for each bar.
This methodology is identical to the tick detection mechanism used in professional cumulative volume delta tools, ensuring accuracy and reliability.
FEATURES
Real-Time Tick Detection
- Captures genuine tick-by-tick volume flow using varip persistence
- Not estimated from OHLC data
- Processes actual market ticks as they occur
Adaptive Bubble Sizing
- Bubbles scale based on delta strength relative to a customizable moving average (default 20 bars)
- Highlights significant order flow imbalances
- Five size levels from tiny to huge
Dual Display Modes
- Normal Mode: Sized bubbles with optional volume labels positioned at bar midpoint
- Minimal Mode: Clean dots above/below bars for unobtrusive delta visualization
Flow Classification
- Aggressive Buy (bright green): Strong positive delta with greater than 1.2x strength
- Aggressive Sell (bright red): Strong negative delta with greater than 1.2x strength
- Passive Buy (light green): Moderate positive delta
- Passive Sell (light red): Moderate negative delta
Intensity Mode (Optional)
- Gray: Low intensity (less than 0.5x average)
- Blue: Medium intensity (0.5-1.0x average)
- Orange: High intensity (1.0-2.0x average)
- Red: Extreme intensity (greater than 2.0x average)
Smart Filtering
- Percentile-based filters (customizable) ensure only significant delta events are displayed
- Reduces chart clutter while highlighting important order flow
- Separate thresholds for bubble display and numeric labels
Data Collection Status
- Optional progress box in top-right corner
- Shows real-time bar collection progress
- Displays percentage completion and bars remaining
- Automatically hides when sufficient data is collected
Hide Until Ready Option
- Suppresses bubble display until the averaging period is complete
- Prevents misleading signals from incomplete data
- Default requires 20 bars before displaying bubbles
SETTINGS
Delta Average Length (1-200, default 20)
- Lookback period for calculating delta strength baseline
- Higher values = longer-term delta comparison
- Lower values = more sensitive to recent changes
Hide Bubbles Until Enough Data
- Prevents display until averaging period completes
- Ensures reliable delta strength calculations
Show Data Collection Status Box
- Displays progress indicator during initialization
- Can be disabled if you understand the warmup period
Minimal Mode
- Switches to simple dot display above/below bars
- Green dots above bars = positive delta
- Red dots below bars = negative delta
- Maintains color intensity or flow type classification
Show Bubbles
- Master toggle for bubble display
Bubble Volume Percentile (0-100, default 60)
- Minimum percentile rank required to display bubble
- Higher values = fewer, more significant bubbles
- Lower values = more bubbles displayed
Show Numbers in Bubbles
- Toggle delta value labels
- Only appears in normal mode
- Disabled automatically in minimal mode
Label Volume Percentile (0-100, default 90)
- Higher threshold for displaying numeric labels
- Typically set higher than bubble percentile
- Reduces label clutter on chart
Intensity Mode
- Switch from flow-type coloring to magnitude-based coloring
- Useful for identifying volume spikes regardless of direction
IMPORTANT NOTES
Real-Time Only: This indicator processes live tick data and does not provide historical analysis. It begins collecting data when added to a live chart.
Volume Required: Symbol must have volume data available. Will not function on symbols without volume (most forex pairs from retail brokers).
Initialization Period: Requires the specified number of bars (default 20) to calculate accurate delta strength. Use the "Hide Until Ready" option to prevent premature signals.
Market Hours: Only collects data during live market hours. Does not backfill historical data.
CREDITS
Tick detection methodology inspired by the Kioseff Trading Tick CVD indicator. This implementation adapts the same core tick-level volume delta calculation for bubble-style visualization and per-bar delta analysis.
Continuation Suite v1 — 5m/15mContinuation Suite v1 — 5m/15m (Non-Repainting, S/R + Trend Continuation)
What it does
Continuation Suite v1 is a practical intraday toolkit that combines non-repainting trend-continuation signals with auto-built Support/Resistance (S/R) from confirmed pivots. It’s designed for fast, liquid names on 5m charts with an optional 15m higher-timeframe (HTF) overlay. You get: stacked-EMA bias, disciplined pullback+reclaim entries, optional volume/volatility gates, a “Strong” signal tier, solid S/R lines or zones, and a compact dashboard for fast reads.
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Why traders use it
• Clear bias using fast/mid/slow EMA stacking.
• Actionable entries that require a pullback, a reclaim, and (optionally) a minor break of prior extremes.
• Signal quality gates (volume vs SMA, ATR%, ADX/DI alignment, EMA spacing, slope).
• Non-repainting logic when “Confirm on Close” = ON. Intrabar previews show what’s forming, but confirmed signals only print on bar close.
• S/R that matters: confirmed-pivot lines or ATR-sized zones, optional HTF overlay, and auto de-dup to avoid clutter.
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Signal construction (no magic, just rules)
Bullish continuation (base):
1. Trend: EMA fast > EMA mid > EMA slow
2. Pullback: price pulls into the stack (lowest low or close vs EMA fast/mid over a lookback)
3. Reclaim: close > EMA fast and close > open
4. Break filter (optional): current bar takes out the prior bar’s high
5. Filters: volume > SMA (if enabled) and ATR% ≤ max (if enabled)
6. Cooldown: a minimum bar gap between signals
Bearish continuation (base): mirror of the above.
Strong signals: base conditions plus ADX ≥ threshold, DI alignment (DI+>DI- for longs; DI->DI+ for shorts), minimum EMA-spacing %, and minimum fast-EMA slope.
Reference stops:
• Longs: lowest low over the pullback lookback
• Shorts: highest high over the pullback lookback
Alerts are included for: Bullish Continuation, Bearish Continuation, STRONG Bullish, STRONG Bearish.
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S/R engine (current TF + optional HTF)
• Builds S/R from confirmed pivots only (left/right bars).
• Choose Lines (midlines) or Zones (ATR-sized).
• Zones merge when a new pivot lands near an existing zone’s mid (ATR-scaled epsilon).
• Touches counter tracks significance; you can require a minimum to draw.
• HTF overlay (default 15m) draws separate lines/zones with tiny TF tags on the right.
• De-dup option hides current-TF zones that sit too close to HTF zones (ATR-scaled), reducing overlap.
• Freeze on Close (optional) keeps arrays stable intrabar; snapshots show levels immediately as bars open.
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Presets
• Auto: Detects QQQ-like tickers (QQQ, QLD, QID) or SoFi; else defaults to Custom.
• QQQ: Tighter ATR% and EMA settings geared to index-ETF behavior.
• SoFi: Wider ATR allowances and longer mid/slow for single-name behavior.
• Custom: Expose all key inputs to tune for your product.
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Dashboard (top-right)
• Preset in use
• Bias (Bullish CONT / Bearish CONT / Neutral)
• Strong (Yes/No)
• Volatility (ATR% bucket)
• Trend (ADX bucket)
• HTF timeframe tag
• Volume (bucket or “off”)
• Signals mode (Close-Confirmed vs Intrabar)
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Inputs you’ll actually adjust
Trend/Signals
• Fast/Mid/Slow EMA lengths
• Pullback lookback, Min bars between signals
• Volume filter (vol > SMA N)
• ATR% max filter (cap excessive volatility)
• Require break of prior bar’s high/low
• “Strong” gates: min EMA slope, min EMA spacing %, ADX length & threshold
Support/Resistance
• Lines vs Zones
• Pivot left/right bars
• Extend left/right (bars)
• Max pivots kept (current & HTF)
• Zone width (× ATR), Merge epsilon (× ATR), Min gap (× ATR)
• Min touches, Max zones per side near price
• De-dup current TF vs HTF (× ATR)
Repainting control
• Confirm on Close: when ON, signals/SR finalize on bar close (non-repainting)
• Freeze on Close: freeze S/R intrabar with snapshot updates
• Show previews: translucent intrabar labels for what’s forming
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How to use it (straightforward)
1. Load on 5-minute chart (baseline). Keep Confirm on Close ON if you hate repainting.
2. Use Bias + Strong + S/R context. If a long prints into HTF resistance, you have information.
3. Manage risk off the reference stop (pullback extreme). If ATR% reads “Great,” widen expectations; if “Poor,” size down or pass.
4. Alerts: wire the four alert types to your workflow.
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Notes and constraints
• Designed for liquid symbols. Thin books and synthetic “volume” will degrade the volume gate.
• S/R is pivot-based. On very choppy tape, touch counts help. Increase min touches or switch to Lines to declutter.
• If your chart timeframe isn’t 5m, behavior changes because lengths are in bars, not minutes. Tune lengths accordingly.
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Disclaimers
This is a research tool. No signals are guaranteed. Markets change, outliers happen, slippage is real. Nothing here is financial advice—use your own judgment and risk management.
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Author: DaddyScruff
License: MPL-2.0 (Mozilla Public License 2.0)
Stage Market AnalyzerStage Market Analyzer – User Guide
Overview:
The “Stage Market Analyzer” indicator is a comprehensive market analysis tool that identifies the current market phase (6 stages) using multiple EMAs (Exponential Moving Averages) and provides key performance metrics including 52-week high, YTD change, and recent price changes. This indicator is displayed on the chart with a visual table and plotted EMA lines for easy trend analysis.
Market Stages
-The indicator classifies the market into six stages based on the position of price relative to the fast and slow EMAs:
Recovery:
-Price above the fast EMA, but below the slow EMA.
-Slow EMA is above the fast EMA.
-ndicates a market recovering from a downtrend.
Accumulation:
-Price above both EMAs, slow EMA above fast EMA.
-Suggests accumulation phase, usually after a downtrend.
Bull Market:
-Price above both EMAs, fast EMA above slow EMA.
-Represents strong uptrend.
Warning:
-Price below both EMAs, fast EMA above slow EMA.
-Signals caution; potential weakening trend.
Distribution:
-Price below fast EMA, slow EMA below fast EMA.
-Market may be topping or preparing to reverse.
Bear Market:
-Price below both EMAs, slow EMA above fast EMA.
-Strong downtrend confirmed.
The indicator counts consecutive bars within the same stage and displays this as “Stage Name (X Bar)” in the table.
EMA Settings
-Fast EMA: Default 50 bars.
-Slow EMA: Default 200 bars.
Additional EMAs: EMA1 (21), EMA2 (100), EMA3 (150) – optional display.
Users can customize all EMA lengths and choose which EMAs to display.
The plotted EMAs help visualize trends, crossovers, and market momentum.
Performance Metrics
30-Bar & 90-Bar Price Change:
Displays the percentage change over the last 30 or 90 bars.
Positive change in green, negative in red.
YTD Change (Year-to-Date):
-Calculated from the first trading bar of the current year to current price.
-Reflects overall market performance for the current year.
52-Week High:
-Shows the percentage difference between current price and the highest price over the last 52 weeks.
-Adjusts automatically for the chart timeframe:
Daily: last 252 bars
Weekly: last 52 bars
Monthly: last 12 bars
Intraday: calculated based on bars per day × 252 trading days
Positive deviation is shown in green, negative in red.
Note: For non-daily charts, the calculation approximates a “year” based on available bars.
Table Display
Located at the bottom-right of the chart.
Columns:
Current Market Stage (with consecutive bar count)
30-Bar Change
90-Bar Change
YTD Change
52-Week High (optional)
Background colors indicate the stage for quick visual reference.
How to Use
Add the indicator to your chart.
Adjust EMAs to match your trading strategy.
Observe the table to understand:
Current market phase
Short-term and long-term performance metrics
Trend direction using plotted EMAs
Use the stage information together with other analysis (support/resistance, volume, etc.) to make informed trading decisions.
Notes & Recommendations
The indicator works best on daily charts for accurate 52-week high and YTD calculations.
For crypto or non-standard trading calendars, be aware that intraday data may approximate the “year” differently.
EMAs are customizable – experiment with different lengths to fit your preferred timeframe or trading style.
BayesStack RSI [CHE]BayesStack RSI — Stacked RSI with Bayesian outcome stats and gradient visualization
Summary
BayesStack RSI builds a four-length RSI stack and evaluates it with a simple Bayesian success model over a rolling window. It highlights bull and bear stack regimes, colors price with magnitude-based gradients, and reports per-regime counts, wins, and estimated win rate in a compact table. Signals seek to be more robust through explicit ordering tolerance, optional midline gating, and outcome evaluation that waits for events to mature by a fixed horizon. The design focuses on readable structure, conservative confirmation, and actionable context rather than raw oscillator flips.
Motivation: Why this design?
Classical RSI signals flip frequently in volatile phases and drift in calm regimes. Pure threshold rules often misclassify shallow pullbacks and stacked momentum phases. The core idea here is ordered, spaced RSI layers combined with outcome tracking. By requiring a consistent order with a tolerance and optionally gating by the midline, regime identification becomes clearer. A horizon-based maturation check and smoothed win-rate estimate provide pragmatic feedback about how often a given stack has recently worked.
What’s different vs. standard approaches?
Reference baseline: Traditional single-length RSI with overbought and oversold rules or simple crossovers.
Architecture differences:
Four fixed RSI lengths with strict ordering and a spacing tolerance.
Optional requirement that all RSI values stay above or below the midline for bull or bear regimes.
Outcome evaluation after a fixed horizon, then rolling counts and a prior-smoothed win rate.
Dispersion measurement across the four RSIs with a percent-rank diagnostic.
Gradient coloring of candles and wicks driven by stack magnitude.
A last-bar statistics table with counts, wins, win rate, dispersion, and priors.
Practical effect: Charts emphasize sustained momentum alignment instead of single-length crosses. Users see when regimes start, how strong alignment is, and how that regime has recently performed for the chosen horizon.
How it works (technical)
The script computes RSI on four lengths and forms a “stack” when they are strictly ordered with at least the chosen tolerance between adjacent lengths. A bull stack requires a descending set from long to short with positive spacing. A bear stack requires the opposite. Optional gating further requires all RSI values to sit above or below the midline.
For evaluation, each detected stack is checked again after the horizon has fully elapsed. A bull event is a success if price is higher than it was at event time after the horizon has passed. A bear event succeeds if price is lower under the same rule. Rolling sums over the training window track counts and successes; a pair of priors stabilizes the win-rate estimate when sample sizes are small.
Dispersion across the four RSIs is measured and converted to a percent rank over a configurable window. Gradients for bars and wicks are normalized over a lookback, then shaped by gamma controls to emphasize strong regimes. A statistics table is created once and updated on the last bar to minimize overhead. Overlay markers and wick coloring are rendered to the price chart even though the indicator runs in a separate pane.
Parameter Guide
Source — Input series for RSI. Default: close. Tips: Use typical price or hlc3 for smoother behavior.
Overbought / Oversold — Guide levels for context. Defaults: seventy and thirty. Bounds: fifty to one hundred, zero to fifty. Tips: Narrow the band for faster feedback.
Stacking tolerance (epsilon) — Minimum spacing between adjacent RSIs to qualify as a stack. Default: zero point twenty-five RSI points. Trade-off: Higher values reduce false stacks but delay entries.
Horizon H — Bars ahead for outcome evaluation. Default: three. Trade-off: Longer horizons reduce noise but delay success attribution.
Rolling window — Lookback for counts and wins. Default: five hundred. Trade-off: Longer windows stabilize the win rate but adapt more slowly.
Alpha prior / Beta prior — Priors used to stabilize the win-rate estimate. Defaults: one and one. Trade-off: Larger priors reduce variance with sparse samples.
Show RSI 8/13/21/34 — Toggle raw RSI lines. Default: on.
Show consensus RSI — Weighted combination of the four RSIs. Default: on.
Show OB/OS zones — Draw overbought, oversold, and midline. Default: on.
Background regime — Pane background tint during bull or bear stacks. Default: on.
Overlay regime markers — Entry markers on price when a stack forms. Default: on.
Show statistics table — Last-bar table with counts, wins, win rate, dispersion, priors, and window. Default: on.
Bull requires all above fifty / Bear requires all below fifty — Midline gate. Defaults: both on. Trade-off: Stricter regimes, fewer but cleaner signals.
Enable gradient barcolor / wick coloring — Gradient visuals mapped to stack magnitude. Defaults: on. Trade-off: Clearer regime strength vs. extra rendering cost.
Collection period — Normalization window for gradients. Default: one hundred. Trade-off: Shorter values react faster but fluctuate more.
Gamma bars and shapes / Gamma plots — Curve shaping for gradients. Defaults: zero point seven and zero point eight. Trade-off: Higher values compress weak signals and emphasize strong ones.
Gradient and wick transparency — Visual opacity controls. Defaults: zero.
Up/Down colors (dark and neon) — Gradient endpoints. Defaults: green and red pairs.
Fallback neutral candles — Directional coloring when gradients are off. Default: off.
Show last candles — Limit for gradient squares rendering. Default: three hundred thirty-three.
Dispersion percent-rank length / High and Low thresholds — Window and cutoffs for dispersion diagnostics. Defaults: two hundred fifty, eighty, and twenty.
Table X/Y, Dark theme, Text size — Table anchor, theme, and typography. Defaults: right, top, dark, small.
Reading & Interpretation
RSI stack lines: Alignment and spacing convey regime quality. Wider spacing suggests stronger alignment.
Consensus RSI: A single line that summarizes the four lengths; use as a smoother reference.
Zones: Overbought, oversold, and midline provide context rather than standalone triggers.
Background tint: Indicates active bull or bear stack.
Markers: “Bull Stack Enter” or “Bear Stack Enter” appears when the stack first forms.
Gradients: Brighter tones suggest stronger stack magnitude; dull tones suggest weak alignment.
Table: Count and Wins show sample size and successes over the window. P(win) is a prior-stabilized estimate. Dispersion percent rank near the high threshold flags stretched alignment; near the low threshold flags tight clustering.
Practical Workflows & Combinations
Trend following: Enter only on new stack markers aligned with structure such as higher highs and higher lows for bull, or lower lows and lower highs for bear. Use the consensus RSI to avoid chasing into overbought or oversold extremes.
Exits and stops: Consider reducing exposure when dispersion percent rank reaches the high threshold or when the stack loses ordering. Use the table’s P(win) as a context check rather than a direct signal.
Multi-asset and multi-timeframe: Defaults travel well on liquid assets from intraday to daily. Combine with higher-timeframe structure or moving averages for regime confirmation. The script itself does not fetch higher-timeframe data.
Behavior, Constraints & Performance
Repaint and confirmation: Stack markers evaluate on the live bar and can flip until close. Alert behavior follows TradingView settings. Outcome evaluation uses matured events and does not look into the future.
HTF and security: Not used. Repaint paths from higher-timeframe aggregation are avoided by design.
Resources: max bars back is two thousand. The script uses rolling sums, percent rank, gradient rendering, and a last-bar table update. Shapes and colored wicks add draw overhead.
Known limits: Lag can appear after sharp turns. Very small windows can overfit recent noise. P(win) is sensitive to sample size and priors. Dispersion normalization depends on the collection period.
Sensible Defaults & Quick Tuning
Start with the shipped defaults.
Too many flips: Increase stacking tolerance, enable midline gates, or lengthen the collection period.
Too sluggish: Reduce stacking tolerance, shorten the collection period, or relax midline gates.
Sparse samples: Extend the rolling window or increase priors to stabilize P(win).
Visual overload: Disable gradient squares or wick coloring, or raise transparency.
What this indicator is—and isn’t
This is a visualization and context layer for RSI stack regimes with simple outcome statistics. It is not a complete trading system, not predictive, and not a signal generator on its own. Use it with market structure, risk controls, and position management that fit your process.
Metadata
- Pine version: v6
- Overlay: false (price overlays are drawn via forced overlay where applicable)
- Primary outputs: Four RSI lines, consensus line, OB/OS guides, background tint, entry markers, gradient bars and wicks, statistics table
- Inputs with defaults: See Parameter Guide
- Metrics and functions used: RSI, rolling sums, percent rank, dispersion across RSI set, gradient color mapping, table rendering, alerts
- Special techniques: Ordered RSI stacking with tolerance, optional midline gating, horizon-based outcome maturation, prior-stabilized win rate, gradient normalization with gamma shaping
- Performance and constraints: max bars back two thousand, rendering of shapes and table on last bar, no higher-timeframe data, no security calls
- Recommended use-cases: Regime confirmation, momentum alignment, post-entry management with dispersion and recent outcome context
- Compatibility: Works across assets and timeframes that support RSI
- Limitations and risks: Sensitive to parameter choices and market regime changes; not a standalone strategy
- Diagnostics: Statistics table, dispersion percent rank, gradient intensity
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
ATR Regime Study [CHE] ATR Regime Study — ATR percentile regimes with clear bands, table and live label
Summary
This study classifies volatility into five regimes by converting ATR into a percentile rank over a rolling window, plotted on a standardized scale between zero and one hundred. Colored bands mark regime thresholds, while a compact table and an optional label report the current percentile and regime. The standardized scale makes symbols and timeframes easier to compare than raw ATR values. Implemented in Pine v6 as a separate pane (overlay set to false), it is a context tool to adapt tactics and risk handling to the prevailing volatility environment.
Motivation: Why this design?
Raw ATR varies with price scale and asset characteristics, which makes regime comparison inconsistent and leads to poor transfer of settings across symbols and timeframes. The core idea is to transform ATR into a percentile rank within a user-defined lookback, then map it into discrete regimes. This yields a stable, interpretable context signal that shifts slower than raw ATR while still responding to genuine volatility changes.
What’s different vs. standard approaches?
Reference baseline: Traditional ATR plots or ATR bands using fixed multipliers.
Architecture differences:
Percentile ranking of ATR within a rolling window.
Five discrete regimes with fixed thresholds at ninety, seventy, thirty, and ten.
Visual fills between thresholds plus a live table and a last-bar label.
Practical effect: You read a single normalized line between zero and one hundred with consistent thresholds. This improves cross-asset comparison and makes regime shifts obvious at a glance.
How it works (technical)
The script computes ATR over a configurable length, then converts that series to a percentile rank over a configurable number of bars. The percentile is naturally scaled and limited between zero and one hundred. That value is mapped to one of five regimes: above ninety (Extreme), between seventy and ninety (Elevated), between thirty and seventy (Normal), between ten and thirty (Calm), and below ten (Squeeze). Horizontal guide lines mark the thresholds, and fills shade the regions. A table is created once and updated on each bar to show regime definitions and highlight the current row. An optional label on the last bar displays the current percentile and regime. No higher-timeframe requests are used, so repaint risk is limited to normal live-bar fluctuation until the bar closes.
Parameter Guide
ATR length — Effect: Controls how fast ATR reacts to new ranges. Default: fourteen. Trade-offs/Tips: Increase to reduce noise in choppy markets; decrease to react faster during regime changes.
Percentile window (bars) — Effect: Number of bars used for the percentile ranking. Default: two hundred fifty-two. Trade-offs/Tips: Larger windows stabilize the percentile but slow adaptation after structural regime shifts; smaller windows adapt faster but may flip more often.
Table › Show — Effect: Toggles the regime overview table. Default: enabled. Trade-offs/Tips: Disable on constrained layouts to reduce visual clutter.
Table › Position — Effect: Anchors the table in a chart corner. Default: Top Right. Trade-offs/Tips: Choose a corner that avoids overlapping other panels or drawings.
Label › Show — Effect: Toggles a last-bar label with current percentile and regime. Default: enabled. Trade-offs/Tips: Useful for quick reads; disable if it obscures other annotations.
Reading & Interpretation
The white line shows ATR percentile between zero and one hundred. Crossing above seventy signals an elevated volatility environment; above ninety indicates event-driven extremes. Between thirty and seventy represents typical conditions. Between ten and thirty indicates calm conditions that often suit mean reversion. Below ten reflects compression, where breakout probability often increases. The colored bands visually reinforce these ranges. The table summarizes regime definitions and highlights the current state. The last-bar label mirrors the current percentile and regime for quick inspection.
Practical Workflows & Combinations
Trend following: Prefer continuation tactics when the percentile holds in the Normal or Elevated bands and structure confirms higher highs and higher lows. Consider wider stops and partial position sizing as percentile rises.
Mean reversion: Favor fades in Calm regimes within defined ranges; use structure filters and time-of-day constraints to avoid low-liquidity whipsaws.
Breakout preparation: Track compressions below ten; plan entries only with structure confirmation and risk caps, since compressions can persist.
Multi-asset/Multi-TF: Defaults travel well on daily charts. For intraday, reduce the percentile window to align with session dynamics. Combine with trend or market structure tools for confirmation.
Behavior, Constraints & Performance
Repaint/confirmation: The percentile updates during live bars and stabilizes on close; closed bars do not repaint.
security/HTF: Not used. If you add higher-timeframe aggregation externally, account for standard repaint caveats.
Resources: Declared maximum bars back is two thousand; limits for lines and labels are five hundred each. A short loop updates the table rows; arrays are used for table content only.
Known limits: Regime boundaries are fixed; assets with persistent volatility shifts may require window retuning. Low-liquidity periods and gaps can produce abrupt percentile changes. ATR is direction-agnostic and should be paired with trend or structure context.
Sensible Defaults & Quick Tuning
Start with ATR length fourteen and percentile window two hundred fifty-two on daily charts.
Too many flips: Increase ATR length or increase the percentile window.
Too sluggish: Decrease the percentile window or reduce ATR length.
Intraday noise: Keep ATR length moderate and reduce the window to a session-appropriate size; optionally hide the label to declutter.
Compressed markets: Maintain defaults but rely more on structure and volume filters before acting.
What this indicator is—and isn’t
This is a volatility regime context layer that standardizes ATR into interpretable regimes. It is not a complete trading system, not predictive, and not a stand-alone entry signal. Use it alongside structure analysis, confirmation tools, and disciplined risk management.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
Heikin Ashi Overlay SuiteHeikin Ashi Overlay Suite is designed to give traders more control and clarity when working with Heikin Ashi candles — whether you're analyzing trend strength, reducing chart noise, or simply improving your visual read of market momentum. It works by layering multiple types of HA overlays and color systems on top of your standard candlestick chart — without switching chart types. With dynamic gradient coloring, smoothing options, and a predictive line tool, this script helps you see not just what the current trend is, but how strong it is, and what it would take to reverse it.
Heikin Ashi candles help reduce noise but this script goes further by:
➡️adding color intelligence that shows trend strength using a streak counter
➡️uses smoothing logic to clean up chop and whipsaws
➡️introduces a predictive close line — a subtle but powerful guide for anticipating trend flips before they happen
Everything is configurable: colors, candle sources, overlays, predictive tools, and line styles. It’s built for traders who want visual speed, but don’t want to sacrifice signal quality.
At its core, the script offers two powerful dropdown controls:
💥HA Color Scheme (Colors Regular Candles) — Applies Heikin Ashi-derived coloring to your regular candles based on trend direction or streak strength. This gives you instant visual context without switching to a separate chart type.
💥HA Candle Overlay Mode — Overlays actual Heikin Ashi-style candles directly on top of your chart, using your preferred source:
➡️Custom HA candles using internal formula logic
➡️TradingView’s built-in Heikin Ashi source with your own colors
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
🎨 Custom + Gradient HA Coloring🎨
See trend strength at a glance:
➡️1–4 bar streaks → lighter tone
➡️5–8 bars → medium tone
➡️9+ bars → bold tone, ideal for momentum-based entries, exits, or scaling strategies
→ Choose from:
➡️Your own custom color set
➡️A simple 2-color base mode
➡️Or a 3-level gradient for progressive trend analysis (using the streak counter)
🏛️ TradingView Official Heikin Ashi Overlay
Prefer native HA candles but want your own colors?
This mode plots TradingView's Heikin Ashi source, with your personal bullish/bearish color scheme.
➡️Ensures consistency with built-in charts while still leveraging your visual style.
🌊 Smoothed Heikin Ashi Candles — Clarity in Chaos🌊
These aren’t your standard HA candles. Smoothed Heikin Ashi uses a two-step EMA process to transform chaotic price action into a cleaner, slower-moving trend structure:
🔹 First, it smooths the raw OHLC data using EMA — filtering out minor price fluctuations.
🔹 Then, it applies the Heikin Ashi transformation on top of the smoothed data.
🔹 Finally, it applies a second EMA smoothing pass to the HA values — creating ultra-smooth candles.
📈 What You See:
Trends appear more fluid and consistent.
Choppy ranges and fakeouts are visually suppressed.
Minor pullbacks within a trend are de-emphasized, helping you avoid premature exits.
🎯 Best For:
Swing traders looking to stay in positions longer.
Intraday traders dealing with volatile or noisy instruments.
Anyone who wants a "trend map" overlay without the distractions of raw price action.
✅ Reduces whipsaws
✅ Delivers high-contrast trend zones
✅ Makes reversals more visually apparent (but with a slight lag)
📍 Predictive Close Line📍
Shows where the real close must land to flip the current HA candle's color.
✅ Use it like predictive support/resistance
✅ Know if the trend is actually at risk
✅Visualize potential fakeouts or confirmation
Color-coded based on current HA direction (bullish, bearish, or neutral).
📈 Tick by tick & bar-to-bar Plots📈
Provides 2 plot types:
1)1 plot that tracks a bar tick by tick
2)another plot that tracks the close from bar to bar
For the bar to bar plot, you can choose between 2 options:
✅Full Plot — continuous line colored by HA trend
✅Recent Segments — color just the last few bars (configurable) to reduce chart clutter
✅ Customize width, number of bars, and visibility
➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖
📘 How to Use this script📘
Imagine you're watching a choppy 15-minute chart on a volatile crypto pair — price action is messy, and it’s hard to tell if a trend is forming or just noise.
Here’s how to cut through the chaos using Heikin Ashi Overlay Suite:
🔹 Step 1: Enable "Smoothed HA Candles"
Start by turning on the smoothed candles. You’ll immediately notice the noise fades, and broader directional moves become easier to follow. It's like switching from static to clean trend zones.
🧠 Why: Smoothed HA uses a double EMA process that filters out small reversals and lets larger moves stand out. Perfect for sideways or jittery charts.
🔹 Step 2: Watch the Color Gradient Build
As the smoothed candles begin to align in one direction, the gradient coloring (1–4, 5–8, 9+ streaks) gives you an at-a-glance visual of how strong the trend is.
✅ If you see 9+ same-colored candles? You’re likely in a mature trend.
✅ If it resets often? You’re in chop — consider staying out.
🔹 Step 3: Use the Predictive Close Line for Anticipation
Now here’s the edge — this line tells you where the candle would have to close to flip colors.
📉 If price is hovering just above it during a bullish run — momentum may be weakening.
📈 If price bounces off it — the trend may be strengthening.
This is excellent for confirming entries, exits, or spotting early warning signs.
🔹 Step 4: Switch Between Candle Modes as Needed
You can flip between:
✅ Custom HA: Gradient candles with your colors
✅ TradingView HA: The official source with your styling
✅ None: Just color regular candles using the HA logic
Use what fits your style — everything is modular.
🔹 Step 5: Tune It to Your Chart
Lastly, tweak streak thresholds (currently only can do this within the source code), smoothing lengths, and line styles to match your timeframe and strategy.
🎯 Tailor The Settings to Fit Your Trading Style🎯
🔹 🧪 Scalper (1–5 min charts)
If you’re trading fast intraday moves, you want quicker responsiveness and less lag.
Try these settings:
🔸Smoothing Lengths: Use lower values (e.g. len = 3, len2 = 5)
🔸Candle Mode: Use Custom HA or TV’s HA for real-time color flips
🔸Predictive Close Line: Great for ultra-fast anticipation of color reversals
🔸Line Mode: Use Recent Segments mode to track short bursts of trend
🔸Colors: Use high-contrast, opaque colors for clarity
✅ These settings help you catch micro-trends and flip signals faster, while still filtering out the worst of the noise.
🔹 🧪 Swing Trader (30m–4h charts and beyond)
If you’re looking for multi-hour or multi-day trend confirmation, prioritize clarity and staying in moves longer.
Recommended setup:
🔸Smoothing Lengths: Medium to high values (e.g. len = 8, len2 = 21)
🔸Candle Mode: Use Smoothed HA Candles to block out intrabar chop
🔸Gradient Colors: Enable to visualize trend maturity and strength
🔸Predictive Close Line: Helps confirm trend continuation or spot early reversals
🔸Line Mode: Use Full Plot Line for clean HA-based trend tracking
✅ These settings give you a calm, clean view of the bigger picture — ideal for holding positions longer and avoiding early exits.
🔧 This script isn’t just a chart overlay — it’s a visual trend engine.🔧
Ideal For:
🔶 Trend-followers who want clean, color-coded confirmation
🔶 Reversal traders spotting exhaustion via predictive flips
🔶 Scalpers filtering noise with lighter smoothing
🔶 Swing traders using smoothed visuals to hold longer
📌 Final Note
Heikin Ashi Overlay Pro is designed to help you see momentum, trend shifts, and market structure with greater clarity — not to predict price on its own. For best results:
✔️ Combine with support/resistance, moving averages, or price action patterns
✔️ Use Predictive Close as a confirmation tool, not a signal generator
✔️ Pair gradient colors with structure to gauge trend maturity
✔️ Always zoom out and check higher timeframes for context
🧠 Use this as part of a layered approach — not a standalone system.
🙏 Credits🙏
⚡HA logic based on SimpleCryptoLife
⚡Smoothed HA concept adapted from a script by Jackvmk
💡💡💡Turn logic into clarity. Structure into trades. And uncertainty into confidence.💡💡💡
Sentinel 5 — OHL daybreak signals [KedArc Quant]Overview
Sentinel 5 plots the first-bar high/low of each trading session and gives clean, rules-based signals in two ways:
1) OHL Setups at the close of the first bar (Open equals/near High for potential short; Open equals/near Low for potential long).
2) Breakout Signals later in the session when price breaks the first-bar High/Low, with optional body/penetration filters.
Basic workflow
1. Wait for the first session bar to finish.
*If O≈H (optionally by proximity) → short setup. •
*If O≈L → long setup. • If neither happens, optionally allow later breakouts.
2. Optional: Act only on breakouts that penetrate a minimum % of that bar’s range/body.
3. Skip the day automatically if the first bar is abnormally large (marubozu-like / extreme ATR / outsized vs yesterday).
Signals & Markers
Markers on the chart:
▲ O=L (exact) / O near L (proximity) – long setup at first-bar close.
▼ O=H (exact) / O near H (proximity) – short setup at first-bar close.
▲ Breakout Long – later bar breaks above first-bar High meeting your penetration rule.
▼ Breakout Short – later bar breaks below first-bar Low meeting your penetration rule.
J12Matic Builder by galgoomA flexible Renko/tick strategy that lets you choose between two entry engines (Multi-Source 3-way or QBand+Moneyball), with a unified trailing/TP exit engine, NY-time trading windows with auto-flatten, daily profit/loss and trade-count limits (HALT mode), and clean webhook routing using {{strategy.order.alert_message}}.
Highlights
Two entry engines
Multi-Source (3): up to three long/short sources with Single / Dual / Triple logic and optional lookback.
QBand + Moneyball: Gate → Trigger workflow with timing windows, OR/AND trigger modes, per-window caps, optional same-bar fire.
Unified exit engine: Trailing by Bricks or Ticks, plus optional static TP/SL.
Session control (NY time): Evening / Overnight / NY Session windows; auto-flatten at end of any enabled window.
Day controls: Profit/Loss (USD) and Trade-count limits. When hit, strategy HALTS new entries, shows an on-chart label/background.
Alert routing designed for webhooks: Every order sets alert_message= so you can run alerts with:
Condition: this strategy
Notify on: Order fills only
Message: {{strategy.order.alert_message}}
Default JSONs or Custom payloads: If a Custom field is blank, a sensible default JSON is sent. Fill a field to override.
How to set up alerts (the 15-second version)
Create a TradingView alert with this strategy as Condition.
Notify on: Order fills only.
Message: {{strategy.order.alert_message}} (exactly).
If you want your own payloads, paste them into Inputs → 08) Custom Alert Payloads.
Leave blank → the strategy sends a default JSON.
Fill in → your text is sent as-is.
Note: Anything you type into the alert dialog’s Message box is ignored except the {{strategy.order.alert_message}} token, which forwards the payload supplied by the strategy at order time.
Publishing notes / best practices
Renko users: Make sure “Renko Brick Size” in Inputs matches your chart’s brick size exactly.
Ticks vs Bricks: Exit distances switch instantly when you toggle Exit Units.
Same-bar flips: If enabled, a new opposite signal will first close the open trade (with its exit payload), then enter the new side.
HALT mode: When day profit/loss limit or trade-count limit triggers, new entries are blocked for the rest of the session day. You’ll see a label and a soft background tint.
Session end flatten: Auto-closes positions at window ends; these exits use the “End of Session Window Exit” payload.
Bar magnifier: Strategy is configured for on-close execution; you can enable Bar Magnifier in Properties if needed.
Default JSONs (used when a Custom field is empty)
Open: {"event":"open","side":"long|short","symbol":""}
Close: {"event":"close","side":"long|short|flat","reason":"tp|sl|flip|session|limit_profit|limit_loss","symbol":""}
You can paste any text/JSON into the Custom fields; it will be forwarded as-is when that event occurs.
Input sections — user guide
01) Entries & Signals
Entry Logic: Choose Multi-Source (3) or QBand + Moneyball (pick one).
Enable Long/Short Signals: Master on/off switches for entering long/short.
Flip on opposite signal: If enabled, a new opposite signal will close the current position first, then open the other side.
Signal Logic (Multi-Source):
Single: any 1 of the 3 sources > 0
Dual: Source1 AND Source2 > 0
Triple (default): 1 AND 2 AND 3 > 0
Long/Short Signal Sources 1–3: Provide up to three series (often indicators). A positive value (> 0) is treated as a “pulse”.
Use Lookback: Keeps a source “true” for N bars after it pulses (helps catch late triggers).
Long/Short Lookback (bars): How many bars to remember that pulse.
01b) QBands + Moneyball (Gate -> Trigger)
Allow same-bar Gate->Trigger: If ON, a trigger can fire on the same bar as the gate pulse.
Trigger must fire within N bars after Gate: Size of the gate window (in bars).
Max signals per window (0 = unlimited): Cap the number of entries allowed while a gate window is open.
Buy/Sell Source 1 – Gate: Gate pulse sources that open the buy/sell window (often a regime/zone, e.g., QBands bull/bear).
Trigger Pulse Mode (Buy/Sell): How to detect a trigger pulse from the trigger sources (Change / Appear / Rise>0 / Fall<0).
Trigger A/B sources + Extend Bars: Primary/secondary triggers plus optional extension to persist their pulse for N bars.
Trigger Mode: Pick S2 only, S3 only, S2 OR S3, or S2 AND S3. AND mode remembers both pulses inside the window before firing.
02) Exit Units (Trailing/TP)
Exit Units: Choose Bricks (Renko) or Ticks. All distances below switch accordingly.
03) Tick-based Trailing / Stops (active when Exit Units = Ticks)
Initial SL (ticks): Starting stop distance from entry.
Start Trailing After (ticks): Start trailing once price moves this far in your favor.
Trailing Distance (ticks): Offset of the trailing stop from peak/trough once trailing begins.
Take Profit (ticks): Optional static TP distance.
Stop Loss (ticks): Optional static SL distance (overrides trailing if enabled).
04) Brick-based Trailing / Stops (active when Exit Units = Bricks)
Renko Brick Size: Must match your chart’s brick size.
Initial SL / Start Trailing After / Trailing Distance (bricks): Same definitions as tick mode, measured in bricks.
Take Profit / Stop Loss (bricks): Optional static distances.
05) TP / SL Switch
Enable Static Take Profit: If ON, closes the trade at the fixed TP distance.
Enable Static Stop Loss (Overrides Trailing): If ON, trailing is disabled and a fixed SL is used.
06) Trading Windows (NY time)
Use Trading Windows: Master toggle for all windows.
Evening / Overnight / NY Session: Define each session in NY time.
Flatten at End of : Auto-close any open position when a window ends (sends the Session Exit payload).
07) Day Controls & Limits
Enable Profit Limits / Profit Limit (Dollars): When daily net PnL ≥ limit → auto-flatten and HALT.
Enable Loss Limits / Loss Limit (Dollars): When daily net PnL ≤ −limit → auto-flatten and HALT.
Enable Trade Count Limits / Number of Trades Allowed: After N entries, HALT new entries (does not auto-flatten).
On-chart HUD: A label and soft background tint appear when HALTED; a compact status table shows Day PnL, trade count, and mode.
08) Custom Alert Payloads (used as strategy.order.alert_message)
Long/Short Entry: Payload sent on entries (if blank, a default open JSON is sent).
Regular Long/Short Exit: Payload sent on closes from SL/TP/flip (if blank, a default close JSON is sent).
End of Session Window Exit: Payload sent when any enabled window ends and positions are flattened.
Profit/Loss/Trade Limit Close: Payload sent when daily profit/loss limit causes auto-flatten.
Tip: Any tokens you include here are forwarded “as is”. If your downstream expects variables, do the substitution on the receiver side.
Known limitations
No bracket orders from Pine: This strategy doesn’t create OCO/attached brackets on the broker; it simulates exits with strategy logic and forwards your payloads for external automation.
alert_message is per order only: Alerts fire on order events. General status pings aren’t sent unless you wire a separate indicator/alert.
Renko specifics: Backtests on synthetic Renko can differ from live execution. Always forward-test on your instrument and settings.
Quick checklist before you publish
✅ Brick size in Inputs matches your Renko chart
✅ Exit Units set to Bricks or Ticks as you intend
✅ Day limits/Windows toggled as you want
✅ Custom payloads filled (or leave blank to use defaults)
✅ Your alert uses Order fills only + {{strategy.order.alert_message}}
[Top] Simple ATR TP/SLSimple TP/SL from ATR (Locked per Bar) - Advanced Position Management Tool
What This Indicator Does:
Automatically calculates and displays Take Profit (TP) and Stop Loss (SL) levels based on Average True Range (ATR)
Locks ATR values and direction signals at the start of each bar to prevent repainting and provide consistent levels
Offers multiple direction detection modes including real-time candle-based positioning for dynamic trading approaches
Displays entry, TP, and SL levels as clean horizontal lines that extend from the current bar
Original Features That Make This Script Unique:
Bar-Locked ATR System: ATR values are captured and frozen at bar open, ensuring levels remain stable throughout the bar's progression
Multi-Modal Direction Detection: Four distinct modes for determining TP/SL positioning - Trend Following (EMA-based), Bullish Only, Bearish Only, and real-time Candle Based
Real-Time Candle Flipping: In Candle Based mode, TP/SL levels flip immediately when the current candle changes from bullish to bearish or vice versa
Persistent Line Management: Uses efficient line object management to prevent ghost lines and maintain clean visual presentation
Flexible Base Price Selection: Choose between Open (static), Close (dynamic), or midpoint (H+L)/2 for entry level calculation
How The Algorithm Works:
ATR Calculation: Captures ATR value at each bar open using specified length parameter, maintaining consistency throughout the bar
Direction Determination: Uses different methods based on selected mode - EMA crossover for trend following, or real-time candle color for dynamic positioning
Level Calculation: TP level = Base Price + (Direction × TP Multiplier × ATR), SL level = Base Price - (Direction × SL Multiplier × ATR)
Visual Management: Creates persistent line objects once, then updates their positions every bar for optimal performance
Direction Modes Explained:
Trend Following: Uses 5-period and 12-period EMA relationship to determine trend direction (locked at bar open)
Bullish Only: Always places TP above and SL below entry (traditional long setup)
Bearish Only: Always places TP below and SL above entry (traditional short setup)
Candle Based: Dynamically adjusts based on current candle direction - flips in real-time as candle develops
Key Input Parameters:
ATR Length: Period for ATR calculation (default 14) - longer periods provide smoother volatility measurement
TP Multiplier: Take profit distance as multiple of ATR (default 1.0) - higher values target larger profits
SL Multiplier: Stop loss distance as multiple of ATR (default 1.0) - higher values allow more room for price movement
Base Price: Reference point for level calculations - Open for static entry, Close for dynamic tracking
Direction Mode: Method for determining whether TP goes above or below entry level
How To Use This Indicator:
For Position Sizing: Use the displayed SL distance to calculate appropriate position size based on your risk tolerance
For Entry Timing: Wait for price to approach the entry level before taking positions
For Risk Management: Set your actual stop loss orders at or near the displayed SL level
For Profit Taking: Use the TP level as initial profit target, consider scaling out at this level
Mode Selection: Choose Candle Based for scalping and quick reversals, Trend Following for swing trading
Visual Style Customization:
Line Colors: Customize TP line color (default teal) and SL line color (default orange) for easy identification
Line Widths: Adjust TP/SL line thickness (1-5) and entry line thickness (1-3) for visibility preferences
Clean Display: Lines extend 3 bars forward from current bar and update position dynamically
Best Practices:
Use on clean charts without multiple overlapping indicators for clearest visual interpretation
Combine with volume analysis and key support/resistance levels for enhanced decision making
Adjust ATR length based on your trading timeframe - shorter for scalping, longer for position trading
Test different TP/SL multipliers based on the volatility characteristics of your chosen instruments
Consider using Trend Following mode during strong trending periods and Candle Based during ranging markets
Prime NumbersPrime Numbers highlights prime numbers (no surprise there 😅), tokens and the recent "active" feature in "input".
🔸 CONCEPTS
🔹 What are Prime Numbers?
A prime number (or a prime) is a natural number greater than 1 that is not a product of two smaller natural numbers.
Wikipedia: Prime number
🔹 Prime Factorization
The fundamental theorem of arithmetic states that every integer larger than 1 can be written as a product of one or more primes. More strongly, this product is unique in the sense that any two prime factorizations of the same number will have the same number of copies of the same primes, although their ordering may differ. So, although there are many different ways of finding a factorization using an integer factorization algorithm, they all must produce the same result. Primes can thus be considered the "basic building blocks" of the natural numbers.
Wikipedia: Fundamental theorem of arithmetic
Math Is Fun: Prime Factorization
We divide a given number by Prime Numbers until only Primes remain.
Example:
24 / 2 = 12 | 24 / 3 = 8
12 / 3 = 4 | 8 / 2 = 4
4 / 2 = 2 | 4 / 2 = 2
|
24 = 2 x 3 x 2 | 24 = 3 x 2 x 2
or | or
24 = 2² x 3 | 24 = 2² x 3
In other words, every natural/integer number above 1 has a unique representation as a product of prime numbers, no matter how the number is divided. Only the order can change, but the factors (the basic elements) are always the same.
🔸 USAGE
The Prime Numbers publication contains two use cases:
Prime Factorization: performed on "close" prices, or a manual chosen number.
List Prime Numbers: shows a list of Prime Numbers.
The other two options are discussed in the DETAILS chapter:
Prime Factorization Without Arrays
Find Prime Numbers
🔹 Prime Factorization
Users can choose to perform Prime Factorization on close prices or a manually given number.
❗️ Note that this option only applies to close prices above 1, which are also rounded since Prime Factorization can only be performed on natural (integer) numbers above 1.
In the image below, the left example shows Prime Factorization performed on each close price for the latest 50 bars (which is set with "Run script only on 'Last x Bars'" -> 50).
The right example shows Prime Factorization performed on a manually given number, in this case "1,340,011". This is done only on the last bar.
When the "Source" option "close price" is chosen, one can toggle "Also current price", where both the historical and the latest current price are factored. If disabled, only historical prices are factored.
Note that, depending on the chosen options, only applicable settings are available, due to a recent feature, namely the parameter "active" in settings.
Setting the "Source" option to "Manual - Limited" will factorize any given number between 1 and 1,340,011, the latter being the highest value in the available arrays with primes.
Setting to "Manual - Not Limited" enables the user to enter a higher number. If all factors of the manual entered number are in the 1 - 1,340,011 range, these factors will be shown; however, if a factor is higher than 1,340,011, the calculation will stop, after which a warning is shown:
The calculated factors are displayed as a label where identical factors are simplified with an exponent notation in superscript.
For example 2 x 2 x 2 x 5 x 7 x 7 will be noted as 2³ x 5 x 7²
🔹 List Prime Numbers
The "List Prime Numbers" option enables users to enter a number, where the first found Prime Number is shown, together with the next x Prime Numbers ("Amount", max. 200)
The highest shown Prime Number is 1,340,011.
One can set the number of shown columns to customize the displayed numbers ("Max. columns", max. 20).
🔸 DETAILS
The Prime Numbers publication consists out of 4 parts:
Prime Factorization Without Arrays
Prime Factorization
List Prime Numbers
Find Prime Numbers
The usage of "Prime Factorization" and "List Prime Numbers" is explained above.
🔹 Prime Factorization Without Arrays
This option is only there to highlight a hurdle while performing Prime Factorization.
The basic method of Prime Factorization is to divide the base number by 2, 3, ... until the result is an integer number. Continue until the remaining number and its factors are all primes.
The division should be done by primes, but then you need to know which one is a prime.
In practice, one performs a loop from 2 to the base number.
Example:
Base_number = input.int(24)
arr = array.new()
n = Base_number
go = true
while go
for i = 2 to n
if n % i == 0
if n / i == 1
go := false
arr.push(i)
label.new(bar_index, high, str.tostring(arr))
else
arr.push(i)
n /= i
break
Small numbers won't cause issues, but when performing the calculations on, for example, 124,001 and a timeframe of, for example, 1 hour, the script will struggle and finally give a runtime error.
How to solve this?
If we use an array with only primes, we need fewer calculations since if we divide by a non-prime number, we have to divide further until all factors are primes.
I've filled arrays with prime numbers and made libraries of them. (see chapter "Find Prime Numbers" to know how these primes were found).
🔹 Tokens
A hurdle was to fill the libraries with as many prime numbers as possible.
Initially, the maximum token limit of a library was 80K.
Very recently, that limit was lifted to 100K. Kudos to the TradingView developers!
What are tokens?
Tokens are the smallest elements of a program that are meaningful to the compiler. They are also known as the fundamental building blocks of the program.
I have included a code block below the publication code (// - - - Educational (2) - - - ) which, if copied and made to a library, will contain exactly 100K tokens.
Adding more exported functions will throw a "too many tokens" error when saving the library. Subtracting 100K from the shown amount of tokens gives you the amount of used tokens for that particular function.
In that way, one can experiment with the impact of each code addition in terms of tokens.
For example adding the following code in the library:
export a() => a = array.from(1) will result in a 100,041 tokens error, in other words (100,041 - 100,000) that functions contains 41 tokens.
Some more examples, some are straightforward, others are not )
// adding these lines in one of the arrays results in x tokens
, 1 // 2 tokens
, 111, 111, 111 // 12 tokens
, 1111 // 5 tokens
, 111111111 // 10 tokens
, 1111111111111111111 // 20 tokens
, 1234567890123456789 // 20 tokens
, 1111111111111111111 + 1 // 20 tokens
, 1111111111111111111 + 8 // 20 tokens
, 1111111111111111111 + 9 // 20 tokens
, 1111111111111111111 * 1 // 20 tokens
, 1111111111111111111 * 9 // 21 tokens
, 9999999999999999999 // 21 tokens
, 1111111111111111111 * 10 // 21 tokens
, 11111111111111111110 // 21 tokens
//adding these functions to the library results in x tokens
export f() => 1 // 4 tokens
export f() => v = 1 // 4 tokens
export f() => var v = 1 // 4 tokens
export f() => var v = 1, v // 4 tokens
//adding these functions to the library results in x tokens
export a() => const arraya = array.from(1) // 42 tokens
export a() => arraya = array.from(1) // 42 tokens
export a() => a = array.from(1) // 41 tokens
export a() => array.from(1) // 32 tokens
export a() => a = array.new() // 44 tokens
export a() => a = array.new(), a.push(1) // 56 tokens
What if we could lower the amount of tokens, so we can export more Prime Numbers?
Look at this example:
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
Eight numbers contain the same number 8291.
If we make a function that removes recurrent values, we get fewer tokens!
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
//is transformed to:
829111, 21, 23, 51, 59, 77, 87, 93
The code block below the publication code (// - - - Educational (1) - - - ) shows how these values were reduced. With each step of 100, only the first Prime Number is shown fully.
This function could be enhanced even more to reduce recurrent thousands, tens of thousands, etc.
Using this technique enables us to export more Prime Numbers. The number of necessary libraries was reduced to half or less.
The reduced Prime Numbers are restored using the restoreValues() function, found in the library fikira/Primes_4.
🔹 Find Prime Numbers
This function is merely added to show how I filled arrays with Prime Numbers, which were, in turn, added to libraries (after reduction of recurrent values).
To know whether a number is a Prime Number, we divide the given number by values of the Primes array (Primes 2 -> max. 1,340,011). Once the division results in an integer, where the divisor is smaller than the dividend, the calculation stops since the given number is not a Prime.
When we perform these calculations in a loop, we can check whether a series of numbers is a Prime or not. Each time a number is proven not to be a Prime, the loop starts again with a higher number. Once all Primes of the array are used without the result being an integer, we have found a new Prime Number, which is added to the array.
Doing such calculations on one bar will result in a runtime error.
To solve this, the findPrimeNumbers() function remembers the index of the array. Once a limit has been reached on 1 bar (for example, the number of iterations), calculations will stop on that bar and restart on the next bar.
This spreads the workload over several bars, making it possible to continue these calculations without a runtime error.
The result is placed in log.info() , which can be copied and pasted into a hardcoded array of Prime Number values.
These settings adjust the amount of workload per bar:
Max Size: maximum size of Primes array.
Max Bars Runtime: maximum amount of bars where the function is called.
Max Numbers To Process Per Bar: maximum numbers to check on each bar, whether they are Prime Numbers.
Max Iterations Per Bar: maximum loop calculations per bar.
🔹 The End
❗️ The code and description is written without the help of an LLM, I've only used Grammarly to improve my description (without AI :) )
Return Volatility (σ) — auto-annualized [v6]Overview
This indicator calculates and visualizes the return-based volatility (standard deviation) of any asset, automatically adjusting for your chart's timeframe to provide both absolute and annualized volatility values.
It’s designed for traders who want to filter trades, adjust position sizing, and detect volatility events based on statistically significant changes in market activity.
Key Features
Absolute Volatility (abs σ%) – Standard deviation of returns for the current timeframe (e.g., 1H, 4H, 1D).
Annualized Volatility (ann σ%) – Converts abs σ% into an annualized figure for easier cross-timeframe and cross-asset comparison.
Relative Volatility (rel σ) – Ratio of current volatility to the long-term average (default: 120 periods).
Z-Score – Number of standard deviations the current volatility is above or below its historical average.
Auto-Timeframe Adjustment – Detects your chart’s bar size (seconds per bar) and calculates bars/year automatically for crypto’s 24/7 market.
Highlight Mode – Optional yellow background when volatility exceeds set thresholds (rel σ ≥ threshold OR z-score ≥ threshold).
Alert Conditions – Alerts trigger when relative volatility or z-score exceed defined limits.
How It Works
Return Calculation
Log returns: ln(Pt / Pt-1) (default)
or Simple returns: (Pt / Pt-1) – 1
Volatility Measurement
Standard deviation of returns over the lookback period N (default: 20 bars).
Absolute volatility = σ × 100 (% per bar).
Annualization
Uses: σₐₙₙ = σ × √(bars/year) × 100 (%)
Bars/year auto-calculated based on timeframe:
1H = 8,760 bars/year
4H ≈ 2,190 bars/year
1D = 365 bars/year
Relative and Statistical Context
Relative σ = Current σ / Historical average σ (baseLen, default: 120)
Z-score = (Current σ – Historical average σ) / Std. dev. of σ over baseLen
Trading Applications
Volatility Filter – Only allow trade entries when volatility exceeds historical norms (trend traders often benefit from this).
Risk Management – Reduce position size during high volatility spikes to manage risk; increase size in low-volatility trending environments.
Market Scanning – Identify assets with the highest relative volatility for momentum or breakout strategies.
Event Detection – Highlight significant volatility surges that may precede large moves.
Suggested Settings
Lookback (N): 20 bars for short/medium-term trading.
Base Length (M): 120 bars to establish long-term volatility baseline.
Relative Threshold: 1.5× baseline σ.
Z-score Threshold: ≥ 2.0 for statistically significant volatility shifts.
Use Log Returns: Recommended for more consistent scaling across prices.
Notes & Limitations
Volatility measures movement magnitude, not direction. Combine with trend or momentum filters for directional bias.
Very low volatility may still produce false breakouts; combine with volume and market structure analysis.
Crypto markets trade 24/7 — annualization assumes no market closures; adjust for other asset classes if needed.
💡 Best Practice: Use this indicator as a pre-trade filter for breakout or trend-following strategies, or as a risk control overlay in mean-reversion systems.
Aggregated VolumeHow to Read the “Aggregated Volume” Signal
This indicator combines normalized volume, short-term volume bursts, pivot levels, VWAP, and a 200-period EMA to give you a multi-dimensional view of trading activity. Here’s how to interpret each component and synthesize them into actionable insights.
1. Custom Volume Signal (vSignal)
• Calculation
• vSignal = Sum of over bars, divided by the current price.
• A rising vSignal means more volume is being traded per unit of price, signaling growing interest relative to price level.
• Plot styling
• Bars are lime when (bullish volume days)
• Bars are orange when (bearish volume days)
How to read it
• Trend confirmation: Increasing lime bars alongside rising price suggests buyers in control.
• Warning sign: Rising orange bars on a down move indicate accelerating selling pressure.
• Divergence:
• Price making new highs while vSignal stalls or drops → potential top.
• Price making new lows while vSignal holds → potential bottom.
2. Short-Term Volume Bursts
Three semi-transparent histograms show how much the last 2, 5, and 10-bar raw volumes exceed (or fall below) the current vSignal:
• Blue = vol(2) – vSignal
• Green = vol(5) – vSignal
• Red = vol(10) – vSignal
If a colored bar sits above zero, that lookback’s volume is surging relative to the longer-term average (vSignal).
How to read it
• Clustered bursts:
• Blue + Green + Red above zero → strong, broad-based volume surge.
• Great for confirming breakouts and shakeouts.
• Isolated burst:
• Only Blue (> 0) on a small range bar → might be a false breakout or intrabar squeeze.
• Only Red (> 0) on a wide range → institutional involvement; act with caution.
3. Pivot Volume Levels (v & t)
• Every 21 bars, the script finds the highest and lowest vSignal values and plots them as shaded price levels:
• Magenta area = recent vSignal high (resistance)
• Cyan area = recent vSignal low (support)
How to read it
• Rejection/Break:
• Price approaches magenta zone and stalls → sellers defending that volume high.
• Break above magenta with high vSignal → likely sustained rally.
• Support flip:
• Cyan zone hold → buyers stepping in at heavy-volume lows.
• Break below cyan with rising vSignal → bearish conviction.
4. Midline Cross (Volume Equilibrium)
• A 10-bar SMA of
• Drawn as a faint white cross on price
How to read it
• Above midline → overall volume bias is skewed bullish.
• Below midline → bearish volume bias.
Crossovers of vSignal through this midline can signal shifts in underlying conviction.
5. VWAP & 200-Period EMA Overlays
• VWAP (transparent red if above price, green if below)
• EMA(200) plotted as aqua circles
How to read them
• VWAP tells you the intraday “value area.”
• Price above VWAP + rising vSignal = intraday buyers in charge.
• Price below VWAP + rising vSignal = aggressive sellers.
• EMA(200) gives you the longer-term trend.
• Above EMA200 = bullish regime
• Below EMA200 = bearish regime
6. Putting It All Together: Example Scenarios
1. Bullish Entry
• Price > EMA200 & VWAP is green
• vSignal rising in lime
• All three short-term bursts above zero
• Price near or breaking the magenta pivot with volume confirmation
2. Bearish Entry
• Price < EMA200 & VWAP is red
• vSignal rising in orange
• Two-bar burst (blue) spikes on a down bar
• Price failing at magenta pivot or breaking cyan support
3. Divergence Play
• Price makes new high, but vSignal peaks lower than last high → look for a reversal.
• Price drops to new low, but vSignal stays above its last low → prepare for a bounce.
By combining these layers—normalized volume, burst indicators, pivot levels, VWAP, and EMA—you get a clear map of where volume is clustering, which lets you anticipate support/resistance, gauge real interest, and spot potential reversals or breakouts with greater confidence.
Range Breakout [sgbpulse]Range Breakout
1. Overview
The "Range Breakout " indicator is a powerful tool designed to identify and visually display price ranges on your chart using pivot points. It dynamically draws two distinct boxes – an External Range and an Internal Range – helping traders pinpoint potential support and resistance zones. Beyond its visual representation, the indicator offers a comprehensive set of 12 unique breakout alerts, providing real-time notifications for significant price movements outside these defined ranges. Additionally, it integrates RSI and MFI metrics for momentum confirmation.
2. How It Works
The indicator operates by identifying pivot points based on user-defined "left" and "right" bar lengths. A high pivot is a bar with a specified number of lower highs both to its left and right, and similarly for a low pivot.
External Range: Calculated using longer pivot lengths (default: 15 bars left, 6 bars right). This range represents broader, more significant price consolidation areas.
Internal Range: Calculated using shorter pivot lengths (default: 4 bars left, 3 bars right). This range captures tighter, more immediate price consolidations within the broader trend.
The External Range will always be greater than or equal to the Internal Range, as it's based on a wider historical context. Both ranges are displayed as transparent boxes on your chart, dynamically adjusting as new pivots are formed.
3. Key Features and Settings
Customizable Pivot Lengths:
External Range (Left/Right Bars): Adjust sensitivity for identifying the broader price range. Longer lengths lead to more stable, but less frequent, range updates.
Internal Range (Left/Right Bars): Adjust sensitivity for the tighter, more immediate price range.
Tool Tips: Minimum 6 bars for the External Range, and minimum 2 bars for the Internal Range.
Customizable Range Colors: Easily change the background colors of the External and Internal Range boxes to match your chart's aesthetic.
Dynamic Range Display: The indicator automatically updates the range boxes as new pivot highs and lows are formed, always presenting the most current valid ranges.
RSI / MFI Settings:
Timeframe Source: Select the timeframe for RSI and MFI calculation.
- Chart: Calculation based on the current chart timeframe.
- Daily: Always calculated based on the daily ("D") timeframe, even if the chart is on a lower timeframe.
RSI Length: Period length for RSI calculation (default: 14).
RSI Overbought Level: Overbought level for RSI (default: 70.0).
RSI Oversold Level: Oversold level for RSI (default: 30.0).
MFI Length: Period length for MFI calculation (default: 14).
MFI Overbought Level: Overbought level for MFI (default: 80.0).
MFI Oversold Level: Oversold level for MFI (default: 20.0).
4. Synergy of Ranges & Breakout Strength
The interaction between the External and Internal Ranges provides deep insights into price movement and breakout strength:
Immediate Direction: The movement of the Internal Range (up or down) indicates the short-term directional bias within the broader framework of the External Range.
Strength Confirmation: A breakout of the External Range, followed by a breakout of the Internal Range, confirms the strength of the move and increases confidence in the breakout.
Strong Momentum ("Leaving" Ranges Behind): When price breaks out with exceptionally strong momentum, it continues to move aggressively and does not immediately form new pivots. In such situations, the existing ranges (External and Internal) remain in place while the candles "leave them behind." A "Full Candle" breakout, where the entire candle moves past both ranges, indicates a particularly powerful and decisive move.
Momentum (RSI / MFI) as Confirmation:
- RSI (Relative Strength Index): Measures the speed and change of price movements. Extreme values (above 70 or below 30) indicate overbought/oversold conditions respectively, confirming strong momentum in a breakout.
- MFI (Money Flow Index): Similar to RSI but incorporates volume. Extreme values (above 80 or below 20) indicate strong money flow in/out, reinforcing breakout confirmation.
- Importance of Confirmation: If a breakout occurs but momentum indicators do not confirm it (for example, an upside breakout while RSI is declining), this could signal weakness in the move and the risk of a false breakout (Fakeout).
5. Visuals
The indicator provides clear visual representations on the chart:
Range Boxes:
Two dynamic boxes are drawn on the chart: one for the External Range and one for the Internal Range.
These boxes update continuously, displaying the current range boundaries based on the latest pivots. They provide an immediate visual indication of support and resistance levels.
RSI/MFI Status Labels:
Small text labels appear to the right of the current bar, vertically centered.
They display the status of RSI and MFI: RSI OB (Overbought), RSI OS (Oversold), MFI OB, MFI OS, along with the exact value.
Important: The labels remain on the chart as long as the condition holds (indicator is above/below the level), unlike alerts which mark a singular crossover event.
Plotting of Key Values:
The indicator plots six invisible series on the chart, primarily to allow the user to view the exact numerical values of:
- The upper and lower bounds of the External Range (External High, External Low).
- The upper and lower bounds of the Internal Range (Internal High, Internal Low).
- The calculated RSI and MFI values (RSI, MFI).
These values are accessible for viewing through TradingView's Data Window and also via the Status Line when hovering over the relevant candle. This enables more precise quantitative analysis of range levels and momentum.
6. Comprehensive Breakout Alerts
The "Range Breakout " indicator provides 12 distinct alert conditions for breakouts, allowing you to select the required level of confirmation for each alert. All alerts are triggered only upon a fully confirmed bar close (barstate.isconfirmed) to minimize false signals and ensure reliability.
All breakout alerts are configured to detect a Crossover/Crossunder of the levels, meaning a specific event where the price moves from one side of the range to the other.
External Range Breakout UP
- Close: Price closes above the External Range.
- Real Body: The entire "real body" of the candle (min of open/close prices) closes above the External Range.
- Full Candle: The entire candle (the lowest point of the candle) closes above the External Range.
External Range Breakout DOWN
- Close: Price closes below the External Range.
- Real Body: The entire "real body" of the candle (max of open/close prices) closes below the External Range.
- Full Candle: The entire candle (the highest point of the candle) closes below the External Range.
Internal Range Breakout UP
- Close: Price closes above the Internal Range.
- Real Body: The "real body" of the candle closes above the Internal Range.
- Full Candle: The entire candle closes above the Internal Range.
Internal Range Breakout DOWN
- Close: Price closes below the Internal Range.
- Real Body: The "real body" of the candle closes below the Internal Range.
- Full Candle: The entire candle closes below the Internal Range.
7. Ideal Use Cases
This indicator is ideal for traders who:
Want to clearly identify and monitor price consolidation zones.
Seek confirmation for breakout strategies across various timeframes.
Require reliable and automated alerts for potential entry or exit points based on range expansion.
8. Complementary Indicator
For even more comprehensive market analysis, we highly recommend using this indicator in conjunction with Market Structure Support & Resistance External/Internal & BoS .
This powerful complementary indicator automatically and accurately identifies significant support and resistance levels by locating high and low pivot points, as well as key Pre-Market High/Low levels. Its strength lies in its dynamic adaptability to any timeframe and asset, providing precise and relevant real-time levels while maintaining a clean chart. It also identifies Break of Structure (BoS) to signal potential trend changes or continuations.
Using both indicators together provides a robust framework for identifying defined ranges and potential trend shifts, enabling more informed trading decisions.
View Market Structure Support & Resistance External/Internal & BoS Indicator
9. Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
