Silver Bullet 5 minutes Box - By KaVeHThis indicator plots high-low range boxes based on selected intraday time windows on the 5-minute chart. It's inspired by the "Silver Bullet" trading concept, highlighting key liquidity grabs and volatility pockets at predefined times. It helps traders visually identify potential smart money trading windows during the New York session and other time anchors.
⚠️ This script only works on the 5-minute chart.
📦 Main Features:
⏰ Customizable Time Boxes:
Define up to 4 separate time windows per day:
3:00 AM – 3:05 AM (New York time) (Box 1)
10:00 AM – 10:05 AM (New York time) (Box 2)
2:00 PM – 2:05 PM (New York time) (Box 3)
8:00 PM – 8:05 PM (New York time) (Box 4)
🎨 Color and Visibility Control:
Each box can be independently toggled and colored for visual distinction.
🕔 New York Time Based:
All timestamps are automatically adjusted to New York Time, aligning with institutional market behavior.
📉 Post-Box Projection:
After each time window closes, a box extends forward 6 hours (72 bars on a 5-minute chart) to highlight the range.
💡 Use Case:
These boxes are best used to:
Detect liquidity sweeps.
Mark potential entry or exit zones.
Track price behavior after specific time-based events.
For example, the 10 AM box is often used to identify setups just after the NYSE open and into the first hour of volatility.
⚠️ TradingView Compliance Notes:
This script is original and does not replicate or resell premium/paid indicators.
All logic is coded from scratch by kaveh_mirmousavi, using public concepts from ICT/Smart Money Trading.
Fully complies with the Mozilla Public License 2.0.
Does not include financial advice or signals — for educational use only.
✅ How to Use:
Apply to a 5-minute chart.
Adjust the desired time boxes in the input panel.
Watch for price action within and after the boxes.
Enjoy and feel free to share feedback or ideas for improvement!
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Harmony in Havoc - The Entropy of VoVix Harmony in Havoc – The Entropy of VoVix
There are moments in the market when chaos and order are not opposites, but partners in a dance.
Harmony in Havoc is not just an indicator—it’s a window into that dance.
Most tools try to tame the market by smoothing it, boxing it in, or chasing after what’s already happened. This script does the opposite: it listens for the music beneath the noise, the rare moments when volatility and unpredictability align, and the market’s next movement is about to begin.
What is Harmony in Havoc?
VoVix Spike:
The pulse of volatility-of-volatility. Not just how much the market is moving, but how violently its own heartbeat is changing.
Entropy:
A real-time measure of surprise. When entropy is high, the market is not just moving—it’s breaking its own patterns, rewriting its own rules.
Progression Bar & Status:
The yellow bar is your visual gauge of tension. As it fills, the market is winding up.
Wait: The world is calm.
Get ready!: The storm is building.
Take Action!!: The probability of a regime eruption is at its peak.
Yellow Background:
When the background glows, the market is at its most unstable—this is not a buy or sell signal, but a quant alert.
How does it work?
Every tick, Harmony in Havoc measures the distance between the market’s current volatility and its own unpredictability. When the VoVix spike approaches or exceeds the entropy threshold, the system knows:
“This is the moment when the improbable becomes possible.”
Why is this different?
It doesn’t tell you what to do.
It doesn’t chase price.
It doesn’t care about trends, bands, or the past.
Instead, it gives you a quantitative sense of anticipation—a way to see when the market is most likely to break from its own history, and when the edge is at its sharpest.
How to use it:
Watch for the yellow background and “Take Action!!” status.
Use it as a regime filter, a volatility dashboard, or a warning system for your own strategies.
Tune the inputs for your asset and timeframe—make it your own.
Inputs—explained for you:
VoVix Fast/Slow ATR & Stdev:
Control how sensitive the system is to volatility shocks. Lower = more signals, higher = only the rarest events.
Entropy Window & Bins:
Control how “surprised” the entropy engine is by current volatility. Shorter window = more responsive, more bins = finer detail.
Show/Hide Controls:
Toggle the VoVix spike, entropy line, and their glows to customize your visual experience.
Bottom line:
This is not a buy or sell script.
This is a quant regime detector for those who want to feel the market’s tension—to sense when harmony and havoc are about to collide.
Disclaimer:
Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
*I've only tested this on 1 and 5 min frames.
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
3 days ago
Release Notes
* Now mobile friendly. I've added a toggle to switch the dashboard on/off, and added a mobile information line that shows the same information on the dashboard. This is to allow the script to stay visually in balance and this also has a toggle.
* Background color added that coresponds with Buy or Sell areas.
Anomaly DetectorPrice Anomaly Detector
This is a script designed to identify unusual price movements. By analyzing deviations from typical price behavior, this tool helps traders spot potential trading opportunities and manage risks effectively.
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Features
- Anomaly Detection: Flags price points that significantly deviate from the average.
- Visual Indicators: Highlights anomalies with background colors and cross markers.
- Customizable Settings: Adjust sensitivity and window size to match your trading strategy.
- Real-Time Analysis: Continuously updates anomaly signals as new data is received.
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Usage
After adding the indicator to your chart:
1. View Anomalies: Red backgrounds and cross markers indicate detected anomalies.
2. Adjust Settings: Modify the `StdDev Threshold` and `Window Length` to change detection sensitivity.
3. Interpret Signals:
- Red Background: Anomaly detected on that bar.
- Red Cross: Specific point of anomaly.
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Inputs
- StdDev Threshold: Higher values reduce anomaly sensitivity. Default: 2.0.
- Window Length: Larger windows smooth data, reducing false positives. Default: 20.
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Limitations
- Approximation Method: Uses a simple method to detect anomalies, which may not capture all types of unusual price movements.
- Performance: Extremely large window sizes may impact script performance.
- Segment Detection: Does not group consecutive anomalies into segments.
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Disclaimer : This tool is for educational purposes only. Trading involves risk, and you should perform your own analysis before making decisions. The author is not liable for any losses incurred.
Volume Footprint Voids [BigBeluga]Volume Footprint Voids is a unique tool that uses lower timeframe calculation to plot different styles of single candle POC.
This indicator is very powerful for scalping and finding very precise entry and exits, spotting potential trapped traders, and more.
Unlike many other volume profiles, this aims to plot single candle profiles as well as their own footprints.
🔶 FEATURES
The script includes the following settings:
Windows: Plotting style and calculations
Coloring modes
Display modes
lower-timeframe calculations
🔶 CALCULATION
In the image above we can see how the script calculates each level position that will serve as a calculation process to see how much volume/closes there are within the levels.
In the image above, we can have a more clear example of how we count each candle close.
We use the prior screenshot as an example, after setting each level we will use the lower-timeframe input to measure the amount of closes within the ranges.
Depending on the lot size, the box will be larger or smaller, usually the POC will always have the highest box size.
NOTE: Size is the starting point, always from the low of the candle.
To find more voids, select a closer LTF to the current one you're using.
To find fewer voids, select a timeframe away from your current one.
Due to Pine Script limitations, we are only able to plot a certain amount of footprints, and we can't plot the whole history chart.
POC will be the largest block displayed, indicating the time point of control
Gray areas are closes above the average
Black are Void or imbalance that price will fill in the future, like FVG
The image above shows an incorrect size input that will lead to bad calculations, while on the other side, a correct size input that will lead to a clear vision and better calculation.
🔶 WINDOWS
The "▲▼" Mode will display delta buyers and delta sellers coloring with voids as black.
It also offers a gradient mode for a beautier visualization
The "Total Volume" mode will display the net volume within the lot size (closes within the levels).
This is useful to spot possible highest net volume within the same highest lot size.
The "POC + Gaps" will show both POC and Gaps as the highest block while all the rest will be considered as the smaller block.
This is useful to see where the highest lot were and if there are higher or lower imbalances within the candle
The last option "Gaps" will simply display the gaps as the highest block, while the POC as the lowest block.
This is useful to have a better view of the gaps areas
🔶 EXAMPLE
This is one of the most basic examples of how this script can be used. POC at the bottom creating a strong support area as price holds and creates higher voids gap that price fills while rising.
🔶 SETTINGS
Users have full control over the script, from colors to choosing the lower-timeframe inputs to disabling the lot size.
LIT - TimingIntroduction
This Script displays the Asia Session Range, the London Open Inducement Window, the NY Open Inducement Window, the Previous Week's high and low, the Previous Day's highs and lows, and the Day Open price in the cleanest way possible.
Description
The Indicator is based on UTC -7 timing but displays the Session Boxes automatically correct at your chart so you do not have to adjust any timings based on your Time Zone and don't have to do any calculations based on your UTC. It is already perfect.
You will see on default settings the purple Asia Box and 2 grey boxes, the first one is for the London Open Inducement Window (1 hour) and the second grey box is for the NY Open Inducement Window (also 1 hour)
Asia Range comes with default settings with the Asia Range high, low, and midline, you can remove these 3 lines in the settings "style" and untick the "Lines" box, that way you only will have the boxes displayed.
Special Feature
Most Timing-based Indicators have "bugged" boxes or don't show clean boxes at all and don't adjust at daylight savings times, we made sure that everything automatically gets adjusted so you don't have to! So the timings will always display at the correct time regarding the daylight savings times.
Combining Timing with Liquidity Zones the right way and in a clear, clean, and simple format.
Different than others this script also shows the "true" Asia range as it respects the "day open gap" which affects the Asia range in other scripts and it also covers the full 8 hours of Asia Session.
Additions
You can add in the settings menu the last week's high and low, the previous day's high and low, and also the day's open price by ticking the boxes in the settings menu
All colors of the boxes are fully adjustable and customizable for your personal preferences. Same for the previous weeks and day highs and lows. Just go to "Style" and you can adjust the Line types or colors to your preferred choice.
Recommended Use
The most beautiful display is on the M5 Timeframe as you have a clear overview of all sessions without losing the intraday view. You can also use it on the M1 for more details or the M15 for the bigger picture. The Template can hide on higher time frames starting from the H1 to not flood your chart with boxes.
How to use the Asia Session Range Box
Use the Asia Range Box as your intraday Guide, keep in mind that a Breakout of Asia high or low induces Liquidity and a common price behavior is a reversal after the fake breakout of that range.
How to use the London Open and NY Open Inducement Windows
Both grey boxes highlight the Open of either London Open or NY Open and you should keep an eye out for potential Liquditiy Graps or Mitigations during that times as this is when they introduce major Liquidity for the regarding Session.
How to use the Asia high, low and midline and day open price
After Asia Range got taken out in one direction, often price comes back to those levels to mitigate or bounce off, so you can imagine those zones as support and resistance on some occasions, recommended in combination with Imbalances.
How to use the previous day and week's highs and lows
Once added in the settings, you can display those price levels, you can use them either as Liquidity Targets or as Inducement Levels once they are taken out.
Enjoy!
Candlestick Pattern Criteria and Analysis Indicator█ OVERVIEW
Define, then locate the presence of a candle that fits a specific criteria. Run a basic calculation on what happens after such a candle occurs.
Here, I’m not giving you an edge, but I’m giving you a clear way to find one.
IMPORTANT NOTE: PLEASE READ:
THE INDICATOR WILL ALWAYS INITIALLY LOAD WITH A RUNTIME ERROR. WHEN INITIALLY LOADED THERE NO CRITERIA SELECTED.
If you do not select a criteria or run a search for a criteria that doesn’t exist, you will get a runtime error. If you want to force the chart to load anyway, enable the debug panel at the bottom of the settings menu.
Who this is for:
- People who want to engage in TradingView for tedious and challenging data analysis related to candlestick measurement and occurrence rate and signal bar relationships with subsequent bars. People who don’t know but want to figure out what a strong bullish bar or a strong bearish bar is.
Who this is not for:
- People who want to be told by an indicator what is good or bad or buy or sell. Also, not for people that don’t have any clear idea on what they think is a strong bullish bar or a strong bearish bar and aren’t willing to put in the work.
Recommendation: Use on the candle resolution that accurately reflects your typical holding period. If you typically hold a trade for 3 weeks, use 3W candles. If you hold a trade for 3 minutes, use 3m candles.
Tldr; Read the tool tips and everything above this line. Let me know any issues that arise or questions you have.
█ CONCEPTS
Many trading styles indicate that a certain candle construct implies a bearish or bullish future for price. That said, it is also common to add to that idea that the context matters. Of course, this is how you end up with all manner of candlestick patterns accounting for thousands of pages of literature. No matter the context though, we can distill a discretionary trader's decision to take a trade based on one very basic premise: “A trader decides to take a trade on the basis of the rightmost candle's construction and what he/she believes that candle construct implies about the future price.” This indicator vets that trader’s theory in the most basic way possible. It finds the instances of any candle construction and takes a look at what happens on the next bar. This current bar is our “Signal Bar.”
█ GUIDE
I said that we vet the theory in the most basic way possible. But, in truth, this indicator is very complex as a result of there being thousands of ways to define a ‘strong’ candle. And you get to define things on a very granular level with this indicator.
Features:
1. Candle Highlighting
When the user’s criteria is met, the candle is highlighted on the chart.
The following candle is highlighted based on whether it breaks out, breaks down, or is an inside bar.
2. User-Defined Criteria
Criteria that you define include:
Candle Type: Bull bars, Bear bars, or both
Candle Attributes
Average Size based on Standard Deviation or Average of all potential bars in price history
Search within a specific price range
Search within a specific time range
Clarify time range using defined sessions and with or without weekends
3. Strike Lines on Candle
Often you want to know how price reacts when it gets back to a certain candle. Also it might be true that candle types cluster in a price region. This can be identified visually by adding lines that extend right on candles that fit the criteria.
4. User-Defined Context
Labeled “Alternative Criteria,” this facet of the script allows the user to take the context provided from another indicator and import it into the indicator to use as a overriding criteria. To account for the fact that the external indicator must be imported as a float value, true (criteria of external indicator is met) must be imported as 1 and false (criteria of external indicator is not met) as 0. Basically a binary Boolean. This can be used to create context, such as in the case of a traditional fractal, or can be used to pair with other signals.
If you know how to code in Pinescript, you can save a copy and simply add your own code to the section indicated in the code and set your bull and bear variables accordingly and the code should compile just fine with no further editing needed.
Included with the script to maximize out-of-the-box functionality, there is preloaded as alternative criteria a code snippet. The criteria is met on the bull side when the current candle close breaks out above the prior candle high. The bear criteria is met when the close breaks below the prior candle. When Alternate Criteria is run by itself, this is the only criteria set and bars are highlighted when it is true. You can qualify these candles by adding additional attributes that you think would fit well.
Using Alternative Criteria, you are essentially setting a filter for the rest of the criteria.
5. Extensive Read Out in the Data Window (right side bar pop out window).
As you can see in the thumbnail, there is pasted a copy of the Data Window Dialogue. I am doubtful I can get the thumbnail to load up perfectly aligned. Its hard to get all these data points in here. It may be better suited for a table at this point. Let me know what you think.
The primary, but not exclusive, purpose of what is in the Data Window is to talk about how often your criteria happens and what happens on the next bar. There are a lot of pieces to this.
Red = Values pertaining to the size of the current bar only
Blue = Values pertaining or related to the total number of signals
Green = Values pertaining to the signal bars themselves, including their measurements
Purple = Values pertaining to bullish bars that happen after the signal bar
Fuchsia = Values pertaining to bearish bars that happen after the signal bar
Lime = Last four rows which are your percentage occurrence vs total signals percentages
The best way I can explain how to understand parts you don’t understand otherwise in the data window is search the title of the row in the code using ‘ctrl+f’ and look at it and see if it makes more sense.
█ [b}Available Candle Attributes
Candle attributes can be used in any combination. They include:
[*}Bodies
[*}High/Low Range
[*}Upper Wick
[*}Lower Wick
[*}Average Size
[*}Alternative Criteria
Criteria will evaluate each attribute independently. If none is set for a particular attribute it is bypassed.
Criteria Quantity can be in Ticks, Points, or Percentage. For percentage keep in mind if using anything involving the candle range will not work well with percentage.
Criteria Operators are “Greater Than,” “Less Than,” and “Threshold.” Threshold means within a range of two numbers.
█ Problems with this methodology and opportunities for future development:
#1 This kind of work is hard.
If you know what you’re doing you might be able to find success changing out the inputs for loops and logging results in arrays or matrices, but to manually go through and test various criteria is a lot of work. However, it is rewarding. At the time of publication in early Oct 2022, you will quickly find that you get MUCH more follow through on bear bars than bull bars. That should be obvious because we’re in the middle of a bear market, but you can still work with the parameters and contextual inputs to determine what maximizes your probability. I’ve found configurations that yield 70% probability across the full series of bars. That’s an edge. That means that 70% of the time, when this criteria is met, the next bar puts you in profit.
#2 The script is VERY heavy.
Takes an eternity to load. But, give it a break, it’s doing a heck of a lot! There is 10 unique arrays in here and a loop that is a bit heavy but gives us the debug window.
#3 If you don’t have a clear idea its hard to know where to start.
There are a lot of levers to pull on in this script. Knowing which ones are useful and meaningful is very challenging. Combine that with long load times… its not great.
#4 Your brain is the only thing that can optimize your results because the criteria come from your mind.
Machine learning would be much more useful here, but for now, you are the machine. Learn.
#5 You can’t save your settings.
So, when you find a good combo, you’ll have to write it down elsewhere for future reference. It would be nice if we could save templates on custom indicators like we can on some of the built in drawing tools, but I’ve had no success in that. So, I recommend screenshotting your settings and saving them in Notion.so or some other solid record keeping database. Then you can go back and retrieve those settings.
#6 no way to export these results into conditions that can be copy/pasted into another script.
Copy/Paste of labels or tables would be the best feature ever at this point. Because you could take the criteria and put it in a label, copy it and drop it into another strategy script or something. But… men can dream.
█ Opportunities to PineCoders Learn:
1. In this script I’m importing libraries, showing some of my libraries functionality. Hopefully that gives you some ideas on how to use them too.
The price displacement library (which I love!)
Creative and conventional ways of using debug()
how to display arrays and matrices on charts
I didn’t call in the library that holds the backtesting function. But, also demonstrating, you can always pull the library up and just copy/paste the function out of there and into your script. That’s fine to do a lot of the time.
2. I am using REALLY complicated logic in this script (at least for me). I included extensive descriptions of this ? : logic in the text of the script. I also did my best to bracket () my logic groups to demonstrate how they fit together, both for you and my future self.
3. The breakout, built-in, “alternative criteria” is actually a small bit of genius built in there if you want to take the time to understand that block of code and think about some of the larger implications of the method deployed.
As always, a big thank you to TradingView and the Pinescript community, the Pinescript pros who have mentored me, and all of you who I am privileged to help in their Pinescripting journey.
"Those who stay will become champions" - Bo Schembechler
Real-Fast Fourier Transform of Price w/ Linear Regression [Loxx]Real-Fast Fourier Transform of Price w/ Linear Regression is a indicator that implements a Real-Fast Fourier Transform on Price and modifies the output by a measure of Linear Regression. The solid line is the Linear Regression Trend of the windowed data, The green/red line is the Real FFT of price.
What is the Discrete Fourier Transform?
In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies. It has the same sample-values as the original input sequence. The DFT is therefore said to be a frequency domain representation of the original input sequence. If the original sequence spans all the non-zero values of a function, its DTFT is continuous (and periodic), and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic function, the DFT provides all the non-zero values of one DTFT cycle.
What is the Complex Fast Fourier Transform?
The complex Fast Fourier Transform algorithm transforms N real or complex numbers into another N complex numbers. The complex FFT transforms a real or complex signal x in the time domain into a complex two-sided spectrum X in the frequency domain. You must remember that zero frequency corresponds to n = 0, positive frequencies 0 < f < f_c correspond to values 1 ≤ n ≤ N/2 −1, while negative frequencies −fc < f < 0 correspond to N/2 +1 ≤ n ≤ N −1. The value n = N/2 corresponds to both f = f_c and f = −f_c. f_c is the critical or Nyquist frequency with f_c = 1/(2*T) or half the sampling frequency. The first harmonic X corresponds to the frequency 1/(N*T).
The complex FFT requires the list of values (resolution, or N) to be a power 2. If the input size if not a power of 2, then the input data will be padded with zeros to fit the size of the closest power of 2 upward.
What is Real-Fast Fourier Transform?
Has conditions similar to the complex Fast Fourier Transform value, except that the input data must be purely real. If the time series data has the basic type complex64, only the real parts of the complex numbers are used for the calculation. The imaginary parts are silently discarded.
Inputs:
src = source price
uselreg = whether you wish to modify output with linear regression calculation
Windowin = windowing period, restricted to powers of 2: "4", "8", "16", "32", "64", "128", "256", "512", "1024", "2048"
Treshold = to modified power output to fine tune signal
dtrendper = adjust regression calculation
barsback = move window backward from bar 0
mutebars = mute bar coloring for the range
Further reading:
Real-valued Fast Fourier Transform Algorithms IEEE Transactions on Acoustics, Speech, and Signal Processing, June 1987
Related indicators utilizing Fourier Transform
Fourier Extrapolator of Variety RSI w/ Bollinger Bands
Fourier Extrapolation of Variety Moving Averages
Fourier Extrapolator of Price w/ Projection Forecast
Debug_Window_LibraryLibrary "Debug_Window_Library"
Provides a framework for logging debug information to a window on the chart.
consoleWrite(txt, maxLines) Adds a line of text to the debug window. The text is rolled off the bottom of the window as it fills up.
Parameters:
txt : - this is the text to be appended to the window
maxLines : - this is the size of the window in lines.
Returns: nothing
The example above shows the close value for the last 10 bars.
Here's the code.
//@version=5
indicator("Debug Library test Script", overlay=true)
import sp2432/Debug_Window_Library/1 as dbg
// add some text to the debug window
dbg .consoleWrite( str .tostring(close), 10)
`security()` revisited [PineCoders]NOTE
The non-repainting technique in this publication that relies on bar states is now deprecated, as we have identified inconsistencies that undermine its credibility as a universal solution. The outputs that use the technique are still available for reference in this publication. However, we do not endorse its usage. See this publication for more information about the current best practices for requesting HTF data and why they work.
█ OVERVIEW
This script presents a new function to help coders use security() in both repainting and non-repainting modes. We revisit this often misunderstood and misused function, and explain its behavior in different contexts, in the hope of dispelling some of the coder lure surrounding it. The function is incredibly powerful, yet misused, it can become a dangerous WMD and an instrument of deception, for both coders and traders.
We will discuss:
• How to use our new `f_security()` function.
• The behavior of Pine code and security() on the three very different types of bars that make up any chart.
• Why what you see on a chart is a simulation, and should be taken with a grain of salt.
• Why we are presenting a new version of a function handling security() calls.
• Other topics of interest to coders using higher timeframe (HTF) data.
█ WARNING
We have tried to deliver a function that is simple to use and will, in non-repainting mode, produce reliable results for both experienced and novice coders. If you are a novice coder, stick to our recommendations to avoid getting into trouble, and DO NOT change our `f_security()` function when using it. Use `false` as the function's last argument and refrain from using your script at smaller timeframes than the chart's. To call our function to fetch a non-repainting value of close from the 1D timeframe, use:
f_security(_sym, _res, _src, _rep) => security(_sym, _res, _src )
previousDayClose = f_security(syminfo.tickerid, "D", close, false)
If that's all you're interested in, you are done.
If you choose to ignore our recommendation and use the function in repainting mode by changing the `false` in there for `true`, we sincerely hope you read the rest of our ramblings before you do so, to understand the consequences of your choice.
Let's now have a look at what security() is showing you. There is a lot to cover, so buckle up! But before we dig in, one last thing.
What is a chart?
A chart is a graphic representation of events that occur in markets. As any representation, it is not reality, but rather a model of reality. As Scott Page eloquently states in The Model Thinker : "All models are wrong; many are useful". Having in mind that both chart bars and plots on our charts are imperfect and incomplete renderings of what actually occurred in realtime markets puts us coders in a place from where we can better understand the nature of, and the causes underlying the inevitable compromises necessary to build the data series our code uses, and print chart bars.
Traders or coders complaining that charts do not reflect reality act like someone who would complain that the word "dog" is not a real dog. Let's recognize that we are dealing with models here, and try to understand them the best we can. Sure, models can be improved; TradingView is constantly improving the quality of the information displayed on charts, but charts nevertheless remain mere translations. Plots of data fetched through security() being modelized renderings of what occurs at higher timeframes, coders will build more useful and reliable tools for both themselves and traders if they endeavor to perfect their understanding of the abstractions they are working with. We hope this publication helps you in this pursuit.
█ FEATURES
This script's "Inputs" tab has four settings:
• Repaint : Determines whether the functions will use their repainting or non-repainting mode.
Note that the setting will not affect the behavior of the yellow plot, as it always repaints.
• Source : The source fetched by the security() calls.
• Timeframe : The timeframe used for the security() calls. If it is lower than the chart's timeframe, a warning appears.
• Show timeframe reminder : Displays a reminder of the timeframe after the last bar.
█ THE CHART
The chart shows two different pieces of information and we want to discuss other topics in this section, so we will be covering:
A — The type of chart bars we are looking at, indicated by the colored band at the top.
B — The plots resulting of calling security() with the close price in different ways.
C — Points of interest on the chart.
A — Chart bars
The colored band at the top shows the three types of bars that any chart on a live market will print. It is critical for coders to understand the important distinctions between each type of bar:
1 — Gray : Historical bars, which are bars that were already closed when the script was run on them.
2 — Red : Elapsed realtime bars, i.e., realtime bars that have run their course and closed.
The state of script calculations showing on those bars is that of the last time they were made, when the realtime bar closed.
3 — Green : The realtime bar. Only the rightmost bar on the chart can be the realtime bar at any given time, and only when the chart's market is active.
Refer to the Pine User Manual's Execution model page for a more detailed explanation of these types of bars.
B — Plots
The chart shows the result of letting our 5sec chart run for a few minutes with the following settings: "Repaint" = "On" (the default is "Off"), "Source" = `close` and "Timeframe" = 1min. The five lines plotted are the following. They have progressively thinner widths:
1 — Yellow : A normal, repainting security() call.
2 — Silver : Our recommended security() function.
3 — Fuchsia : Our recommended way of achieving the same result as our security() function, for cases when the source used is a function returning a tuple.
4 — White : The method we previously recommended in our MTF Selection Framework , which uses two distinct security() calls.
5 — Black : A lame attempt at fooling traders that MUST be avoided.
All lines except the first one in yellow will vary depending on the "Repaint" setting in the script's inputs. The first plot does not change because, contrary to all other plots, it contains no conditional code to adapt to repainting/no-repainting modes; it is a simple security() call showing its default behavior.
C — Points of interest on the chart
Historical bars do not show actual repainting behavior
To appreciate what a repainting security() call will plot in realtime, one must look at the realtime bar and at elapsed realtime bars, the bars where the top line is green or red on the chart at the top of this page. There you can see how the plots go up and down, following the close value of each successive chart bar making up a single bar of the higher timeframe. You would see the same behavior in "Replay" mode. In the realtime bar, the movement of repainting plots will vary with the source you are fetching: open will not move after a new timeframe opens, low and high will change when a new low or high are found, close will follow the last feed update. If you are fetching a value calculated by a function, it may also change on each update.
Now notice how different the plots are on historical bars. There, the plot shows the close of the previously completed timeframe for the whole duration of the current timeframe, until on its last bar the price updates to the current timeframe's close when it is confirmed (if the timeframe's last bar is missing, the plot will only update on the next timeframe's first bar). That last bar is the only one showing where the plot would end if that timeframe's bars had elapsed in realtime. If one doesn't understand this, one cannot properly visualize how his script will calculate in realtime when using repainting. Additionally, as published scripts typically show charts where the script has only run on historical bars, they are, in fact, misleading traders who will naturally assume the script will behave the same way on realtime bars.
Non-repainting plots are more accurate on historical bars
Now consider this chart, where we are using the same settings as on the chart used to publish this script, except that we have turned "Repainting" off this time:
The yellow line here is our reference, repainting line, so although repainting is turned off, it is still repainting, as expected. Because repainting is now off, however, plots on historical bars show the previous timeframe's close until the first bar of a new timeframe, at which point the plot updates. This correctly reflects the behavior of the script in the realtime bar, where because we are offsetting the series by one, we are always showing the previously calculated—and thus confirmed—higher timeframe value. This means that in realtime, we will only get the previous timeframe's values one bar after the timeframe's last bar has elapsed, at the open of the first bar of a new timeframe. Historical and elapsed realtime bars will not actually show this nuance because they reflect the state of calculations made on their close , but we can see the plot update on that bar nonetheless.
► This more accurate representation on historical bars of what will happen in the realtime bar is one of the two key reasons why using non-repainting data is preferable.
The other is that in realtime, your script will be using more reliable data and behave more consistently.
Misleading plots
Valiant attempts by coders to show non-repainting, higher timeframe data updating earlier than on our chart are futile. If updates occur one bar earlier because coders use the repainting version of the function, then so be it, but they must then also accept that their historical bars are not displaying information that is as accurate. Not informing script users of this is to mislead them. Coders should also be aware that if they choose to use repainting data in realtime, they are sacrificing reliability to speed and may be running a strategy that behaves very differently from the one they backtested, thus invalidating their tests.
When, however, coders make what are supposed to be non-repainting plots plot artificially early on historical bars, as in examples "c4" and "c5" of our script, they would want us to believe they have achieved the miracle of time travel. Our understanding of the current state of science dictates that for now, this is impossible. Using such techniques in scripts is plainly misleading, and public scripts using them will be moderated. We are coding trading tools here—not video games. Elementary ethics prescribe that we should not mislead traders, even if it means not being able to show sexy plots. As the great Feynman said: You should not fool the layman when you're talking as a scientist.
You can readily appreciate the fantasy plot of "c4", the thinnest line in black, by comparing its supposedly non-repainting behavior between historical bars and realtime bars. After updating—by miracle—as early as the wide yellow line that is repainting, it suddenly moves in a more realistic place when the script is running in realtime, in synch with our non-repainting lines. The "c5" version does not plot on the chart, but it displays in the Data Window. It is even worse than "c4" in that it also updates magically early on historical bars, but goes on to evaluate like the repainting yellow line in realtime, except one bar late.
Data Window
The Data Window shows the values of the chart's plots, then the values of both the inside and outside offsets used in our calculations, so you can see them change bar by bar. Notice their differences between historical and elapsed realtime bars, and the realtime bar itself. If you do not know about the Data Window, have a look at this essential tool for Pine coders in the Pine User Manual's page on Debugging . The conditional expressions used to calculate the offsets may seem tortuous but their objective is quite simple. When repainting is on, we use this form, so with no offset on all bars:
security(ticker, i_timeframe, i_source )
// which is equivalent to:
security(ticker, i_timeframe, i_source)
When repainting is off, we use two different and inverted offsets on historical bars and the realtime bar:
// Historical bars:
security(ticker, i_timeframe, i_source )
// Realtime bar (and thus, elapsed realtime bars):
security(ticker, i_timeframe, i_source )
The offsets in the first line show how we prevent repainting on historical bars without the need for the `lookahead` parameter. We use the value of the function call on the chart's previous bar. Since values between the repainting and non-repainting versions only differ on the timeframe's last bar, we can use the previous value so that the update only occurs on the timeframe's first bar, as it will in realtime when not repainting.
In the realtime bar, we use the second call, where the offsets are inverted. This is because if we used the first call in realtime, we would be fetching the value of the repainting function on the previous bar, so the close of the last bar. What we want, instead, is the data from the previous, higher timeframe bar , which has elapsed and is confirmed, and thus will not change throughout realtime bars, except on the first constituent chart bar belonging to a new higher timeframe.
After the offsets, the Data Window shows values for the `barstate.*` variables we use in our calculations.
█ NOTES
Why are we revisiting security() ?
For four reasons:
1 — We were seeing coders misuse our `f_secureSecurity()` function presented in How to avoid repainting when using security() .
Some novice coders were modifying the offset used with the history-referencing operator in the function, making it zero instead of one,
which to our horror, caused look-ahead bias when used with `lookahead = barmerge.lookahead_on`.
We wanted to present a safer function which avoids introducing the dreaded "lookahead" in the scripts of unsuspecting coders.
2 — The popularity of security() in screener-type scripts where coders need to use the full 40 calls allowed per script made us want to propose
a solid method of allowing coders to offer a repainting/no-repainting choice to their script users with only one security() call.
3 — We wanted to explain why some alternatives we see circulating are inadequate and produce misleading behavior.
4 — Our previous publication on security() focused on how to avoid repainting, yet many other considerations worthy of attention are not related to repainting.
Handling tuples
When sending function calls that return tuples with security() , our `f_security()` function will not work because Pine does not allow us to use the history-referencing operator with tuple return values. The solution is to integrate the inside offset to your function's arguments, use it to offset the results the function is returning, and then add the outside offset in a reassignment of the tuple variables, after security() returns its values to the script, as we do in our "c2" example.
Does it repaint?
We're pretty sure Wilder was not asked very often if RSI repainted. Why? Because it wasn't in fashion—and largely unnecessary—to ask that sort of question in the 80's. Many traders back then used daily charts only, and indicator values were calculated at the day's close, so everybody knew what they were getting. Additionally, indicator values were calculated by generally reputable outfits or traders themselves, so data was pretty reliable. Today, almost anybody can write a simple indicator, and the programming languages used to write them are complex enough for some coders lacking the caution, know-how or ethics of the best professional coders, to get in over their heads and produce code that does not work the way they think it does.
As we hope to have clearly demonstrated, traders do have legitimate cause to ask if MTF scripts repaint or not when authors do not specify it in their script's description.
► We recommend that authors always use our `f_security()` with `false` as the last argument to avoid repainting when fetching data dependent on OHLCV information. This is the only way to obtain reliable HTF data. If you want to offer users a choice, make non-repainting mode the default, so that if users choose repainting, it will be their responsibility. Non-repainting security() calls are also the only way for scripts to show historical behavior that matches the script's realtime behavior, so you are not misleading traders. Additionally, non-repainting HTF data is the only way that non-repainting alerts can be configured on MTF scripts, as users of MTF scripts cannot prevent their alerts from repainting by simply configuring them to trigger on the bar's close.
Data feeds
A chart at one timeframe is made up of multiple feeds that mesh seamlessly to form one chart. Historical bars can use one feed, and the realtime bar another, which brokers/exchanges can sometimes update retroactively so that elapsed realtime bars will reappear with very slight modifications when the browser's tab is refreshed. Intraday and daily chart prices also very often originate from different feeds supplied by brokers/exchanges. That is why security() calls at higher timeframes may be using a completely different feed than the chart, and explains why the daily high value, for example, can vary between timeframes. Volume information can also vary considerably between intraday and daily feeds in markets like stocks, because more volume information becomes available at the end of day. It is thus expected behavior—and not a bug—to see data variations between timeframes.
Another point to keep in mind concerning feeds it that when you are using a repainting security() plot in realtime, you will sometimes see discrepancies between its plot and the realtime bars. An artefact revealing these inconsistencies can be seen when security() plots sometimes skip a realtime chart bar during periods of high market activity. This occurs because of races between the chart and the security() feeds, which are being monitored by independent, concurrent processes. A blue arrow on the chart indicates such an occurrence. This is another cause of repainting, where realtime bar-building logic can produce different outcomes on one closing price. It is also another argument supporting our recommendation to use non-repainting data.
Alternatives
There is an alternative to using security() in some conditions. If all you need are OHLC prices of a higher timeframe, you can use a technique like the one Duyck demonstrates in his security free MTF example - JD script. It has the great advantage of displaying actual repainting values on historical bars, which mimic the code's behavior in the realtime bar—or at least on elapsed realtime bars, contrary to a repainting security() plot. It has the disadvantage of using the current chart's TF data feed prices, whereas higher timeframe data feeds may contain different and more reliable prices when they are compiled at the end of the day. In its current state, it also does not allow for a repainting/no-repainting choice.
When `lookahead` is useful
When retrieving non-price data, or in special cases, for experiments, it can be useful to use `lookahead`. One example is our Backtesting on Non-Standard Charts: Caution! script where we are fetching prices of standard chart bars from non-standard charts.
Warning users
Normal use of security() dictates that it only be used at timeframes equal to or higher than the chart's. To prevent users from inadvertently using your script in contexts where it will not produce expected behavior, it is good practice to warn them when their chart is on a higher timeframe than the one in the script's "Timeframe" field. Our `f_tfReminderAndErrorCheck()` function in this script does that. It can also print a reminder of the higher timeframe. It uses one security() call.
Intrabar timeframes
security() is not supported by TradingView when used with timeframes lower than the chart's. While it is still possible to use security() at intrabar timeframes, it then behaves differently. If no care is taken to send a function specifically written to handle the successive intrabars, security() will return the value of the last intrabar in the chart's timeframe, so the last 1H bar in the current 1D bar, if called at "60" from a "D" chart timeframe. If you are an advanced coder, see our FAQ entry on the techniques involved in processing intrabar timeframes. Using intrabar timeframes comes with important limitations, which you must understand and explain to traders if you choose to make scripts using the technique available to others. Special care should also be taken to thoroughly test this type of script. Novice coders should refrain from getting involved in this.
█ TERMINOLOGY
Timeframe
Timeframe , interval and resolution are all being used to name the concept of timeframe. We have, in the past, used "timeframe" and "resolution" more or less interchangeably. Recently, members from the Pine and PineCoders team have decided to settle on "timeframe", so from hereon we will be sticking to that term.
Multi-timeframe (MTF)
Some coders use "multi-timeframe" or "MTF" to name what are in fact "multi-period" calculations, as when they use MAs of progressively longer periods. We consider that a misleading use of "multi-timeframe", which should be reserved for code using calculations actually made from another timeframe's context and using security() , safe for scripts like Duyck's one mentioned earlier, or TradingView's Relative Volume at Time , which use a user-selected timeframe as an anchor to reset calculations. Calculations made at the chart's timeframe by varying the period of MAs or other rolling window calculations should be called "multi-period", and "MTF-anchored" could be used for scripts that reset calculations on timeframe boundaries.
Colophon
Our script was written using the PineCoders Coding Conventions for Pine .
The description was formatted using the techniques explained in the How We Write and Format Script Descriptions PineCoders publication.
Snippets were lifted from our MTF Selection Framework , then massaged to create the `f_tfReminderAndErrorCheck()` function.
█ THANKS
Thanks to apozdnyakov for his help with the innards of security() .
Thanks to bmistiaen for proofreading our description.
Look first. Then leap.
RSI Stochastic AlignmentRSI Stochastic Alignment input RSI and Stochastic into 1 windows and align them to find bullish and bearish divergence.
A. The Line display in windows:
1. Fast RSI (green line) is RSI(close,3)
2. Slow Rsi (red line) is Linear Regession of Fast RSI with 5 period and offset 0 = linreg(rsi,5,0)
3. Fast Stochastic (blue line) is %K of Stochastic
4. Slow Stochastic (aqua line) is %D of Stochastic
B. Alignment and Divergence Detect
1. Bearish Divergence:
* Slow RSI at top
* Fast Stochastic at bottom
* Fast RSI over overbought level (default = 70)
* Slow Stochastic under overbought level minus a constant value (Divergence Power value, default this value = 1)
2. Bullish Divergence:
* Fast Stochastic at top
* Slow RSI at bottom
* Fast RSI under oversold level (default = 30)
* Slow Stochastic over oversold level plus a constant value (Divergence Power value, default this value = 1)
C. Script Option
1. RSI value adjustable
2. Stochastic value adjustable
3. Overbought and Oversold Level adjustable
4. Enable/Disable Level line
5. Enable/Disable Divergence Column
6. Enable/Disable Key Bar Colored
Narrow Bandpass FilterIn technical analysis most bandpass filters like the MACD, TRIX, AO, or COG will have a non-symmetrical frequency response, in fact, this one is generally right-skewed. As such these oscillators will not fully remove lower and higher frequency components from the input signal, the following indicator is a bandpass filter with a more symmetrical frequency response with the possibility to have a narrow bandwidth, this allows the indicator to potentially isolate sinusoids from the input signal.
Indicator & Settings
The filter is calculated via convolution, if we take into account that the frequency response of a filter is the Fourier transform of its weighting function we can deduce that we can get a narrow response by using a sinusoid sin(2𝛑nf) as the weighting function, with the peak of the frequency response being equal to f , this makes the filter quite easy to control by the user, as this one can choose the frequency to be isolated. The length of the weighting function controls the bandwidth of the frequency response, with a higher length returning an ever-smaller frequency response width.
In the indicator settings the "Cycle Period" determine the period of the sinusoid used as a weighting function, while "Bandwidth" determine the filter passband width, with higher values returning a narrower passband, this setting also determine the length of the convolution, because the sum of the weights must add to 0 we know that the length of the convolution must be a multiple of "Cycle Period", so the length of the convolution is equal to "Cycle Period × Bandwidth".
Finally, the windowing option determines if a window is applied to the weighting function, a weighting function allow to remove ripples in the filter frequency response
Above both indicators have a Cycle period of 100 and a Bandwidth of 4, we can see that the indicator with no windowing don't fully remove the trend component in the price, this is due to the presence of ripples allowing lower frequency components to pass, this is not the case for the windowed version.
In theory, an ultra-narrow passband would allow to fully isolate pure sinusoids, below the cycle period of interest is 20
using a bandwidth equal to 10 allow to retain that sinusoid, however, note that this sinusoid is subject to phase shift and that it might not be a dominant frequency in the price.
Indicador Millo SMA20-SMA200-AO-RSI M1This indicator is designed for scalping in 1-minute timeframes on crypto pairs, combining trend direction, momentum, and oscillator confirmation.
Logic:
Trend Filter:
Only BUY signals when price is above the SMA200.
Only SELL signals when price is below the SMA200.
Entry Trigger:
BUY: Price crosses above the SMA20.
SELL: Price crosses below the SMA20.
Confirmation Window:
After the price cross, the Awesome Oscillator (AO) must cross the zero line in the same direction within a maximum of N bars (configurable, default = 4).
RSI must be > 50 for BUY and < 50 for SELL at the moment AO confirms.
Cooldown:
A cooldown period (configurable, default = 10 bars) prevents multiple signals of the same type in a short time, reducing noise in sideways markets.
Features:
Works on any crypto pair and can be used in other markets.
Adjustable confirmation window, RSI threshold, and cooldown.
Alerts ready for BUY and SELL conditions.
Can be converted into a strategy for backtesting with TP/SL.
Suggested Use:
Pair: BTC/USDT M1 or similar high-liquidity asset.
Combine with manual support/resistance or higher timeframe trend analysis.
Recommended to confirm entries visually and with additional confluence before trading live.
Ichimoku Cloud Signals [sgbpulse] Ichimoku Cloud Signals – Your Advanced Trading Tool
Meet Ichimoku Cloud Signals, the enhanced and interactive version of the classic Ichimoku Cloud indicator, designed specifically for TradingView traders seeking precision and flexibility in their trading decisions. This indicator allows you to maximize the Ichimoku's potential by customizing trend criteria, receiving clear visual signals for entering and exiting positions, and getting alerts to keep you informed.
Introduction to the Ichimoku Cloud
The Ichimoku Cloud, also known as Ichimoku Kinko Hyo, is a comprehensive technical analysis tool developed in Japan. It provides a broad view of the market: trend direction, momentum, and support and resistance levels. "Ichimoku Cloud Signals" takes this power and amplifies it with advanced features.
Key Components of the Ichimoku Cloud
The indicator displays all five familiar Ichimoku lines, along with the "Cloud" (Kumo):
Tenkan-sen (Conversion Line): Calculated as the average of the highest high and lowest low over the past 9 periods. A fast, short-term indicator used as a measure of immediate momentum.
Kijun-sen (Base Line): Calculated as the average of the highest high and lowest low over the past 26 periods. A medium-term reference line serving as a significant support/resistance level.
Senkou Span A (Leading Span A): The average of the Tenkan-sen and Kijun-sen, shifted 26 periods forward into the future.
Senkou Span B (Leading Span B): The average of the highest high and lowest low over the past 52 periods, also shifted 26 periods forward into the future.
Kumo (Cloud): The area between Senkou Span A and Senkou Span B. Its color changes: green for an uptrend (when Senkou Span A is above Senkou Span B) and red for a downtrend (when Senkou Span B is above Senkou Span A). The Cloud serves as a dynamic area of support/resistance and a tool for forecasting future trends.
Chikou Span (Lagging Span): The current closing price, shifted 26 periods backward into the past. It serves as a powerful trend confirmation tool.
How the Ichimoku Cloud Works and How to Interpret It
Trend Identification :
- Uptrend (Bullish): The price is above the Cloud. The higher the price is above the Cloud, the stronger the trend.
- Downtrend (Bearish): The price is below the Cloud. The lower the price is below the Cloud, the stronger the trend.
- Range/Consolidation: The price is within the Cloud. This indicates a market without a clear direction or one that is consolidating.
Support and Resistance:
- The Cloud itself acts as a dynamic area of support and resistance. In an uptrend, the Cloud serves as support. In a downtrend, it serves as resistance.
- A thick Cloud indicates stronger support/resistance levels, while a thin Cloud indicates weaker levels.
The Cloud as a Predictive Indicator:
The uniqueness of the Kumo (Cloud) lies in its ability to be shifted 26 periods forward. This part of the Cloud provides forecasts for future support and resistance levels and even suggests expected trend changes (like a "Kumo Twist" – a change in Cloud color), giving you a planning advantage.
Unique Advantages of Ichimoku Cloud Signals:
Ichimoku Cloud Signals takes the classic Ichimoku principles and gives you unprecedented control:
Focused Trend Selection:
Choose whether you want to analyze a bullish (uptrend) or bearish (downtrend) trend. The indicator will focus on the relevant criteria for your selection.
Customizable Trend Confirmation Criteria (8 Criteria):
The indicator relies on 8 key criteria for clear trend confirmation. You can enable or disable each criterion individually based on your trading strategy and desired risk level. Each criterion plays a vital role in confirming the strength of the trend:
- Price position relative to the Cloud (Kumo) (Default: true): Determines the main trend direction and whether it's bullish or bearish.
- Price position relative to Kijun-sen (Base Line) (Default: true): Indicates the medium-term trend and acts as a critical equilibrium level.
- Price position relative to Tenkan-sen (Conversion Line) (Default: false): Provides quick confirmation of current momentum and short-term market changes.
- Tenkan-sen (Conversion Line) / Kijun-sen (Base Line) Crossover (Default: true): A classic signal for momentum change, crucial for identifying entry points.
- Current Cloud trend (Kumo) (Default: false): Cloud color confirms the main trend direction in real-time.
- Projected Future Cloud trend (Kumo) (Default: true): Indicates an expected future change in the Cloud's trend, providing strong visual insight.
- Chikou Span (Lagging Span) position relative to the Cloud (Kumo) (Default: true): Confirms the current trend strength by comparing the price to the Ichimoku 26 periods ago.
- Chikou Span (Lagging Span) position relative to the Price (Default: false): Additional confirmation of trend strength, indicating buyer/seller dominance.
Full Customization of Ichimoku Parameters:
You can change the period lengths for each Ichimoku component, depending on your strategy:
- Conversion Line Length (Default: 9)
- Base Line Length (Default: 26)
- Leading Span Length (Default: 52)
- Cloud Lagging Length (Default: 26)
- Lagging Span Length (Default: 26)
Visual Criteria Table on the Chart:
Get immediate and clear feedback! A visual table is placed on the chart, showing in real-time which of the 8 criteria you have defined are met for your chosen trend. Criteria you have enabled will be highlighted with a blue color and a "➤" symbol, while disabled criteria will appear in a subtle gray shade. For each criterion, the table shows its real-time status with a "✔" symbol if the condition is met and an "✘" symbol if it is not met. This powerful visual tool provides a quick assessment, helps with learning, and allows for strategy optimization at the click of a button.
Precise Criteria Details in the Data Window:
Beyond the visual table, the indicator provides an additional critical layer of detail: for any point on the chart, you can hover over a candle and see in TradingView's Data Window the precise status and values of all eight criteria. For each criterion, you'll see a clear numerical value (1 or 0) indicating whether it's fully met (1) or not met (0). Additionally, you can inspect the exact numerical values of the Ichimoku lines (Tenkan-sen, Kijun-sen, etc.) at that specific moment. This comprehensive data supports in-depth analysis, strategy debugging, and long-term optimization, providing complete transparency regarding every component of the signal.
Smart and Customizable Alerts:
Ichimoku Cloud Signals provides a powerful alert system to keep you informed of key market movements, so you never miss an opportunity. There are eight unique alerts you can enable in TradingView's alert panel:
Uptrend Entry Alert: Triggers when all of your selected criteria for an uptrend are met on a new candle.
Uptrend Exit Alert: Triggers when one of your selected uptrend criteria is no longer met, signaling a potential exit point.
Downtrend Entry Alert: Triggers when all of your selected criteria for a downtrend are met on a new candle.
Downtrend Exit Alert: Triggers when one of your selected downtrend criteria is no longer met, signaling a potential exit point.
Bullish Crossover Alert: Triggers when the Conversion Line (Tenkan-sen) crosses above the Base Line (Kijun-sen), a classic signal for an upward momentum shift.
Bearish Crossover Alert: Triggers when the Conversion Line (Tenkan-sen) crosses below the Base Line (Kijun-sen), signaling a potential shift to downward momentum.
Bullish Cloud Breakout Alert: Triggers when the price closes above the Ichimoku Cloud (Kumo), indicating a strong bullish trend.
Bearish Cloud Breakout Alert: Triggers when the price closes below the Ichimoku Cloud (Kumo), indicating a strong bearish trend.
Each alert can be independently configured in TradingView's alert panel, allowing you to tailor your notifications to fit your exact trading strategy and risk management preferences.
Summary:
Ichimoku Cloud Signals is an essential tool for TradingView traders seeking control, clarity, and precision. It combines the power of the classic Ichimoku Cloud indicator with advanced customization capabilities, a convenient visual table, and clear signals, empowering you to make informed trading decisions and stay focused on managing your positions.
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.
ADR/ATR Session No Probability Table by LKHere you go—clear, English docs you can drop into your script’s description or share with teammates.
ADR/ATR Session by LK — Overview
This indicator summarizes Average Daily Range (ADR) and Average True Range (ATR) for two horizons:
• Session H4 (e.g., 06:00–13:00 on a 4‑hour chart)
• Daily (D)
It shows:
• Current ADR/ATR values (using your chosen smoothing method)
• How much of ADR/ATR today/this bar has already been consumed (% of ADR/ATR)
• ADR/ATR as a percent of price
• Optional probability blocks: likelihood that %ADR will exceed user‑defined thresholds over a lookback window
• Optional on‑chart lines for the current H4 and Daily candles: Open, ADR High, ADR Low
⸻
What the metrics mean
• ADR (H4 / D): Moving average of the bar range (high - low).
• ATR (H4 / D): Moving average of True Range (max(hi-lo, |hi-close |, |lo-close |)).
• % of ADR (curr H4): (H4 range of the current H4 bar) / ADR(H4) × 100. Updates live even if the current time is outside the session.
• % of ADR (Daily): (today’s intra‑day range) / ADR(D) × 100.
• % of ATR (curr H4 / Daily): TR / ATR × 100 for that horizon.
• ADR % of Price / ATR % of Price: ADR or ATR divided by current price × 100 (a quick “volatility vs. price” gauge).
Session logic (H4): ADR/ATR(H4) only update on bars that fall inside the configured session window; outside the window the values hold steady (no recalculation “bleed”).
Daily range tracking: The indicator tracks today’s high/low in real‑time and resets at the day change.
⸻
Inputs (quick reference)
Core
• Length (ADR/ATR): smoothing length for ADR/ATR (default 21).
• Wait for Higher TF Bar Close: if true, updates ADR/ATR only after the higher‑TF bar closes when using request.security.
Timeframes
• Session Timeframe (H4): default 240.
• Daily Timeframe: default D.
Session time
• Session Timezone: “Chart” (default) or a fixed timezone.
• Session Start Hour, End Hour (minutes are fixed to 0 in this version).
Smoothing methods
• H4 ADR Method / H4 ATR Method: SMA/EMA/RMA/WMA.
• Daily ADR Method / Daily ATR Method: SMA/EMA/RMA/WMA.
Table appearance
• Table BG, Table Text, Table Font Size.
Lines (optional)
• Show current H4 segments, Show current Daily segments
• Line colors for Open / ADR High / ADR Low
• Line width
Probability
• H4 Probability Lookback (bars): number of H4 bars to examine (e.g., 300).
• Daily Probability Lookback (days): number of D bars (e.g., 180).
• ADR thresholds (%): CSV list of thresholds (e.g., 25,50,55,60,65,70,75,80,85,90,95,100,125,150).
The table will show the % of lookback bars where %ADR ≥ threshold.
Tip: If you want probabilities only for session H4 bars (not every H4 bar), ask and I can add a toggle to filter by inSess.
⸻
How to read the table
H4 block
• ADR (method) / ATR (method): the session‑aware averages.
• % of ADR (curr H4): live progress of this H4 bar toward the session ADR.
• ADR % of Price: ADR(H4) relative to price.
• % of ATR (curr H4) and ATR % of Price: same idea for ATR.
H4 Probability (lookback N bars)
• Rows like “≥ 80% ADR” show the fraction (in %) of the last N H4 bars that reached at least 80% of ADR(H4).
Daily block
• Mirrors the H4 block, but for Daily.
Daily Probability (lookback M days)
• Rows like “≥ 100% ADR” show the fraction of the last M daily bars whose daily range reached at least 100% of ADR(D).
⸻
Practical usage
• Use % of ADR (curr H4 / Daily) to judge exhaustion or room left in the day/session.
E.g., if Daily %ADR is already 95%, be cautious with momentum continuation trades.
• The probability tables give a quick historical context:
If “≥ 125% ADR” is ~18%, the market rarely stretches that far; your trade sizing/targets can reflect that.
• ADR/ATR % of Price helps normalize volatility between instruments.
⸻
Troubleshooting
• If probability rows are blank: ensure lookback windows are large enough (and that the chart has enough history).
• If ADR/ATR show … (NA): usually you don’t have enough bars for the chosen length/TF yet.
• If line segments are missing: verify you’re on a chart with visible current H4/D bars and the toggles are enabled.
⸻
Notes & customization ideas
• Add a toggle to count only session bars in H4 probability.
• Add separate thresholds for H4 vs Daily.
• Let users pick minutes for session start/end if needed.
• Add alerts when %ADR crosses specified thresholds.
If you want me to bundle any of the “ideas” above into the code, say the word and I’ll ship a clean patch.
LANZ Strategy 5.0 [Backtest]🔷 LANZ Strategy 5.0 — Rule-Based BUY Logic with Time Filter, Session Limits and Auto SL/TP Execution
This is the backtest version of LANZ Strategy 5.0, built as a strategy script to evaluate real performance under fixed intraday conditions. It automatically places BUY and SELL trades based on structured candle confirmation, EMA trend alignment, and session-based filters. The system simulates real-time execution with precise Stop Loss and Take Profit levels.
📌 Built for traders seeking to simulate clean intraday logic with fully automated entries and performance metrics.
🧠 Core Logic & Strategy Conditions
✅ BUY Signal Conditions:
Price is above the EMA200
The last 3 candles are bullish (close > open)
The signal occurs within the defined session window (NY time)
Daily trade limit has not been exceeded
If all are true, a BUY order is executed at market, with SL and TP set immediately.
🔻 SELL Signal Conditions (Optional):
Exactly inverse to BUY (below EMA + 3 bearish candles). Disabled by default.
🕐 Operational Time Filter (New York Time)
You can fully customize your intraday window:
Start Time: e.g., 01:15 NY
End Time: e.g., 16:00 NY
The system evaluates signals only within this range, even across midnight if configured.
🔁 Trade Management System
One trade at a time per signal
Trades include a Stop Loss (SL) and Take Profit (TP) based on pip distance
Trade result is calculated automatically
Each signal is shown with a triangle marker (BUY only, by default)
🧪 Backtest Accuracy
This version uses:
strategy.order() for entries
strategy.exit() for SL and TP
strategy.close_all() at the configured manual closing time
This ensures realistic behavior in the TradingView strategy tester.
⚙️ Flow Summary (Step-by-Step)
On every bar, check:
Is the time within the operational session?
Is the price above the EMA?
Are the last 3 candles bullish?
If conditions met → A BUY trade is opened:
SL = entry – X pips
TP = entry + Y pips
Trade closes:
If SL or TP is hit
Or at the configured manual close time (e.g., 16:00 NY)
📊 Settings Overview
Timeframe: 1-hour (ideal)
SL/TP: Configurable in pips
Max trades/day: User-defined (default = 99 = unlimited)
Manual close: Adjustable by time
Entry type: Market (not limit)
Visuals: Plotshape triangle for BUY entry
👨💻 Credits:
💡 Developed by: LANZ
🧠 Strategy logic & execution: LANZ
✅ Designed for: Clean backtesting, clarity in execution, and intraday logic simulation
Price Statistical Strategy-Z Score V 1.01
Price Statistical Strategy – Z Score V 1.01
Overview
A technical breakdown of the logic and components of the “Price Statistical Strategy – Z Score V 1.01”.
This script implements a smoothed Z-Score crossover mechanism applied to the closing price to detect potential statistical deviations from local price mean. The strategy operates solely on price data (close) and includes signal spacing control and momentum-based candle filters. No volume-based or trend-detection components are included.
Core Methodology
The strategy is built on the statistical concept of Z-Score, which quantifies how far a value (closing price) is from its recent average, normalized by standard deviation. Two moving averages of the raw Z-Score are calculated: a short-term and a long-term smoothed version. The crossover between them generates long entries and exits.
Signal Conditions
Entry Condition:
A long position is opened when the short-term smoothed Z-Score crosses above the long-term smoothed Z-Score, and additional entry conditions are met.
Exit Condition:
The position is closed when the short-term Z-Score crosses below the long-term Z-Score, provided the exit conditions allow.
Signal Gapping:
A minimum number of bars (Bars gap between identical signals) must pass between repeated entry or exit signals to reduce noise.
Momentum Filter:
Entries are prevented during sequences of three or more consecutively bullish candles, and exits are prevented during three or more consecutively bearish candles.
Z-Score Function
The Z-Score is calculated as:
Z = (Close - SMA(Close, N)) / STDEV(Close, N)
Where N is the base period selected by the user.
Input Parameters
Enable Smoothed Z-Score Strategy
Enables or disables the Z-Score strategy logic. When disabled, no trades are executed.
Z-Score Base Period
Defines the number of bars used to calculate the simple moving average and standard deviation for the Z-Score. This value affects how responsive the raw Z-Score is to price changes.
Short-Term Smoothing
Sets the smoothing window for the short-term Z-Score. Higher values produce smoother short-term signals, reducing sensitivity to short-term volatility.
Long-Term Smoothing
Sets the smoothing window for the long-term Z-Score, which acts as the reference line in the crossover logic.
Bars gap between identical signals
Minimum number of bars that must pass before another signal of the same type (entry or exit) is allowed. This helps reduce redundant or overly frequent signals.
Trade Visualization Table
A table positioned at the bottom-right displays live PnL for open trades:
Entry Price
Unrealized PnL %
Text colors adapt based on whether unrealized profit is positive, negative, or neutral.
Technical Notes
This strategy uses only close prices — no trend indicators or volume components are applied.
All calculations are based on simple moving averages and standard deviation over user-defined windows.
Designed as a minimal, isolated Z-Score engine without confirmation filters or multi-factor triggers.
Tangent Extrapolation ForecastTangent Extrapolation Forecast
This indicator visually projects price direction by drawing a smoothed sequence of tangent lines based on recent price movements. For each bar in a user-defined lookback window, it calculates the slope over a smoothing period and extends the projected price forward. The resulting polyline forecast connect the endpoints of the extrapolations, and is color-coded to reflect directional changes: green for upward moves, red for downward, and gray for flat segments. This tool can assist traders in visualizing short-term momentum and potential trend continuity without introducing artificial future gaps.
Inputs:
Bars to Use: Number of historical bars used in the forecast.
Slope Smoothing Window: The number of bars used to calculate slope for projection.
Source: Price input for calculations (default is close).
This indicator does not generate buy/sell signals. It is intended as a visual aid to support discretionary analysis.
FibSync - DynamicFibSupportWhat is this indicator?
FibSync – DynamicFibSupport overlays your chart with both static and dynamic Fibonacci retracement levels, making it easy to spot potential areas of support and resistance.
Static Fibs: Calculated from the highest and lowest price over a user-defined lookback period.
Dynamic Fibs: Calculated from the most recent swing high and swing low, automatically adapting as new swings form.
How to use
Add the indicator to your chart.
Configure the settings:
Static Fib Period: Sets the lookback window for static fib levels.
Show Dynamic Fibonacci Levels: Toggle dynamic fibs on/off.
Dynamic Fib Swing Search Window: How far back to search for valid swing highs/lows.
Swing Strength (bars left/right): How many bars define a swing high/low (higher = stronger swing).
Interpret the levels:
Solid lines are static fibs.
Transparent lines are dynamic fibs (if enabled).
Colors match standard fib conventions (yellow = 0.236, red = 0.382, blue = 0.618, green = 0.786, gray = 0.5).
Tips
Static and dynamic fibs can overlap-this often highlights especially important support/resistance zones.
Adjust the swing strength for your trading style: lower values for short-term, higher for long-term swings.
Hide/show individual lines using the indicator’s style settings in TradingView.
Trading Ideas (for higher timeframes and static fibs)
Close above the blue line (0.618 static fib):
This can be interpreted as a potential long (buy) signal, suggesting the market is breaking above a key resistance level.
Close below the red line (0.382 static fib):
This can be interpreted as a potential short (sell) signal, indicating the market is breaking below a key support level.
Note: These signals are most meaningful on higher timeframes and when using the static fib lines. Always confirm with your own strategy and risk management.
Entropy Chart Analysis [PhenLabs]📊 Entropy Chart analysis -
Version: PineScript™ v6
📌 Description
The Entropy Chart indicator analysis applies Approximate Entropy (ApEn) to identify zones of potential support and resistance on your price chart. It is designed to locate changes in the market’s predictability, with a focus on zones near significant psychological price levels (e.g., multiples of 50). By quantifying entropy, the indicator aims to identify zones where price action might stabilize (potential support) or become randomized (potential resistance).
This tool automates the visualization of these key areas for traders, which may have the effect of revealing reversal levels or consolidation zones that would be hard to discern through traditional means. It also filters the signals by proximity to key levels in an attempt to reduce noise and highlight higher-probability setups. These dynamic zones adapt to changing market conditions by stretching, merging, and expiring based on user-inputted rules.
🚀 Points of Innovation
Combines Approximate Entropy (ApEn) calculation with price action near significant levels.
Filters zone signals based on proximity (in ticks) to predefined significant price levels (multiples of 50).
Dynamically merges overlapping or nearby zones to consolidate signals and reduce chart clutter.
Uses ApEn crossovers relative to its moving average as the core trigger mechanism.
Provides distinct visual coloring for bullish, bearish, and merged (mixed-signal) zones.
Offers comprehensive customization for entropy calculation, zone sensitivity, level filtering, and visual appearance.
🔧 Core Components
Approximate Entropy (ApEn) Calculation : Measures the regularity or randomness of price fluctuations over a specified window. Low ApEn suggests predictability, while high ApEn suggests randomness.
Zone Trigger Logic : Creates potential support zones when ApEn crosses below its average (indicating increasing predictability) and potential resistance zones when it crosses above (indicating increasing randomness).
Significant Level Filter : Validates zone triggers only if they occur within a user-defined tick distance from significant price levels (multiples of 50).
Dynamic Zone Management : Automatically creates, extends, merges nearby zones based on tick distance, and removes the oldest zones to maintain a maximum limit.
Zone Visualization : Draws and updates colored boxes on the chart to represent active support, resistance, or mixed zones.
🔥 Key Features
Entropy-Based S/R Detection : Uses ApEn to identify potential support (low entropy) and resistance (high entropy) areas.
Significant Level Filtering : Enhances signal quality by focusing on entropy changes near key psychological price points.
Automatic Zone Drawing & Merging : Visualizes zones dynamically, merging close signals for clearer interpretation.
Highly Customizable : Allows traders to adjust parameters for ApEn calculation, zone detection thresholds, level filter sensitivity, merging distance, and visual styles.
Integrated Alerts : Provides built-in alert conditions for the formation of new bullish or bearish zones near significant levels.
Clear Visual Output : Uses distinct, customizable colors for buy (support), sell (resistance), and mixed (merged) zones.
🎨 Visualization
Buy Zones : Represented by greenish boxes (default: #26a69a), indicating potential support areas formed during low entropy periods near significant levels.
Sell Zones : Represented by reddish boxes (default: #ef5350), indicating potential resistance areas formed during high entropy periods near significant levels.
Mixed Zones : Represented by bluish/purple boxes (default: #8894ff), formed when a buy zone and a sell zone merge, indicating areas of potential consolidation or conflict.
Dynamic Extension : Active zones are automatically extended to the right with each new bar.
📖 Usage Guidelines
Calculation Parameters
Window Length
Default: 15
Range: 10-100
Description: Lookback period for ApEn calculation. Shorter lengths are more responsive; longer lengths are smoother.
Embedding Dimension (m)
Default: 2
Range: 1-6
Description: Length of patterns compared in ApEn calculation. Higher values detect more complex patterns but require more data.
Tolerance (r)
Default: 0.5
Range: 0.1-1.0 (step 0.1)
Description: Sensitivity factor for pattern matching (as a multiple of standard deviation). Lower values require closer matches (more sensitive).
Zone Settings
Zone Lookback
Default: 5
Range: 5-50
Description: Lookback period for the moving average of ApEn used in threshold calculations.
Zone Threshold
Default: 0.5
Range: 0.5-3.0
Description: Multiplier for the ApEn average to set crossover trigger levels. Higher values require larger ApEn deviations to create zones.
Maximum Zones
Default: 5
Range: 1-10
Description: Maximum number of active zones displayed. The oldest zones are removed first when the limit is reached.
Zone Merge Distance (Ticks)
Default: 5
Range: 1-50
Description: Maximum distance in ticks for two separate zones to be merged into one.
Level Filter Settings
Tick Size
Default: 0.25
Description: The minimum price increment for the asset. Must be set correctly for the specific instrument to ensure accurate level filtering.
Max Ticks Distance from Levels
Default: 40
Description: Maximum allowed distance (in ticks) from a significant level (multiple of 50) for a zone trigger to be valid.
Visual Settings
Buy Zone Color : Default: color.new(#26a69a, 83). Sets the fill color for support zones.
Sell Zone Color : Default: color.new(#ef5350, 83). Sets the fill color for resistance zones.
Mixed Zone Color : Default: color.new(#8894ff, 83). Sets the fill color for merged zones.
Buy Border Color : Default: #26a69a. Sets the border color for support zones.
Sell Border Color : Default: #ef5350. Sets the border color for resistance zones.
Mixed Border Color : Default: color.new(#a288ff, 50). Sets the border color for mixed zones.
Border Width : Default: 1, Range: 1-3. Sets the thickness of zone borders.
✅ Best Use Cases
Identifying potential support/resistance near significant psychological price levels (e.g., $50, $100 increments).
Detecting potential market turning points or consolidation zones based on shifts in price predictability.
Filtering entries or exits by confirming signals occurring near significant levels identified by the indicator.
Adding context to other technical analysis approaches by highlighting entropy-derived zones.
⚠️ Limitations
Parameter Dependency : Indicator performance is sensitive to parameter settings ( Window Length , Tolerance , Zone Threshold , Max Ticks Distance ), which may need optimization for different assets and timeframes.
Volatility Sensitivity : High market volatility or erratic price action can affect ApEn calculations and potentially lead to less reliable zone signals.
Fixed Level Filter : The significant level filter is based on multiples of 50. While common, this may not capture all relevant levels for every asset or market condition. Accurate Tick Size input is essential.
Not Standalone : Should be used in conjunction with other analysis methods (price action, volume, other indicators) for confirmation, not as a sole basis for trading decisions.
💡 What Makes This Unique
Entropy + Level Context : Uniquely combines ApEn analysis with a specific filter for proximity to significant price levels (multiples of 50), adding locational context to entropy signals.
Intelligent Zone Merging : Automatically consolidates nearby buy/sell zones based on tick distance, simplifying visual analysis and highlighting stronger confluence areas.
Targeted Signal Generation : Focuses alerts and zone creation on specific market conditions (entropy shifts near key levels).
🔬 How It Works
Calculate Entropy : The script computes the Approximate Entropy (ApEn) of the closing prices over the defined Window Length to quantify price predictability.
Check Triggers : It monitors ApEn relative to its moving average. A crossunder below a calculated threshold (avg_apen / zone_threshold) indicates potential support; a crossover above (avg_apen * zone_threshold) indicates potential resistance.
Filter by Level : A potential zone trigger is confirmed only if the low (for support) or high (for resistance) of the trigger bar is within the Max Ticks Distance of a significant price level (multiple of 50).
Manage & Draw Zones : If a trigger is confirmed, a new zone box is created. The script checks for overlaps with existing zones within the Zone Merge Distance and merges them if necessary. Zones are extended forward, and the oldest are removed to respect the Maximum Zones limit. Active zones are drawn and updated on the chart.
💡 Note:
Crucially, set the Tick Size parameter correctly for your specific trading instrument in the “Level Filter Settings”. Incorrect Tick Size will make the significant level filter inaccurate.
Experiment with parameters, especially Window Length , Tolerance (r) , Zone Threshold , and Max Ticks Distance , to tailor the indicator’s sensitivity to your preferred asset and timeframe.
Always use this indicator as part of a comprehensive trading plan, incorporating risk management and seeking confirmation from other analysis techniques.
LANZ Strategy 3.0🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Strategy with Execution Window Logic
LANZ Strategy 3.0 is a rule-based trading system that utilizes the Asian session range to project Fibonacci levels and manage entries during a defined execution window. Designed for Forex and index traders, this strategy focuses on structured price behavior around key levels before the New York session.
🧠 Core Components:
Asian Session Range Mapping: Automatically detects the high, low, and midpoint during the Asian session.
Fibonacci Level Projection: Projects configurable Fibonacci retracement and extension levels based on the Asian range.
Execution Window Logic: Uses the 01:15 NY candle as a reference to validate potential reversals or continuation setups.
Conditional Entry System: Includes logic for limit order entries (buy or sell) at specific Fib levels, with reversal logic if price breaks structure before execution.
Risk Management: Entry orders are paired with dynamic SL and TP based on Fibonacci-based distances, maintaining a risk-reward ratio consistent with intraday strategies.
📊 Visual Features:
Asian session high/low/mid lines.
Fibonacci levels: Original (based on raw range) and Optimized (user-adjustable).
Session background coloring for Asia, Execution Window, and NY session.
Labels and lines for entry, SL, and TP targets.
Dynamic deletion of untriggered orders after execution window expires.
⚙️ How It Works:
The script calculates the Asian session range.
Projects Fibonacci levels from the range.
Waits for the 01:15 NY candle to close to validate a signal.
If valid, a limit entry order (BUY or SELL) is plotted at the selected level.
If price structure changes (e.g., breaks the high/low), reversal logic may activate.
If no trade is triggered, orders are cleared before the NY session.
🔔 Alerts:
Alerts trigger when a valid setup appears after 01:15 NY candle.
Optional alerts for order activation, SL/TP hit, or trade cancellation.
📝 Notes:
Intended for semi-automated or discretionary trading.
Best used on highly liquid markets like Forex majors or indices.
Script parameters include session times, Fib ratios, SL/TP settings, and reversal logic toggle.
Credits:
Developed by LANZ, this script merges traditional session-based analysis with Fibonacci tools and structured execution timing, offering a unique framework for morning volatility plays.
ICT Macro H1"H1 Candle Time Box" is a custom TradingView indicator that highlights a configurable time window surrounding the close of each 1-hour (H1) candle. The indicator draws a transparent box 15 minutes before and after each H1 candle close (by default), helping traders visualize time-based reaction zones.
🔍 Features:
Custom time window: Users can set how many minutes before and after the H1 close the box should appear.
Dynamic positioning: Boxes are drawn slightly above the candles to avoid overlap with price bars.
Live time labels: Each box displays its time range (e.g., "08:45 - 09:15") based on the start and end time of the zone.
Auto-cleaning: Only a limited number of recent boxes (default: 5) are shown, keeping the chart clean.
Requires 1-minute chart for precise timing.
This tool is especially helpful for intraday traders to identify areas of interest or market reactions before and after key hourly closes.
Cointegration Buy and Sell Signals [EdgeTerminal]The Cointegration Buy And Sell Signals is a sophisticated technical analysis tool to spot high-probability market turning points — before they fully develop on price charts.
Most reversal indicators rely on raw price action, visual patterns, or basic and common indicator logic — which often suffer in noisy or trending markets. In most cases, they lag behind the actual change in trend and provide useless and late signals.
This indicator is rooted in advanced concepts from statistical arbitrage, mean reversion theory, and quantitative finance, and it packages these ideas in a user-friendly visual format that works on any timeframe and asset class.
It does this by analyzing how the short-term and long-term EMAs behave relative to each other — and uses statistical filters like Z-score, correlation, volatility normalization, and stationarity tests to issue highly selective Buy and Sell signals.
This tool provides statistical confirmation of trend exhaustion, allowing you to trade mean-reverting setups. It fades overextended moves and uses signal stacking to reduce false entries. The entire indicator is based on a very interesting mathematically grounded model which I will get into down below.
Here’s how the indicator works at a high level:
EMAs as Anchors: It starts with two Exponential Moving Averages (EMAs) — one short-term and one long-term — to track market direction.
Statistical Spread (Regression Residuals): It performs a rolling linear regression between the short and long EMA. Instead of using the raw difference (short - long), it calculates the regression residual, which better models their natural relationship.
Normalize the Spread: The spread is divided by historical price volatility (ATR) to make it scale-invariant. This ensures the indicator works on low-priced stocks, high-priced indices, and crypto alike.
Z-Score: It computes a Z-score of the normalized spread to measure how “extreme” the current deviation is from its historical average.
Dynamic Thresholds: Unlike most tools that use fixed thresholds (like Z = ±2), this one calculates dynamic thresholds using historical percentiles (e.g., top 10% and bottom 10%) so that it adapts to the asset's current behavior to reduce false signals based on market’s extreme volatility at a certain time.
Z-Score Momentum: It tracks the direction of the Z-score — if Z is extreme but still moving away from zero, it's too early. It waits for reversion to start (Z momentum flips).
Correlation Check: Uses a rolling Pearson correlation to confirm the two EMAs are still statistically related. If they diverge (low correlation), no signal is shown.
Stationarity Filter (ADF-like): Uses the volatility of the regression residual to determine if the spread is stationary (mean-reverting) — a key concept in cointegration and statistical arbitrage. It’s not possible to build an exact ADF filter in Pine Script so we used the next best thing.
Signal Control: Prevents noisy charts and overtrading by ensuring no back-to-back buy or sell signals. Each signal must alternate and respect a cooldown period so you won’t be overwhelmed and won’t get a messy chart.
Important Notes to Remember:
The whole idea behind this indicator is to try to use some stat arb models to detect shifting patterns faster than they appear on common indicators, so in some cases, some assumptions are made based on historic values.
This means that in some cases, the indicator can “jump” into the conclusion too quickly. Although we try to eliminate this by using stationary filters, correlation checks, and Z-score momentum detection, there is still a chance some signals that are generated can be too early, in the stock market, that's the same as being incorrect. So make sure to use this with other indicators to confirm the movement.
How To Use The Indicator:
You can use the indicator as a standalone reversal system, as a filter for overbought and oversold setups, in combination with other trend indicators and as a part of a signal stack with other common indicators for divergence spotting and fade trades.
The indicator produces simple buy and sell signals when all criteria is met. Based on our own testing, we recommend treating these signals as standalone and independent from each other . Meaning that if you take position after a buy signal, don’t wait for a sell signal to appear to exit the trade and vice versa.
This is why we recommend using this indicator with other advanced or even simple indicators as an early confirmation tool.
The Display Table:
The floating diagnostic table in the top-right corner of the chart is a key part of this indicator. It's a live statistical dashboard that helps you understand why a signal is (or isn’t) being triggered, and whether the market conditions are lining up for a potential reversal.
1. Z-Score
What it shows: The current Z-score value of the volatility-normalized spread between the short EMA and the regression line of the long EMA.
Why it matters: Z-score tells you how statistically extreme the current relationship is. A Z-score of:
0 = perfectly average
> +2 = very overbought
< -2 = very oversold
How to use it: Look for Z-score reaching extreme highs or lows (beyond dynamic thresholds). Watch for it to start reversing direction, especially when paired with green table rows (see below)
2. Z-Score Momentum
What it shows: The rate of change (ROC) of the Z-score:
Zmomentum=Zt − Zt − 1
Why it matters: This tells you if the Z-score is still stretching out (e.g., getting more overbought/oversold), or reverting back toward the mean.
How to use it: A positive Z-momentum after a very low Z-score = potential bullish reversal A negative Z-momentum after a very high Z-score = potential bearish reversal. Avoid signals when momentum is still pushing deeper into extremes
3. Correlation
What it shows: The rolling Pearson correlation coefficient between the short EMA and long EMA.
Why it matters: High correlation (closer to +1) means the EMAs are still statistically connected — a key requirement for cointegration or mean reversion to be valid.
How to use it: Look for correlation > 0.7 for reliable signals. If correlation drops below 0.5, ignore the Z-score — the EMAs aren’t moving together anymore
4. Stationary
What it shows: A simplified "Yes" or "No" answer to the question:
“Is the spread statistically stable (stationary) and mean-reverting right now?”
Why it matters: Mean reversion strategies only work when the spread is stationary — that is, when the distance between EMAs behaves like a rubber band, not a drifting cloud.
How to use it: A "Yes" means the indicator sees a consistent, stable spread — good for trading. "No" means the market is too volatile, disjointed, or chaotic for reliable mean reversion. Wait for this to flip to "Yes" before trusting signals
5. Last Signal
What it shows: The last signal issued by the system — either "Buy", "Sell", or "None"
Why it matters: Helps avoid confusion and repeated entries. Signals only alternate — you won’t get another Buy until a Sell happens, and vice versa.
How to use it: If the last signal was a "Buy", and you’re watching for a Sell, don’t act on more bullish signals. Great for systems where you only want one position open at a time
6. Bars Since Signal
What it shows: How many bars (candles) have passed since the last Buy or Sell signal.
Why it matters: Gives you context for how long the current condition has persisted
How to use it: If it says 1 or 2, a signal just happened — avoid jumping in late. If it’s been 10+ bars, a new opportunity might be brewing soon. You can use this to time exits if you want to fade a recent signal manually
Indicator Settings:
Short EMA: Sets the short-term EMA period. The smaller the number, the more reactive and more signals you get.
Long EMA: Sets the slow EMA period. The larger this number is, the smoother baseline, and more reliable trend bases are generated.
Z-Score Lookback: The period or bars used for mean & std deviation of spread between short and long EMAs. Larger values result in smoother signals with fewer false positives.
Volatility Window: This value normalizes the spread by historical volatility. This allows you to prevent scale distortion, showing you a cleaner and better chart.
Correlation Lookback: How many periods or how far back to test correlation between slow and long EMAs. This filters out false positives when EMAs lose alignment.
Hurst Lookback: The multiplier to approximate stationarity. Lower leads to more sensitivity to regime change, higher produces a more stricter filtering.
Z Threshold Percentile: This value sets how extreme Z-score must be to trigger a signal. For example, 90 equals only top/bottom 10% of extremes, 80 = more frequent.
Min Bars Between Signals: This hard stop prevents back-to-back signals. The idea is to avoid over-trading or whipsaws in volatile markets even when Hurst lookback and volatility window values are not enough to filter signals.
Some More Recommendations:
We recommend trying different EMA pairs (10/50, 21/100, 5/20) for different asset behaviors. You can set percentile to 85 or 80 if you want more frequent but looser signals. You can also use the Z-score reversion monitor for powerful confirmation.
VWAP + EMA Retracement Indicator SwiftEdgeVWAP + EMA Retracement Indicator
Overview
The VWAP + EMA Retracement Indicator is a powerful and visually engaging tool designed to help traders identify high-probability buy and sell opportunities in trending markets. By combining the Volume Weighted Average Price (VWAP) with two Exponential Moving Averages (EMAs) and a unique retracement-based signal logic, this indicator pinpoints moments when the price pulls back to a key zone before resuming its trend. Its modern, AI-inspired visuals and customizable features make it both intuitive and adaptable for traders of all levels.
What It Does
This indicator generates buy and sell signals based on a sophisticated yet straightforward strategy:
Buy Signals: Triggered when the price is above VWAP, has recently retraced to the zone between two EMAs (default 12 and 21 periods), and a strong bullish candle closes above both EMAs.
Sell Signals: Triggered when the price is below VWAP, has retraced to the EMA zone, and a strong bearish candle closes below both EMAs.
Signal Filtering: A customizable cooldown period ensures that only the first signal in a sequence is shown, reducing noise while preserving opportunities for new trends.
Confidence Scores: Each signal includes an AI-inspired confidence score (0-100%), calculated from candle strength and price distance to VWAP, helping traders gauge signal reliability.
The indicator’s visuals enhance decision-making with dynamic gradient lines, a highlighted retracement zone, and clear signal labels, all customizable to suit your preferences.
How It Works
The indicator integrates several components that work together to create a cohesive trading tool:
VWAP: Acts as a dynamic support/resistance level, reflecting the average price weighted by volume. It filters signals to ensure buys occur in uptrends (price above VWAP) and sells in downtrends (price below VWAP).
Dual EMAs: Two EMAs (default 12 and 21 periods) define a retracement zone where the price is likely to consolidate before continuing its trend. Signals are generated only after the price exits this zone with conviction.
Retracement Logic: The indicator looks for price pullbacks to the EMA zone within a user-defined lookback window (default 5 candles), ensuring signals align with trend continuation patterns.
Candle Strength: Signals require strong candles (bullish for buys, bearish for sells) with a minimum body size based on the Average True Range (ATR), filtering out weak or indecisive moves.
Cooldown Mechanism: A unique feature that prevents signal clutter by allowing only the first signal within a user-defined period (default 3 candles), balancing responsiveness with clarity.
Confidence Score: Combines candle body size and price distance to VWAP to assign a score, giving traders an at-a-glance measure of signal strength without needing external analysis.
These components are carefully combined to capture high-probability setups while minimizing false signals, making the indicator suitable for both short-term and swing trading.
How to Use It
Add to Chart: Apply the indicator to a 15-minute chart (recommended) or your preferred timeframe.
Customize Settings:
VWAP Source: Choose the price source (default: hlc3).
EMA Periods: Adjust the fast and slow EMA periods (default: 12 and 21).
Retracement Window: Set how many candles to look back for retracement (default: 5).
ATR Period & Body Size: Define candle strength requirements (default: 14 ATR period, 0.3 multiplier).
Cooldown Period: Control the minimum candles between signals (default: 3; set to 0 to disable).
Candle Requirements: Toggle whether signals require bullish/bearish candles or entire candle above/below EMAs.
Visuals: Enable/disable gradient colors, retracement zone, confidence scores, and choose a color scheme (Neon, Light, or Dark).
Interpret Signals:
Buy: A green "Buy" label with a confidence score appears below the candle when conditions are met.
Sell: A red "Sell" label with a confidence score appears above the candle.
Use the confidence score to prioritize higher-probability signals (e.g., above 80%).
Trade Management: Combine signals with your risk management strategy, such as setting stop-loss below the retracement zone and targeting a 1:2 risk-reward ratio.
Why It’s Unique
The VWAP + EMA Retracement Indicator stands out due to its thoughtful integration of classic indicators with modern enhancements:
Balanced Signal Filtering: The cooldown mechanism ensures clarity without missing key opportunities, unlike many indicators that overwhelm with frequent signals.
AI-Inspired Confidence: The confidence score simplifies decision-making by quantifying signal strength, mimicking advanced analytical tools in an accessible way.
Elegant Visuals: Dynamic gradients, a highlighted retracement zone, and customizable color schemes (Neon, Light, Dark) create a sleek, futuristic interface that’s both functional and visually appealing.
Flexibility: Extensive customization options let traders tailor the indicator to their style, from conservative swing trading to aggressive scalping.
