Cyclic Smoothed RSI with Motive-Corrective Wave Indicator
This indicator uses the cyclic smoothed Relative Strength Index (cRSI) instead of the traditional Relative Strength Index (RSI). See below for more info on the benefits to the cRSI.
My key contributions
1) A Weighted Moving Average (WMA) to track the general trend of the cRSI signal. This is very helpful in determining when the equity switches from bullish to bearish, which can be used to determine buy/sell points. This is then is used to color the region between the upper and lower cRSI bands (green above, red below).
2) An attempt to detect the motive (impulse) and corrective and waves. Corrective waves are indicated A, B, C, D, E, F, G. F and G waves are not technically Elliot Waves, but the way I detect waves it is really hard to always get it right. Once and a while you could actually see G and F a second time. Motive waves are identified as s (strong) and w (weak). Strong waves have a peak above the cRSI upper band and weak waves have a peak below the upper band.
3) My own divergence indicator for bull, hidden bull, bear, and hidden bear. I was not able to replicate the TradingView style of drawing a line from peak to peak, but for this indicator I think in the end it makes the chart cleaner.
There is a latency issue with an indicator that is based on moving averages. That means they tend to trigger right after key events. Perfect timing is not possible strictly with these indicators, but they do work very well "on average." However, my implementation has minimal latency as peaks (tops/bottoms) only require one bar to detect.
As a bit of an Easter Egg, this code can be tweaked and run as a strategy to get buy/sell signals. I use this code for both my indicator and for trading strategy. Just copy and past it into a new strategy script and just change it from study to a strategy, something like this:
strategy("cRSI + Waves Strategy with VWMA overlay", overlay=overlay)
The buy/sell code is at the end and just needs to be uncommented. I make no promises or guarantees about how good it is as a strategy, but it gives you some code and ideas to work with.
Tuning
1) Volume Weighted Moving Average (VWMA): This is a “hidden strategy” feature implemented that will display the high-low bands of the VWMA on the price chart if run the code using “overlay = true”.
- If the equity does not have volume, then the VWMA will not show up. Uncheck this box and it will use the regular WMA (no volume).
- defines how far back the WMA averages price.
2) cRSI (Black line in the indicator)
- Increase to length that amount of time a band (upper/lower) stays high/low after a peak. Reduce the value to shorten the time. Just increment it up/down to see the effect.
- defines how far back the SMA averages the cRSI. This affects the purple line in the indicator.
- defines how many bars back the peak detector looks to determine if a peak has occurred. For example, a top is detected like this: current-bar down relative to the 1-bar-back, 1-bar-back up relative to 2-bars-back (look back = 1), c) 2-bars-back up relative to 3-bars-back (lookback = 2), and d) 3-bars-back up relative to 4-bars-back (lookback = 3). I hope that makes sense. There are only 2 options for this setting: 2 or 3 bars. 2 bars will be able to detect small peaks but create more “false” peaks that may not be meaningful. 3 bars will be more robust but can miss short duration peaks.
3) Waves
- The check boxes are self explanatory for which labels they turn on and off on the plot.
4) Divergence Indicators
- The check boxes are self explanatory for which labels they turn on and off on the plot.
Hints
- The most common parameter to change is the . Different stocks will have different levels of strength in their peaks. A setting of 2 may generate too many corrective waves.
- Different times scales will give you different wave counts. This is to be expected. A counter impulse wave inside a corrective wave may actually go above the cRSI WMA on a smaller time frame. You may need to increase it one or two levels to see large waves.
- Just because you see divergence (bear or hidden bear) does not mean a price is going to go down. Often price continues to rise through bears, so take note and that is normal. Bulls are usually pretty good indicators especially if you see them on C,E,G waves.
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cyclic smoothed RSI (cRSI) indicator
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The “core” code for the cyclic smoothed RSI (cRSI) indicator was written by Lars von Theinen and is subject to the terms of the Mozilla Public License 2.0 at mozilla.org Copyright (C) 2017 CC BY, whentotrade / Lars von Thienen. For more details on the cRSI Indicator:
The cyclic smoothed RSI indicator is an enhancement of the classic RSI, adding
1) additional smoothing according to the market vibration,
2) adaptive upper and lower bands according to the cyclic memory and
3) using the current dominant cycle length as input for the indicator.
It is much more responsive to market moves than the basic RSI. The indicator uses the dominant cycle as input to optimize signal, smoothing, and cyclic memory. To get more in-depth information on the cyclic-smoothed RSI indicator, please read Decoding The Hidden Market Rhythm - Part 1: Dynamic Cycles (2017), Chapter 4: "Fine-tuning technical indicators." You need to derive the dominant cycle as input parameter for the cycle length as described in chapter 4.
Hope this helps and good luck.
在脚本中搜索"averages"
Displaced Moving Average Channel (DMA)What is This?
The Displaced Moving Average Channel (DMA) indicator is a combination of two moving averages calculated on the high and low of a set time period back which are displaced forward or backward with the center highlighted as a central channel.
What Information Can I Get Out of It?
This indicator can be used as a support or resistance as some moving averages are typically used as well as a tiny measure of recent volatility by looking at the spread between the top and bottom moving averages.
Where Did This Idea Come From?
I did not come up with the concept of this indicator since I was inspired to use this as a setup/trigger indicator in a potential trading strategy as seen in this whitepaper .
Trading With Colors7 hours ago
Hello friends. This is simply a moving average ribbon, per se. The values for the colored ribbon can have their length calculated to fit their chosen resolution on the current one. This solved problems for me, but it was my own solution. Maybe I'll learn something new from sharing this.
To everybody else who is learning as well, this script essentially serves to introduce other time-frame moving averages. This intends to helps traders find the scope of relevance and not get lost in the current time-frame.
Besides the colored moving averages (2 sets, different resolutions, great zoomed in our out), I included optional check-boxes to allow comparison of sets of moving averages at will, so that the most important to the individual trader can be compared and selected specifically.
I kept the default options set to keep it clean. It likely won't be the only indicator on one's chart, so it's naturally best to reduce indicator noise from one, as to not subtract from the benefit of the other indicators.
I integrated tons of acquired knowledge into this, so I hope somebody finds a missing piece to their collection or a solution to a coding problem within. I also hope this provides a new insight and helps others on their path to financial freedom.
Best wishes.
PS: I left some old code in comments in case it helps to understand the evolution of my code. I'll update this again once it works on the Daily. You might figure it out before I do, in wish case, do share :)
Filter Amplitude Response Estimator - A Simple CalculationIn digital signal processing knowing how a system interact with the frequency content of an input signal is extremely important, the mathematical tool that give you this information is called "frequency response". The frequency response regroup two elements, the amplitude response, and the phase response. The amplitude response tells you how the system modify the amplitude of the frequency components in the input signal, the phase response tells you how the system modify the phase of the frequency components in the signal, each being a function of the frequency.
The today proposed tool aim to give a low resolution representation of the amplitude response of any filter.
What Is The Amplitude Response Of A Filter ?
Remember that filters allow to interact with the frequency content of a signal by amplifying, attenuating and/or removing certain frequency components in the input signal, the amplitude (also called magnitude) response of a filter let you know exactly how your filter change the amplitude of the frequency components in the input signal, another way to see the amplitude response is as a tool that tell you what is the peak amplitude of a filter using a sinusoid of a certain frequency as input signal.
For example if the amplitude response of a filter give you a value of 0.9 at frequency 0.5, it means that the filter peak amplitude using a sinusoid of frequency 0.5 is equal to 0.9.
There are several ways to calculate the frequency response of a filter, when our filter is a FIR filter (the filter impulse response is finite), the frequency response of the filter is the absolute value of the discrete Fourier transform (DFT) of the filter impulse response.
If you are curious about this process, know that the DFT of a N samples signal return N values, so if our FIR filter coefficients are composed of only 5 values we would get a frequency response of 5 values...which would not be useful, this is why we "pad" our coefficients with zeros, that is we add zeros to the start and end of our series of coefficients, this process is called "zero-padding", so if our series of coefficients is: (1,2,3,4,5), applying zero padding would give (0,0...1,2,3,4,5,...0,0) while keeping a certain symmetry. This is related to the concept of resolution, a low resolution amplitude response would be composed of a low number of values and would not be useful, this is why we use zero-padding to add more values thus increasing the resolution.
Making a Fourier transform in Pinescript is not doable, as you need the complex number i for computing a DFT, but thats not even the only problem, a DFT would not be that useful anyway (as the processes to make it useful in a trading context would be way too complex) . So how can we calculate a filter amplitude response without using a DFT ? The simple answer is by taking the peak amplitude of a filter using a sinusoid of a certain frequency as input, this is what the proposed tool do.
Using The Tool
The proposed tool give you a 50 point amplitude response from frequency 0.005 to 0.25 by default. the setting "Range Divisor" allow you to see the amplitude response by using a different range of frequency, for example if the range divisor is equal to 2 the filter amplitude response will be evaluated from frequency 0.0025 to 0.125.
In the script, filt hold the filter you want to see the frequency response, by default a simple moving average.
The position of the frequency response is defined by the "Show Amplitude Response At Bar Number" setting, if you want the frequency response to start at bar number 5000 then enter 5000, by default 10000. If you are not a premium set the number at 4000 and it should work.
amplitude response of a simple moving average of period 14, res = 2.
By default the amplitude response use an amplitude scale, a value of 1 represent an unchanged amplitude. You can use Dbfs (decibel full scale) instead by checking the "To Decibels (Full Scale)" setting.
Dbfs amplitude response, a value of 0 represent an unchanged amplitude.
Some Amplitude Responses
In order to prove the accuracy of the proposed tool we can compare the amplitude response given by the proposed tool with the mathematical function of the amplitude response of a simple moving average, that is:
abs(sin(pi*f*length)/(length*sin(pi*f)))
In cyan the amplitude response given by the proposed tool and in blue the above function. Below are the amplitude responses of some moving averages with period 14.
Amplitude response of an EMA, the EMA is a IIR filter, therefore the amplitude response can't be made by taking the DFT of the impulse response (as this ones has infinite length), however our tool can give its frequency response.
Amplitude response of the Hull MA, as you can see some frequencies are amplified, this is common with low-lag filters.
Gaussian moving average (ALMA), with offset = 0.5 and sigma = 6.
Simple moving average high-pass filter amplitude response
Center of gravity bandpass filter amplitude response
Center of gravity bandreject filter.
IMPORTANT!: The amplitude response of adaptive moving averages is not stationary and might change over time.
Conclusion
A tool giving the amplitude response of any filter has been presented, of course this method is not efficient at all and has a low resolution of 50 points (the common resolution is of 512 points) and is difficult to work with, but has the merit to work on Tradingview and can give the frequency response of IIR filters, if you really need to see the frequency response of a filter then i recommend you to use the function freqz from the scipy package.
I still hope you will enjoy using this tool to have a look at the amplitude responses of your favorite moving averages.
I'am aware of the current situation, however i'am somehow feeling left out from the pinescript community, let me know via PM if i have done something to you and i'll do my best to fix any problems i might have caused (or i might be being parano xD)
Gann High LowGann High Low is a moving average based trend indicator consisting of two different simple moving averages.
The Gann High Low Activator Indicator was described by Robert Krausz in a 1998 issue of Stocks & Commodities Magazine. It is a simple moving average SMA of the previous n period's highs or lows.
The indicator tracks both curves (of the highs and the lows). The close of the bar defines which of the two gets plotted.
This version is showing the channel that needs to be broken if the trend is going to be changed, and it allows you to chose from the 4 basic averages type for calculation (by definition, Gann High Low Activator uses only simple moving average, but some other averages can give you results that are probably more acceptable for trading in some conditions).
Increasing HPeriod and decreasing LPeriod better for short trades, vice versa for long positions.
Multiple MA (techsound088)Common moving addresses often act as support and resistance levels. This script will incorporate four (2 exponential and 2 simple ) moving averages. The default are lengths of 8, 20, 50, and 200. These are adjustable. Many of us are aware that these areas often tend to be supply / demands zones. We are also aware that movement around these areas can fluctuate greatly so I've included ATR-based bands around the moving averages hoping to visualize these moving averages in a less rigid and more realistic way. Feel free to modify this script as you please. Constructive feedback is always appreciated.
GMMA Oscillator v1 by JustUncleLOn request, here is my version of the Guppy GMMA Oscillator (and SuperGuppy Oscillator) to match with my Guppy and Super Guppy indicators.
Description:
The Guppy Multiple Moving Average (GMMA) is a technical indicator that displays two sets of moving averages. The first set contains six exponential moving averages that use faster periods to monitor the trading activity of short-term traders. The second set contains six exponential moving averages that use slower periods to monitor the trading activity of long-term investors.
The GMMA Oscillator is a technical indicator developed by Leon Wilson. The oscillator line, which percentage difference between the Fast and Slow GMMA sets. The second line is the signal line and it is simply the exponential moving average of the oscillator line.
As with many trend following indicators, a bullish signal occurs when the oscillator line crosses above the signal line and a bearish signal when the oscillator line crosses below the signal line.
Options:
Select between Guppy MMA or SuperGuppy MMA calculated Oscillator.
Option to apply smoothing to the Oscillator line (recommendation 3)
Option to change Signal line period length
Option to use Anchor Time frame to match the Guppy or SuperGuppy chart
Option to show coloured Bullish/Bearish trading Zones
Crossover alerts are also generated to be picked up by the TradingView's Alarm Sub-system.
4 Time Frame Two EMAs Ribbon Comparison - Tom1traderI had seen something like this on metatrader but not here. Since I use TradingView and not metatrader had some fun with this. Indicates up or down for 4 chosen time Frames and as such helps to see the historical trend. Works best on daily or shorter charts because of load time.
User can choose the length of the two exponential moving averages used on each time frame or use defaults 9 and 15.
User can choose the 4 time frames defaults are (display from top to bottom) 5, 15, 60 and D.
Displays a column of 4 dots or circles for each bar of current chart the top being the shortest time frame.
If the faster exponential moving average is above the slower (uptrend) the dot is green else red.
This is similar (actually what I was originally shooting for but took extra time to figure out time frames on here) to another script of mine that has the same display method but uses a spaced set of Hull Moving Averages on one time frame, you choose the shortest length and the space increment between the averages. One may work better than the other for different markets or trading styles. The other one is here: Have fun trading and keep smiling!
Zero Lag MACD Enhanced - Version 1.0*Zero Lag MACD indicator - Enhanced version 1.0*
Based on ZeroLag EMA - see Technical Analysis of Stocks and Commodities, April 2000
Original version by user Glaz. Thanks ! (see at the end of this description).
Tweaked by Albert Callisto
Displayed components:
Fast and slow "zero lag" moving averages
Histogram showing delta between the two moving averages
You can choose between SMA or EMA for the moving averages. They give slightly different results. Glaz had used SMA instead of EMA. Most "zero MACD" scripts are based upon EMA.
Usage is similar to the classic MACD and it can be integrated in an existing strategy, you will notice the crossing occurs earlier.
This is the original version by Glaz:
RSI Crossover AlertRSI Crossover Alert Indicator - User Guide
The RSI Crossover Alert Indicator is a comprehensive technical analysis tool that detects multiple types of RSI crossovers and generates real-time alerts. It combines traditional RSI analysis with signal lines, divergence detection, and multi-level crossing alerts.
1. Multiple Crossover Detection
- RSI/Signal Line Cross: Signals a primary trend change.
- RSI/Second Signal Cross: Confirmation signals for stronger trends.
- Level Crossings: Crosses of Overbought 70, Oversold 30, and Midline 50.
- Divergence Detection: Hidden and regular divergences for reversal signals.
2. Alert Types
- Alert: RSI > Signal
Description: Bullish momentum is building.
Signal: Consider long positions.
- Alert: RSI < Signal
Description: Bearish momentum is building.
Signal: Consider short positions.
- Alert: RSI > 70
Description: Entering the overbought zone.
Signal: Prepare for a potential reversal.
- Alert: RSI < 30
Description: Entering the oversold zone.
Signal: Watch for a bounce opportunity.
- Alert: RSI crosses 50
Description: A shift in momentum.
Signal: Trend confirmation.
3. Visual Components
- Lines: RSI blue, Signal orange, Second Signal purple
- Histogram: Visualizes momentum by showing the difference between RSI and the Signal line.
- Background Zones: Red overbought, Green oversold
- Markers: Up/down triangles to indicate crossovers.
- Info Table: Real-time RSI values and status.
Strategy 1: Classic Crossover
- Entry Long: RSI crosses above the Signal Line AND RSI is below 50.
- Entry Short: RSI crosses below the Signal Line AND RSI is above 50.
- Take Profit: On the opposite signal.
- Stop Loss: At the recent swing high/low.
Strategy 2: Extreme Zone Reversal
- Entry Long: RSI is below 30 and crosses above the Signal Line.
- Entry Short: RSI is above 70 and crosses below the Signal Line.
- Risk Management: Higher win rate but fewer signals. Use a minimum 2:1 risk-reward ratio.
Strategy 3: Divergence Trading
- Setup: Enable divergence alerts and look for price/RSI divergence. Wait for an RSI crossover for confirmation.
- Entry: Enter on the crossover after the divergence appears. Place the stop loss beyond the starting point of the divergence.
Strategy 4: Multi-Timeframe Confirmation
1. Check the higher timeframe e.g. Daily to identify the main trend.
2. Use the current timeframe e.g. 4H/1H for your entry.
3. Only enter in the direction of the main trend.
4. Use the RSI crossover as the entry trigger.
Optimal Settings by Market
- Forex Major Pairs
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 70/30
- Crypto High Volatility
RSI Length: 10-12, Signal Length: 6-8, Overbought/Oversold: 75/25
- Stocks Trending
RSI Length: 14-21, Signal Length: 9-12, Overbought/Oversold: 70/30
- Commodities
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 80/20
Risk Management Rules
1. Position Sizing: Never risk more than 1-2% on a single trade. Reduce size in ranging markets.
2. Stop Loss Placement: Place stops beyond the recent swing high/low for crossovers. Using an ATR-based stop is also effective.
3. Profit Taking: Take partial profits at a 1:1 risk-reward ratio. Switch to a trailing stop after reaching 2:1.
1. Filtering Signals
- Combine with volume indicators.
- Confirm the trend on a higher timeframe.
- Wait for candlestick pattern confirmation.
2. Avoid Common Mistakes
- Don't trade every single crossover.
- Avoid taking signals against a strong trend.
- Do not ignore risk management.
3. Market Conditions
- Trending Market: Focus on midline 50 crosses.
- Ranging Market: Look for reversals from overbought/oversold levels.
- Volatile Market: Widen the overbought/oversold levels.
- If you get too many false signals:
Increase the signal line period, add other confirmation indicators, or use a higher timeframe.
- If you are missing major moves:
Decrease the RSI length, shorten the signal line period, or check your alert settings.
Recommended Combinations
1. RSI + MACD: For dual momentum confirmation.
2. RSI + Bollinger Bands: For volatility-adjusted signals.
3. RSI + Volume: To confirm the strength of a signal.
4. RSI + Moving Averages: To use as a trend filter.
This indicator provides a comprehensive RSI analysis. Success depends on proper configuration, risk management, and combining signals with the overall market context. Start with the default settings, then optimize based on your trading style and market conditions.
PnL Bubble [%] | Fractalyst1. What's the indicator purpose?
The PnL Bubble indicator transforms your strategy's trade PnL percentages into an interactive bubble chart with professional-grade statistics and performance analytics. It helps traders quickly assess system profitability, understand win/loss distribution patterns, identify outliers, and make data-driven strategy improvements.
How does it work?
Think of this indicator as a visual report card for your trading performance. Here's what it does:
What You See
Colorful Bubbles: Each bubble represents one of your trades
Blue/Cyan bubbles = Winning trades (you made money)
Red bubbles = Losing trades (you lost money)
Bigger bubbles = Bigger wins or losses
Smaller bubbles = Smaller wins or losses
How It Organizes Your Trades:
Like a Photo Album: Instead of showing all your trades at once (which would be messy), it shows them in "pages" of 500 trades each:
Page 1: Your first 500 trades
Page 2: Trades 501-1000
Page 3: Trades 1001-1500, etc.
What the Numbers Tell You:
Average Win: How much money you typically make on winning trades
Average Loss: How much money you typically lose on losing trades
Expected Value (EV): Whether your trading system makes money over time
Positive EV = Your system is profitable long-term
Negative EV = Your system loses money long-term
Payoff Ratio (R): How your average win compares to your average loss
R > 1 = Your wins are bigger than your losses
R < 1 = Your losses are bigger than your wins
Why This Matters:
At a Glance: You can instantly see if you're a profitable trader or not
Pattern Recognition: Spot if you have more big wins than big losses
Performance Tracking: Watch how your trading improves over time
Realistic Expectations: Understand what "average" performance looks like for your system
The Cool Visual Effects:
Animation: The bubbles glow and shimmer to make the chart more engaging
Highlighting: Your biggest wins and losses get extra attention with special effects
Tooltips: hover any bubble to see details about that specific trade.
What are the underlying calculations?
The indicator processes trade PnL data using a dual-matrix architecture for optimal performance:
Dual-Matrix System:
• Display Matrix (display_matrix): Bounded to 500 trades for rendering performance
• Statistics Matrix (stats_matrix): Unbounded storage for complete statistical accuracy
Trade Classification & Aggregation:
// Separate wins, losses, and break-even trades
if val > 0.0
pos_sum += val // Sum winning trades
pos_count += 1 // Count winning trades
else if val < 0.0
neg_sum += val // Sum losing trades
neg_count += 1 // Count losing trades
else
zero_count += 1 // Count break-even trades
Statistical Averages:
avg_win = pos_count > 0 ? pos_sum / pos_count : na
avg_loss = neg_count > 0 ? math.abs(neg_sum) / neg_count : na
Win/Loss Rates:
total_obs = pos_count + neg_count + zero_count
win_rate = pos_count / total_obs
loss_rate = neg_count / total_obs
Expected Value (EV):
ev_value = (avg_win × win_rate) - (avg_loss × loss_rate)
Payoff Ratio (R):
R = avg_win ÷ |avg_loss|
Contribution Analysis:
ev_pos_contrib = avg_win × win_rate // Positive EV contribution
ev_neg_contrib = avg_loss × loss_rate // Negative EV contribution
How to integrate with any trading strategy?
Equity Change Tracking Method:
//@version=6
strategy("Your Strategy with Equity Change Export", overlay=true)
float prev_trade_equity = na
float equity_change_pct = na
if barstate.isconfirmed and na(prev_trade_equity)
prev_trade_equity := strategy.equity
trade_just_closed = strategy.closedtrades != strategy.closedtrades
if trade_just_closed and not na(prev_trade_equity)
current_equity = strategy.equity
equity_change_pct := ((current_equity - prev_trade_equity) / prev_trade_equity) * 100
prev_trade_equity := current_equity
else
equity_change_pct := na
plot(equity_change_pct, "Equity Change %", display=display.data_window)
Integration Steps:
1. Add equity tracking code to your strategy
2. Load both strategy and PnL Bubble indicator on the same chart
3. In bubble indicator settings, select your strategy's equity tracking output as data source
4. Configure visualization preferences (colors, effects, page navigation)
How does the pagination system work?
The indicator uses an intelligent pagination system to handle large trade datasets efficiently:
Page Organization:
• Page 1: Trades 1-500 (most recent)
• Page 2: Trades 501-1000
• Page 3: Trades 1001-1500
• Page N: Trades to
Example: With 1,500 trades total (3 pages available):
• User selects Page 1: Shows trades 1-500
• User selects Page 4: Automatically falls back to Page 3 (trades 1001-1500)
5. Understanding the Visual Elements
Bubble Visualization:
• Color Coding: Cyan/blue gradients for wins, red gradients for losses
• Size Mapping: Bubble size proportional to trade magnitude (larger = bigger P&L)
• Priority Rendering: Largest trades displayed first to ensure visibility
• Gradient Effects: Color intensity increases with trade magnitude within each category
Interactive Tooltips:
Each bubble displays quantitative trade information:
tooltip_text = outcome + " | PnL: " + pnl_str +
"\nDate: " + date_str + " " + time_str +
"\nTrade #" + str.tostring(trade_number) + " (Page " + str.tostring(active_page) + ")" +
"\nRank: " + str.tostring(rank) + " of " + str.tostring(n_display_rows) +
"\nPercentile: " + str.tostring(percentile, "#.#") + "%" +
"\nMagnitude: " + str.tostring(magnitude_pct, "#.#") + "%"
Example Tooltip:
Win | PnL: +2.45%
Date: 2024.03.15 14:30
Trade #1,247 (Page 3)
Rank: 5 of 347
Percentile: 98.6%
Magnitude: 85.2%
Reference Lines & Statistics:
• Average Win Line: Horizontal reference showing typical winning trade size
• Average Loss Line: Horizontal reference showing typical losing trade size
• Zero Line: Threshold separating wins from losses
• Statistical Labels: EV, R-Ratio, and contribution analysis displayed on chart
What do the statistical metrics mean?
Expected Value (EV):
Represents the mathematical expectation per trade in percentage terms
EV = (Average Win × Win Rate) - (Average Loss × Loss Rate)
Interpretation:
• EV > 0: Profitable system with positive mathematical expectation
• EV = 0: Break-even system, profitability depends on execution
• EV < 0: Unprofitable system with negative mathematical expectation
Example: EV = +0.34% means you expect +0.34% profit per trade on average
Payoff Ratio (R):
Quantifies the risk-reward relationship of your trading system
R = Average Win ÷ |Average Loss|
Interpretation:
• R > 1.0: Wins are larger than losses on average (favorable risk-reward)
• R = 1.0: Wins and losses are equal in magnitude
• R < 1.0: Losses are larger than wins on average (unfavorable risk-reward)
Example: R = 1.5 means your average win is 50% larger than your average loss
Contribution Analysis (Σ):
Breaks down the components of expected value
Positive Contribution (Σ+) = Average Win × Win Rate
Negative Contribution (Σ-) = Average Loss × Loss Rate
Purpose:
• Shows how much wins contribute to overall expectancy
• Shows how much losses detract from overall expectancy
• Net EV = Σ+ - Σ- (Expected Value per trade)
Example: Σ+: 1.23% means wins contribute +1.23% to expectancy
Example: Σ-: -0.89% means losses drag expectancy by -0.89%
Win/Loss Rates:
Win Rate = Count(Wins) ÷ Total Trades
Loss Rate = Count(Losses) ÷ Total Trades
Shows the probability of winning vs losing trades
Higher win rates don't guarantee profitability if average losses exceed average wins
7. Demo Mode & Synthetic Data Generation
When using built-in sources (close, open, etc.), the indicator generates realistic demo trades for testing:
if isBuiltInSource(source_data)
// Generate random trade outcomes with realistic distribution
u_sign = prand(float(time), float(bar_index))
if u_sign < 0.5
v_push := -1.0 // Loss trade
else
// Skewed distribution favoring smaller wins (realistic)
u_mag = prand(float(time) + 9876.543, float(bar_index) + 321.0)
k = 8.0 // Skewness factor
t = math.pow(u_mag, k)
v_push := 2.5 + t * 8.0 // Win trade
Demo Characteristics:
• Realistic win/loss distribution mimicking actual trading patterns
• Skewed distribution favoring smaller wins over large wins
• Deterministic randomness for consistent demo results
• Includes jitter effects to prevent visual overlap
8. Performance Limitations & Optimizations
Display Constraints:
points_count = 500 // Maximum 500 dots per page for optimal performance
Pine Script v6 Limits:
• Label Count: Maximum 500 labels per indicator
• Line Count: Maximum 100 lines per indicator
• Box Count: Maximum 50 boxes per indicator
• Matrix Size: Efficient memory management with dual-matrix system
Optimization Strategies:
• Pagination System: Handle unlimited trades through 500-trade pages
• Priority Rendering: Largest trades displayed first for maximum visibility
• Dual-Matrix Architecture: Separate display (bounded) from statistics (unbounded)
• Smart Fallback: Automatic page clamping prevents empty displays
Impact & Workarounds:
• Visual Limitation: Only 500 trades visible per page
• Statistical Accuracy: Complete dataset used for all calculations
• Navigation: Use page input to browse through entire trade history
• Performance: Smooth operation even with thousands of trades
9. Statistical Accuracy Guarantees
Data Integrity:
• Complete Dataset: Statistics matrix stores ALL trades without limit
• Proper Aggregation: Separate tracking of wins, losses, and break-even trades
• Mathematical Precision: Pine Script v6's enhanced floating-point calculations
• Dual-Matrix System: Display limitations don't affect statistical accuracy
Calculation Validation:
// Verified formulas match standard trading mathematics
avg_win = pos_sum / pos_count // Standard average calculation
win_rate = pos_count / total_obs // Standard probability calculation
ev_value = (avg_win * win_rate) - (avg_loss * loss_rate) // Standard EV formula
Accuracy Features:
• Mathematical Correctness: Formulas follow established trading statistics
• Data Preservation: Complete dataset maintained for all calculations
• Precision Handling: Proper rounding and boundary condition management
• Real-Time Updates: Statistics recalculated on every new trade
10. Advanced Technical Features
Real-Time Animation Engine:
// Shimmer effects with sine wave modulation
offset = math.sin(shimmer_t + phase) * amp
// Dynamic transparency with organic flicker
new_transp = math.min(flicker_limit, math.max(-flicker_limit, cur_transp + dir * flicker_step))
• Sine Wave Shimmer: Dynamic glowing effects on bubbles
• Organic Flicker: Random transparency variations for natural feel
• Extreme Value Highlighting: Special visual treatment for outliers
• Smooth Animations: Tick-based updates for fluid motion
Magnitude-Based Priority Rendering:
// Sort trades by magnitude for optimal visual hierarchy
sort_indices_by_magnitude(values_mat)
• Largest First: Most important trades always visible
• Intelligent Sorting: Custom bubble sort algorithm for trade prioritization
• Performance Optimized: Efficient sorting for real-time updates
• Visual Hierarchy: Ensures critical trades never get hidden
Professional Tooltip System:
• Quantitative Data: Pure numerical information without interpretative language
• Contextual Ranking: Shows trade position within page dataset
• Percentile Analysis: Performance ranking as percentage
• Magnitude Scaling: Relative size compared to page maximum
• Professional Format: Clean, data-focused presentation
11. Quick Start Guide
Step 1: Add Indicator
• Search for "PnL Bubble | Fractalyst" in TradingView indicators
• Add to your chart (works on any timeframe)
Step 2: Configure Data Source
• Demo Mode: Leave source as "close" to see synthetic trading data
• Strategy Mode: Select your strategy's PnL% output as data source
Step 3: Customize Visualization
• Colors: Set positive (cyan), negative (red), and neutral colors
• Page Navigation: Use "Trade Page" input to browse trade history
• Visual Effects: Built-in shimmer and animation effects are enabled by default
Step 4: Analyze Performance
• Study bubble patterns for win/loss distribution
• Review statistical metrics: EV, R-Ratio, Win Rate
• Use tooltips for detailed trade analysis
• Navigate pages to explore full trade history
Step 5: Optimize Strategy
• Identify outlier trades (largest bubbles)
• Analyze risk-reward profile through R-Ratio
• Monitor Expected Value for system profitability
• Use contribution analysis to understand win/loss impact
12. Why Choose PnL Bubble Indicator?
Unique Advantages:
• Advanced Pagination: Handle unlimited trades with smart fallback system
• Dual-Matrix Architecture: Perfect balance of performance and accuracy
• Professional Statistics: Institution-grade metrics with complete data integrity
• Real-Time Animation: Dynamic visual effects for engaging analysis
• Quantitative Tooltips: Pure numerical data without subjective interpretations
• Priority Rendering: Intelligent magnitude-based display ensures critical trades are always visible
Technical Excellence:
• Built with Pine Script v6 for maximum performance and modern features
• Optimized algorithms for smooth operation with large datasets
• Complete statistical accuracy despite display optimizations
• Professional-grade calculations matching institutional trading analytics
Practical Benefits:
• Instantly identify system profitability through visual patterns
• Spot outlier trades and risk management issues
• Understand true risk-reward profile of your strategies
• Make data-driven decisions for strategy optimization
• Professional presentation suitable for performance reporting
Disclaimer & Risk Considerations:
Important: Historical performance metrics, including positive Expected Value (EV), do not guarantee future trading success. Statistical measures are derived from finite sample data and subject to inherent limitations:
• Sample Bias: Historical data may not represent future market conditions or regime changes
• Ergodicity Assumption: Markets are non-stationary; past statistical relationships may break down
• Survivorship Bias: Strategies showing positive historical EV may fail during different market cycles
• Parameter Instability: Optimal parameters identified in backtesting often degrade in forward testing
• Transaction Cost Evolution: Slippage, spreads, and commission structures change over time
• Behavioral Factors: Live trading introduces psychological elements absent in backtesting
• Black Swan Events: Extreme market events can invalidate statistical assumptions instantaneously
Peak Reversal v3# Peak Reversal v3
## Summary
Peak Reversal v3 adds new configurability, clearer visuals, and a faster trader workflow. The release introduces a new Squeeze Detector , expanded Keltner Channels , and streamlined Momentum signals , with no repaints and improved performance. The menus have been reorganized and simplified. Color swatches have been added for better customization. All other colors will be derived from these swatches.
## Highlights
New Squeeze Detector to mark low-volatility periods and prepare for breakouts.
New: Bands are now fully configurable with independent MA length, ATR length, and multipliers.
Five moving average bases for bands: EMA (from v2), SMA, RMA, VMA, HMA.
Simplified color system: three swatches drive candles, on-chart marks, and band fill.
Reorganized menu with focused sections and tooltips for each parameter making the entire trader experience more intuitive.
No repaints and faster performance across calculations.
## Overview
Configuration : Pick from three color swatches and apply them to candles, plotted characters, and band fill for consistent chart context. Use the reorganized menu to reach Keltner settings, momentum signals, and squeeze detection without extra clicks; tooltips clarify each input.
Bands and averages: Choose the band basis from EMA, SMA, RMA, VMA, or HMA to match your strategy. Configure two bands independently by setting MA length, ATR length, and band multipliers for the inner and outer envelopes.
Signals : Select the band responsible for momentum signals. Choose wick or close as the price source for entries and exits. Control the window for extreme momentum with “Max Momentum Bars,” a setting now exposed in v3 for direct tuning.
Squeeze detection : The Squeeze Detector normalizes band width and uses percentile ranking to highlight volatility compression. When the market falls below a user-defined threshold, the indicator colors the region with a gradient to signal potential expansion.
## Details about major features and changes
### New
Squeeze Detector to highlight low-volatility conditions.
Five MA bases for bands: EMA, SMA, RMA, VMA, HMA.
“Max Momentum Bars” to cap the bars used for extreme momentum.
### Keltner channel improvements
Refactored Keltner settings for flexible inner and outer band control.
MA type selection added; band calculations updated for consistency.
Removed the third Keltner band to reduce noise and simplify setup.
### Display and signals
Gradient fills for band breakouts, mean deviations, and squeeze periods.
“Show Mean EMA?” set to true and default “Signal Band” set to “Inner.”
Clearer tooltips and input descriptions.
### Reliability and performance
No more repaints. The indicator waits for confirmation before drawing occurs.
Faster execution through targeted refactors.
All algorithms have been reviewed and now use a consistent logic, naming, and structure.
Vietnamese: Swing Low Detection with SMA Bands & BackgroundThis script detects **swing lows** using a dynamic SMA-based logic and visually highlights them on the chart.
Features
Customizable Moving Averages: Supports multiple MA types (SMA, EMA, WMA, RMA, HMA, DEMA, TEMA, VWMA).
Swing Low Visualization: Identifies swing lows when price closes below the SMA of lows and exits once price trades above the SMA of highs.
Smart Rectangles: Marks detected swing lows with labeled boxes for clear visual reference.
Background Highlights**: Dynamically shades the chart background when price breaks below recent swing lows, helping traders spot potential breakdown zones.
Configurable Parameters: Period length, rectangle length, and MA source can all be tuned.
Use Cases
Spot breakdown/bearish continuation signals when price closes under recent lows.
Combine with higher timeframe trend analysis for confluence.
Notes
* This tool is designed for **visual analysis** and is not a standalone buy/sell signal.
* Works best when combined with broader trend analysis, support/resistance levels, and volume.
Constance Brown Composite Index EnhancedWhat This Indicator Does
Implements Constance Brown's copyrighted Composite Index formula (1996) from her Master's thesis - a breakthrough oscillator that solves the critical problem where RSI fails to show divergences in long-horizon trends, providing early warning signals for major market reversals.
The Problem It Solves
Traditional RSI frequently fails to display divergence signals in Global Equity Indexes and long-term charts, leaving asset managers without warning of major price reversals. Brown's research showed RSI failed to provide divergence signals 42 times across major markets - failures that would have been "extremely costly for asset managers."
Key Components
Composite Line: RSI Momentum (9-period) + Smoothed RSI Average - the core breakthrough formula
Fast/Slow Moving Averages: Trend direction confirmation (13/33 periods default)
Bollinger Bands: Volatility envelope around the composite signal
Enhanced Divergence Detection: Significantly improved trend reversal timing vs standard RSI
Research-Proven Performance
Based on Brown's extensive study across 6 major markets (1919-2015):
42 divergence signals triggered where RSI showed none
33 signals passed with meaningful reversals (78% success rate)
Only 5 failures - exceptional performance in monthly/2-month timeframes
Tested on: German DAX, French CAC 40, Shanghai Composite, Dow Jones, US/Japanese Government Bonds
New Customization Features
Moving Average Types: Choose SMA or EMA for fast/slow lines
Optional Fills: Toggle composite and Bollinger band fills on/off
All Periods Adjustable: RSI length, momentum, smoothing periods
Visual Styling: Customize colors and line widths in Style tab
Default Settings (Original Formula)
RSI Length: 14
RSI Momentum: 9 periods
RSI MA Length: 3
SMA Length: 3
Fast SMA: 13, Slow SMA: 33
Bollinger STD: 2.0
Applications
Long-term investing: Monthly/2-month charts for major trend changes
Elliott Wave analysis: Maximum displacement at 3rd-of-3rd waves, divergence at 5th waves
Multi-timeframe: Pairs well with MACD, works across all timeframes
Global markets: Proven effective on equities, bonds, currencies, commodities
Perfect for serious traders and asset managers seeking the proven mathematical edge that traditional RSI cannot provide.
FUMO MA Cross Matrix 9/21/50/100/200 FUMO MA Cross Matrix is a flexible and advanced indicator designed for traders who rely on moving average crossovers as part of their strategy.
🔹 Key Features:
Supports 5 types of Moving Averages: EMA, SMA, SMMA (RMA), WMA, HMA.
Includes 5 standard MAs: 9, 21, 50, 100, 200 (toggle on/off individually).
Choose which MA crosses to monitor (9×21, 21×50, 50×100, 100×200, and 6 extended combinations).
On-chart signals (labels) when crosses occur.
Alerts system for every selected cross and also summary alerts (“Any Cross Up/Down”).
Option to trigger signals only on confirmed bars (no repaint).
Fully adjustable label visibility and signal style.
🔹 Use Cases:
Detect trend shifts (short-term vs long-term).
Build scalping, swing, or position trading strategies.
Combine with price action or volume analysis for stronger setups.
Quickly react to Golden Cross and Death Cross events.
🔹 How to Use:
Select your preferred MA type (EMA, SMA, etc.).
Enable the MAs (9, 21, 50, 100, 200) you want to plot.
Choose which crossovers to track in the settings.
Enable/disable on-chart labels for better visualization.
Set up alerts:
“CROSS UP/DOWN X>Y” for specific pairs.
“ANY CROSS UP/DOWN” for aggregated signals.
📌 Example Alerts
MA Cross UP 9>21 on BTCUSDT 15m @ 65432
Any selected MA cross DOWN on AAPL 1D @ 195.2
VHX EMA 135/315📈 EMA 135/315 Cross Strategy – Your Trend Compass with Smart Confirmations
🔍 Core Idea
The EMA 135/315 Cross strategy is a trend-following system.
It tracks two moving averages:
EMA 135 → the “fast” line that reacts to short-term price moves
EMA 315 → the “slow” line that reacts to the bigger trend
When the fast EMA crosses above the slow EMA → market momentum is turning up → BUY signal 🟢
When the fast EMA crosses below the slow EMA → momentum is turning down → SELL signal 🔴
This gives you a clear entry trigger — no guessing, no overcomplication.
✨ On Your Chart
BUY/SELL Arrows
🟢 Green arrow = bullish cross → trend turning up
🔴 Red arrow = bearish cross → trend turning down
Trend Info Panel (Top Left)
Current Trend: BUY / SELL / Neutral
Last Cross: how many bars ago it happened
EMA Gap in %: measures the strength of the trend
Status: “Approaching” if EMAs are getting close → possible cross soon
Automatic TP/SL Levels
📈 TP line (+2% from entry)
📉 SL line (–0.5% from entry)
Saves time — you instantly see your target and protection
EMA Distance Meter
Big % gap = strong trend momentum 🚀
Small % gap = weak or sideways market ⚠️
Real-Time Alerts
You get notified when a cross happens, even if you’re away from the screen
🧠 The Logic Behind It
The EMA 135 reacts faster → it reflects short-term momentum
The EMA 315 moves slower → it reflects the main trend
When the fast EMA overtakes the slow EMA: short-term strength now aligns with the long-term trend → higher probability of a sustained move
The gap % tells you how strong the alignment is — large gap = cleaner moves, small gap = market in transition
“Approaching” status warns that the EMAs are converging, which often happens before a reversal
📊 Boosting the Strategy with Volume Analysis
The EMA cross is a strong trigger, but volume confirms the quality of the move:
High Volume + Cross → more reliable signal, as strong market participation is pushing the trend
Low Volume + Cross → caution, the move might be weak or a false breakout
💡 Tip:
Check the volume histogram or a volume-based indicator (e.g., Volume Profile, OBV).
On a BUY signal: volume should spike above the recent average.
On a SELL signal: watch for strong selling volume bars.
📍 Adding Support & Resistance for Precision
Support and resistance levels help filter out bad trades and optimize entries:
Best BUY setups:
EMA 135 crosses above EMA 315 near a known support zone
Bonus if volume confirms the move
Avoid buying directly into a strong resistance
Best SELL setups:
EMA 135 crosses below EMA 315 near a known resistance zone
Bonus if selling volume is strong
Avoid selling directly into a major support
💡 Use tools like horizontal lines, previous highs/lows, and Volume Profile nodes to spot these zones.
📈 Best Usage Practices
Timeframes
Lower timeframes (1m–5m) → more signals, but more noise → best for scalping with extra filters
Always Combine With Confirmation
EMA Cross = Trigger
Volume spike = Confirmation
S/R zone in your favor = High-probability setup
Manage Risk
Start with the built-in TP/SL
Adjust SL if volatility is higher than usual
Consider trailing stop once price moves in your favor
Avoid Sideways Markets
If EMA gap % is very small and crosses happen often → stand aside until a clear direction forms
Use Alerts
Set alerts for BUY & SELL crosses so you never miss a setup
In short:
This isn’t just an EMA cross indicator — it’s a trend system with built-in risk management, strength measurement, and pre-trade preparation. Combine it with volume confirmation and smart use of support/resistance, and you turn a simple signal into a high-probability trading edge.
