Price Action Trading System v0.3 by JustUncleL with modifcationsThe base of this script is the Price Action Trading System from JustUncle .
I have first combined it with script ADX and DI by BeikabuOyaji to indicate when the +DI is above the -DI and the ADX is above 20. This is represented by crosses at the top of the page: green indicating that the +DI is above the -DI and ADX above 20, and red if -DI is above the +DI and ADX above 20. If the ADX is increasing in slope while the +DI is above the -DI, an up green arrow is shown at the bottom of the page, indicating an increase in this trend, and the slope of the ADX is increasing and the -DI is above the +DI, a down arrow is shown at the bottom. One could think to a green cross with a green up arrow as a potential buy opportunity, and a red cross with a red down arrow as a potential sell opportunity.
Next, I have combined this script with the Indicator: WaveTrend Oscillator from Lazybear . If the oscillator has readings below -45 and the slope of the line is increasing, a green diamond appears above the chart. This indicates a potential buy opportunity. If the oscillator has readings above 50 and the slope of the line is decreasing, a red diamond appears above the chart. This indicates a potential sell opportunity. Now if the slope of the oscillator is rising significantly but does not hit the -45 threshold to start its increase, but is negative in value, a green flag appears at the top of the page. This represents a potential buy opportunity. If the slope of the oscillator is significantly decreasing and is positive in value, a red flag appears at the bottom of the page. This represents a potential sell opportunity.
The base of this script, the Price Action Trading System v0.3 by JustUncle , has many of its own features that I have kept. If the MACD is positive, the background colour is green. If it is negative, the colour is red. If the CCI and RSI indicate an oversold opportunity and the MACD is positive, you get an up olive arrow below the chart. If they indicate an overbought opportunity and the MACD is negative, you get a red down arrow above the chart. If the CCI value stays oversold after a green arrow, the candle chart turns turquoise, and if overbought, turns black after a red arrow.
You can use these indicators in combination to help you with your trading strategy.
在腳本中搜尋"wave"
Dominant Cycle Tuned RsiIntroduction
Adaptive technical indicators are importants in a non stationary market, the ability to adapt to a situation can boost the efficiency of your strategy. A lot of methods have been proposed to make technical indicators "smarters" , from the use of variable smoothing constant for exponential smoothing to artificial intelligence.
The dominant cycle tuned rsi depend on the dominant cycle period of the market, such method allow the rsi to return accurate peaks and valleys levels. This indicator is an estimation of the cycle finder tuned rsi proposed by Lars von Thienen published in Decoding the Hidden Market Rhythm/Fine-tuning technical indicators using the dominant market vibration/2010 using the cycle measurement method described by John F.Ehlers in Cybernetic Analysis for Stocks and Futures .
The following section is for information purpose only, it can be technical so you can skip directly to the The Indicator section.
Frequency Estimation and Maximum Entropy Spectral Analysis
“Looks like rain,” said Tom precipitously.
Tom would have been a great weather forecaster, but market patterns are more complex than weather ones. The ability to measure dominant cycles in a complex signal is hard, also a method able to estimate it really fast add even more challenge to the task. First lets talk about the term dominant cycle , signals can be decomposed in a sum of various sine waves of different frequencies and amplitudes, the dominant cycle is considered to be the frequency of the sine wave with the highest amplitude. In general the highest frequencies are those who form the trend (often called fundamentals) , so detrending is used to eliminate those frequencies in order to keep only mid/mid - highs ones.
A lot of methods have been introduced but not that many target market price, Lars von Thienen proposed a method relying on the following processing chain :
Lars von Thienen Method = Input -> Filtering and Detrending -> Discrete Fourier Transform of the result -> Selection using Bartels statistical test -> Output
Thienen said that his method is better than the one proposed by Elhers. The method from Elhers called MESA was originally developed to interpret seismographic information. This method in short involve the estimation of the phase using low amount of information which divided by 360 return the frequency. At first sight there are no relations with the Maximum entropy spectral estimation proposed by Burg J.P. (1967). Maximum Entropy Spectral Analysis. Proceedings of 37th Meeting, Society of Exploration Geophysics, Oklahoma City.
You may also notice that these methods are plotted in the time domain where more classic method such as : power spectrum, spectrogram or FFT are not. The method from Elhers is the one used to tune our rsi.
The Indicator
Our indicator use the dominant cycle frequency to calculate the period of the rsi thus producing an adaptive rsi . When our adaptive rsi cross under 70, price might start a downtrend, else when our adaptive rsi crossover 30, price might start an uptrend. The alpha parameter is a parameter set to be always lower than 1 and greater than 0. Lower values of alpha minimize the number of detected peaks/valleys while higher ones increase the number of those. 0.07 for alpha seems like a great parameter but it can sometimes need to be changed.
The adaptive indicator can also detect small top/bottoms of small periods
Of course the indicator is subject to failures
At the end it is totally dependent of the dominant cycle estimation, which is still a rough method subject to uncertainty.
Conclusion
Tuning your indicator is a great way to make it adapt to the market, but its also a complex way to do so and i'm not that convinced about the complexity/result ratio. The version using chart background will be published separately.
Feel free to tune your indicators with the estimator from elhers and see if it provide a great enhancement :)
Thanks for reading !
References
for the calculation of the dominant cycle estimator originally from www.davenewberg.com
Decoding the Hidden Market Rhythm (2010) Lars von Thienen
Ehlers , J. F. 2004 . Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading . Wiley
Ehlers Simple DecyclerThis indicator was originally developed by John F. Ehlers (Stocks & Commodities, V.33:10 (September, 2015): "Decyclers").
Mr. Ehlers suggested a way to improve trend identification using high-pass filters. The basic smoothers like SMA, low-pass filters, have considerable lag in their display. Mr. Ehlers applied the high-pass filter and subtracted the high-pass filter output from the time series input. Doing these steps he removed high-frequency short-wavelength components (the ones causing the wiggles) from the time series.
As a result he got a special series of the low-frequency components with virtually no lag - the Decycler.
The Decycler is plotted with two additional lines (the percent-shifts of Decycler) and together they form a hysteresis band.
If the prices are above the upper hysteresis line, then the market is in an uptrend . If the prices are below the low hysteresis line, then the market is in a downtrend . Prices within the hysteresis band are trend-neutral .
Simple TrenderOriginates from:
I was reading some Impulse Trading literature by A. Elder.. In it, someone named Kerry Lovvorn proposed "An End of Day Trend Following System" for someone lazy.
Originally it is just price closing above an 8 ema (low) for long. Exit when price closes below an 8 ema (low). The opposite for a short position.
Conditions: Buy when price closed below ema (low) for two bars or more, then closes above. Opposite for a short position. I do not follow this condition. Though it may help with whipsaw.
My condition is when price closes above the 26 ema (low) (works the best for me) I place orders above the initial crossing bars high. Opposite for lows.
I look for stocks that are low in price to go long on. I want the run from 2's to 15's
I look for stocks that are mid-teens/20's in price to go short on. I want the run from 20's to 2's
I look for stock with news and earnings that are already running (up or down) to play the pullback.
These conditions can easily be scanned for on thinkorswim
From first glance, the system looks like CMsling shotsystem. Although, I plagiarized some parts of the codes, because I am inept when it comes to that shit, it differs as it is not a moving average crossover system.
It is a price crossing over concept. A moving average VWAP is used for best entries on pullbacks.
Purpose:
--To catch the majority of a trend/wave/run.
--To identify pullback areas to go long or short while in midst of trend. To catch pullbacks off news and earning runners.
--To catch the initial start of trend with clear rules to enter
--Clear rules to exit
Issues
--possibilities of getting ninja sliced the fuck up. Can be mitigated by entering stocks with decent average volume. And also only going long above 200 ema and short below it. ADX won't work, at the initial start of the trend it will show not trending. Can look at blow off volume at the bottom followed by increase in buying for long and vice versa for short.
--Can give some huge gains away through gap ups or gap downs from news or earnings during trend. However, can get huge gain on gaps from news or earning. Nature of the game.
--Need some brass balls and a supply of pepto to stomach through some of the pullbacks. Gut wrenching seeing big gains dwindle. But they all even out at the end, you hope. (see NBEV and IGC, and CRON and others. shit don't go in straight lines, homie)
Pros
--It's simple and easy. Overall, you profit
--works with any security
Cons
--It can be stressful.
--does not work well on lower time frames. Do not recommend going below 15 minutes
--Possibility of working on 5 minutes with a time frame breakout strategy (15,30 min).
Couple it with LazyBear "Weis Wave Volume" indicator. Works well for pullback entries.
Enjoy. Ride some waves.
Godmode RSIbased on the popular Godmode Indicator with modifications by LEGION, LAZYBEAR, Ni6HTH4wK, xSilas, oh92, sco77m4r7in
All Credit belongs to them. THX Guys!
This is a Combination of a RSI and Godmode.
RSI has a Simple or Exponential Moving Average, Histogram Color Changes when the RSI reaches the Overbought/Oversold Zones.
Godmode is basicly the same as the Original one only scaled down a bit with slightly adjusted Caution Signal Zones which i like more. I also added the Option to adjust the Length of the 2nd Wavetrend SMA. Removed the Wavetrend Area because it doesnt have any use for me.
Hope you like it.
BE-EMA(12,26) (Blue Empire Exponential Moving Average)
Simple EMA where you get a CROSS mark between EMA 12 and EMA 26.
Each time a cross happens, a spot gets created.
If it's cyan, it goes up.
If it's magenta, it goes down.
I'm studying Trading at Blue Empire Academy, if you want to know more send me a PM.
Wave Analysis study the wave's behavior and tries to predict by using trendlines, elliot waves, fibonacci retracements, and EMAs basically.
In this Indicator, It's a confirmation when EMA 12 goes over to confirm the price may go up. and Vice versa.
Hope you like, please share if you think it's useful and comment if you think this can be better.
Thank you again for reading
>> This is just an indicator, it doesn't predict the future. Use it at your own risk. <<
##########
All the credits to @tracks, a genius who helped me polish the code. :] thank you.
Periodic ChannelThis indicator try to create a channel by summing a re-scaled and readapted sinusoidal wave form to the price mean.
The length parameter control the speed of the sinusoidal wave form, this parameter is not converted to a sine wave period for allowing a better estimation, higher length's work better but feel free to try shorter periods.
The invert parameter invert the sinusoidal wave.
Each bands represent possible return points, the higher the band the higher the probability.
Inverted sin wave exemple
The performance of the indicator is subjective to the main estimation (blue line), select the parameter that best fit the blue line to the price.
Best ragards
CMYK XIAM OPEN◊ Introduction
This is project XIAM, a work in progress.
Recently i came across the repainting problem.
Since then i haven't seen any bot-code that makes > 5% profit in two weeks with 0.25% fees/trade.
People who make good bots either bluff or don't share the code.
they let you rent it.
I aim to understand, learn it, write it myself. And share my findings with whoever shares with me.
◊ Origin
Based on RMI (RSI with momentum) and SMA, and values derived from those.
◊ Usage
Currently an investigative script.
◊ Theoretical Approaches
Philosophy α :: Cleansignal
:: Cleaning up the signal, from irregularities that cause unpredictable results.
Merging available tickers of a pair into one.
Merging available tickers of different coins into one in the correct proportion. (eg. Crypto market cap)
Removing Jitter, and smoothing signal without delay.
Philosophy β :: Rythmic
:: Syncing into the rythm's, to never miss the que, and trade on every theoretical low/high
Searching Amplitude, Period, Phase Shift, Frequency's of the carrier waves.
Marking Acrivity/inactivity of the carrier waves.
Partial Fractal repetition asses-able with above data?
Philosophy γ :: consequential
:: Seeking for Indicatory events and causal relations
Probability / reward.
Confirmation and culmination.
...
◊ Community
Wanna share your findings ? or need help resolving a problem ?
CMYK :: discord.gg
AUTOTVIEW :: discordapp.com
rem sim v0.1every alt-coin has similarity.
cause of bitcoin.
always i want to delete that similarity and read the true(?) value of each coin.
and i made some script for that, but not good enough.
this one is different.
Rem Sim (rs) removes the similarity very effectively.
it make avg WaveTrend from nxt, strat, steem, ...
and that is the similarity
and it show true(?) WaveTrend without similarity.
so if the alt-coin move like other alt-coin, the WT almost 0.
sorry my bad english.
if you dont understand my english. just look at that chart.
also you can see source code.
--------
대부분의 알트가 어느정도 비슷한 차트를 가지는데, 그 유사성을 제거하면 어떤 모양인지 궁금해서 만들었어요.
전에 만들었던 비트코인의 영향력을 제거해주는 아이디어는 실제론 별 효용이 없는데 이건 좀 쓸만해보이네요.
웨이브트렌드의 모양으로 보여줍니다.
FLD's - Future Lines of Demarcation Backtest An FLD is a line that is plotted on the same scale as the price and is in fact the
price itself displaced to the right (into the future) by (approximately) half the
wavelength of the cycle for which the FLD is plotted. There are three FLD's that can be
plotted for each cycle:
An FLD based on the median price.
An FLD based on the high price.
An FLD based on the low price.
FLD - Future Lines of Demarcation Strategy An FLD is a line that is plotted on the same scale as the price and is in fact the
price itself displaced to the right (into the future) by (approximately) half the
wavelength of the cycle for which the FLD is plotted. There are three FLD's that can be
plotted for each cycle:
An FLD based on the median price.
An FLD based on the high price.
An FLD based on the low price.
FLD's - Future Lines of Demarcation An FLD is a line that is plotted on the same scale as the price and is in fact the
price itself displaced to the right (into the future) by (approximately) half the
wavelength of the cycle for which the FLD is plotted. There are three FLD's that can be
plotted for each cycle:
An FLD based on the median price.
An FLD based on the high price.
An FLD based on the low price.
AlphaFlow: Oscillator PanelAlphaFlow: Oscillator Panel
The AlphaFlow: Oscillator Panel indicator is a versatile multi-tool designed to provide a comprehensive view of momentum, volatility, and trend strength across different timeframes. This script combines several popular technical analysis tools into a single dashboard for faster decision-making.
Key Features:
WaveTrend Oscillator (WT1 and WT2): Tracks price momentum to help identify potential reversals or trend continuations.
RSI and BBWP : Measures relative strength and volatility compression/expansion.
VWAP-MACD and OBV : Includes volume-based momentum insights and higher timeframe confirmations.
Multi-Timeframe Confluence : Highlights if various oscillators align across multiple timeframes.
Dynamic Table : A dashboard that updates in real time, providing numeric values and playful narratives for easier reading.
Configurable Text Size : Customize the table’s text size for better visibility.
Anchor, Trigger, Snake Eye Labels : These markers appear when WT1 crosses significant thresholds:
Anchor (A): Marks a potential base or bottoming signal.
Trigger (T): Confirms a potential momentum reversal.
Snake Eyes: Indicates particularly strong or rare reversal conditions.
How to Use:
Load the indicator on your chart.
Adjust input parameters like RSI length, BBWP length, CMF length, and others to suit your market and timeframe.
Use the Decision Table: It updates automatically on the latest bar to show oscillator readings, trend state, and multi-timeframe confluence.
Monitor for alignment: Bullish or bearish signals are highlighted when all components agree.
Look for Anchor, Trigger, Snake Eye labels: These help identify key turning points.
Combine with your trading strategy: This indicator is a decision-support tool and should be used with other forms of analysis and risk management.
Important:
This script does not provide financial advice. It’s a technical analysis tool designed to aid traders in decision-making and should be used at your own risk.
Quantum State Superposition Indicator (QSSI)Quantum State Superposition Indicator (QSSI) - Where Physics Meets Finance
The Quantum Revolution in Market Analysis
After months of research into quantum mechanics and its applications to financial markets, I'm thrilled to present the Quantum State Superposition Indicator (QSSI) - a groundbreaking approach that models price action through the lens of quantum physics. This isn't just another technical indicator; it's a paradigm shift in how we understand market behavior.
The Theoretical Foundation
Quantum Superposition in Markets
In quantum mechanics, particles exist in multiple states simultaneously until observed. Similarly, markets exist in a superposition of potential states (bullish, bearish, neutral) until a significant volume event "collapses" the wave function into a definitive direction.
The mathematical framework:
Wave Function (Ψ): Represents the market's quantum state as a weighted sum of all possible states:
Ψ = Σ(αᵢ × Sᵢ)
Where αᵢ are probability amplitudes and Sᵢ are individual quantum states.
Probability Amplitudes: Calculated using the Born rule, normalized so Σ|αᵢ|² = 1
Observation Operator: Volume/Average Volume ratio determines observation strength
The Five Quantum States
Momentum State: Short-term price velocity (EMA of returns)
Mean Reversion State: Deviation from equilibrium (normalized z-score)
Volatility Expansion State: ATR relative to historical average
Trend Continuation State: Long-term price positioning
Chaos State: Volatility of volatility (market uncertainty)
Each state contributes to the overall wave function based on current market conditions.
Wave Function Collapse
When volume exceeds the observation threshold (default 1.5x average), the wave function "collapses," committing the market to a direction. This models how institutional volume forces markets out of uncertainty into trending states.
Collapse Detection Formula:
Collapse = Volume > (Threshold × Average Volume)
Direction = Sign(Ψ) at collapse moment
Advanced Quantum Concepts
Heisenberg Uncertainty Principle
The indicator calculates market uncertainty as the product of price and momentum
uncertainties:
ΔP × ΔM = ℏ (market uncertainty constant)
This manifests as dynamic uncertainty bands that widen during unstable periods.
Quantum Tunneling
Calculates the probability of price "tunneling" through resistance/support barriers:
P(tunnel) = e^(-2×|barrier_height|×√coherence_length)
Unlike classical technical analysis, this gives probability of breakouts before they occur.
Entanglement
Measures the quantum correlation between price and volume:
Entanglement = |Correlation(Price, Volume, lookback)|
High entanglement suggests coordinated institutional activity.
Decoherence
When market states lose quantum properties and behave classically:
Decoherence = 1 - Σ(amplitude²)
Indicates trend emergence from quantum uncertainty.
Visual Innovation
Probability Clouds
Three-tier probability distributions visualize market uncertainty:
Inner Cloud (68%): One standard deviation - most likely price range
Middle Cloud (95%): Two standard deviations - probable extremes
Outer Cloud (99.7%): Three standard deviations - tail risk zones
Cloud width directly represents market uncertainty - wider clouds signal higher entropy states.
Quantum State Visualization
Colored dots represent individual quantum states:
Green: Momentum state strength
Red: Mean reversion state strength
Yellow: Volatility state strength
Dot brightness indicates amplitude (influence) of each state.
Collapse Events
Aqua Diamonds (Above): Bullish collapse - upward commitment
Pink Diamonds (Below): Bearish collapse - downward commitment
These mark precise moments when markets exit superposition.
Implementation Details
Core Calculations
Feature Extraction: Normalize price returns, volume ratios, and volatility measures
State Calculation: Compute each quantum state's value
Amplitude Assignment: Weight states by market conditions and observation strength
Wave Function: Sum weighted states for final market quantum state
Visualization: Transform quantum values to price space for display
Performance Optimization
- Efficient array operations for state calculations
- Single-pass normalization algorithms
- Optimized correlation calculations for entanglement
- Smart label management to prevent visual clutter
Trading Applications:
Signal Generation
Bullish Signals:
- Positive wave function during collapse
- High tunneling probability at support
- Coherent market state with bullish bias
Bearish Signals:
- Negative wave function during collapse
- High tunneling probability at resistance
- Decoherent state transitioning bearish
Risk Management
Uncertainty-Based Position Sizing:
Narrow clouds: Normal position size
Wide clouds: Reduced position size
Extreme uncertainty: Stay flat
Quantum Stop Losses:
- Place stops outside probability clouds
- Adjust for Heisenberg uncertainty
- Respect quantum tunneling levels
Market Regime Recognition
Quantum Coherent (Superposed):
- Market in multiple states
- Avoid directional trades
- Prepare for collapse
Quantum Decoherent (Classical):
-Clear trend emergence
- Follow directional signals
- Traditional analysis applies
Advanced Features
Adaptive Dashboards
Quantum State Panel: Real-time wave function, dominant state, and coherence status
Performance Metrics: Win rate, signal frequency, and regime analysis
Information Guide: Comprehensive explanation of all quantum concepts
- All dashboards feature adjustable sizing for different screen resolutions.
Multi-Timeframe Quantum Analysis
The indicator adapts to any timeframe:
Scalping (1-5m): Short coherence length, sensitive thresholds
Day Trading (15m-1H): Balanced parameters
Swing Trading (4H-1D): Long coherence, stable states
Alert System
Sophisticated alerts for:
- Wave function collapse events
- Decoherence transitions
- High tunneling probability
- Strong entanglement detection
Originality & Innovation
This indicator introduces several firsts:
Quantum Superposition: First to model markets as quantum systems
Wave Function Collapse: Original volume-triggered state commitment
Tunneling Probability: Novel breakout prediction method
Entanglement Metrics: Unique price-volume quantum correlation
Probability Clouds: Revolutionary uncertainty visualization
Development Journey
Creating QSSI required:
- Deep study of quantum mechanics principles
- Translation of physics equations to market context
- Extensive backtesting across multiple markets
- UI/UX optimization for trader accessibility
- Performance optimization for real-time calculation
- The result bridges cutting-edge physics with practical trading.
Best Practices
Parameter Optimization
Quantum States (2-5):
- 2-3 for simple markets (forex majors)
- 4-5 for complex markets (indices, crypto)
Coherence Length (10-50):
- Lower for fast markets
- Higher for stable markets
Observation Threshold (1.0-3.0):
- Lower for active markets
- Higher for thin markets
Signal Confirmation
Always confirm quantum signals with:
- Market structure (support/resistance)
- Volume patterns
- Correlated assets
- Fundamental context
Risk Guidelines
- Never risk more than 2% per trade
- Respect probability cloud boundaries
- Exit on decoherence shifts
- Scale with confidence levels
Educational Value
QSSI teaches advanced concepts:
- Quantum mechanics applications
- Probability theory
- Non-linear dynamics
- Risk management
- Market microstructure
Perfect for traders seeking deeper market understanding.
Disclaimer
This indicator is for educational and research purposes only. While quantum mechanics provides a fascinating framework for market analysis, no indicator can predict future prices with certainty. The probabilistic nature of both quantum mechanics and markets means outcomes are inherently uncertain.
Always use proper risk management, conduct thorough analysis, and never risk more than you can afford to lose. Past performance does not guarantee future results.
Conclusion
The Quantum State Superposition Indicator represents a revolutionary approach to market analysis, bringing institutional-grade quantum modeling to retail traders. By viewing markets through the lens of quantum mechanics, we gain unique insights into uncertainty, probability, and state transitions that classical indicators miss.
Whether you're a physicist interested in finance or a trader seeking cutting-edge tools, QSSI opens new dimensions in market analysis.
"The market, like Schrödinger's cat, exists in multiple states until observed through volume."
* As you may have noticed, the past two indicators I've released (Lorentzian Classification and Quantum State Superposition) are designed with strategy implementation in mind. I'm currently developing a stable execution platform that's completely unique and moves away from traditional ATR-based position sizing and stop loss systems. I've found ATR-based approaches to be unreliable in volatile markets and regime transitions - they often lag behind actual market conditions and can lead to premature exits or oversized positions during volatility spikes.
The goal is to create something that adapts to market conditions in real-time using the quantum and relativistic principles we've been exploring. Hopefully I'll have something groundbreaking to share soon. Stay tuned!
Trade with quantum insight. Trade with QSSI .
— Dskyz , for DAFE Trading Systems
Macd, Wt Cross & HVPMacd Wt Cross & HVP – Advanced Multi-Signal Indicator
This script is a custom-designed multi-signal indicator that brings together three proven concepts to provide a complete view of market momentum, reversals, and volatility build-ups. It is built for traders who want to anticipate key market moves, not just react to them.
Why This Combination ?
While each tool has its strengths, their combined use creates powerful signal confluence.
Instead of juggling multiple indicators separately, this script synchronizes three key perspectives into a single, intuitive display—helping you trade with greater clarity and confidence.
1. MACD Histogram – Momentum and Trend Clarity
At the core of the indicator is the MACD histogram, calculated as the difference between two exponential moving averages (EMAs).
Color-coded bars represent momentum direction and intensity:
Green / blue bars: bullish momentum
Red / pink bars: bearish momentum
Color intensity shows acceleration or weakening of trend.
This visual makes it easy to detect trend shifts and momentum divergence at a glance.
2. WT Cross Signals – Early Reversal Detection
Overlaid on the histogram are green and red dots, based on the logic of the WaveTrend oscillator cross:
Green dots = potential bullish cross (buy signal)
Red dots = potential bearish cross (sell signal)
These signals are helpful for identifying reversal points during both trending and ranging phases.
3. Historical Volatility Percentile (HVP) – Volatility Compression Zones
Behind the histogram, purple vertical zones highlight periods of low historical volatility, based on the HVP:
When volatility compresses below a specific threshold, these zones appear.
Such periods are often followed by explosive price moves, making them prime areas for pre-breakout positioning.
By integrating HVP, the script doesn’t just tell you where the trend is—it tells you when the trend is likely to erupt.
How to Use This Script
Use the MACD histogram to confirm the dominant trend and its strength.
Watch for WT Cross dots as potential entry/exit signals in alignment or divergence with the MACD.
Monitor HVP purple zones as warnings of incoming volatility expansions—ideal moments to prepare for breakout trades.
Best results occur when all three elements align, offering a high-probability trade setup.
What Makes This Script Original?
Unlike many mashups, this script was not created by simply merging indicators. Each component was carefully integrated to serve a specific, complementary purpose:
MACD detects directional bias
WT Cross adds precision timing
HVP anticipates volatility-based breakout timing
This results in a strategic tool for traders, useful on multiple timeframes and adaptable to different trading styles (trend-following, breakout, swing).
WaveFunction MACD (TechnoBlooms)WaveFunction MACD — The Next Generation of Market Momentum
WaveFunction MACD is an advanced hybrid momentum indicator that merges:
• The classical MACD crossover logic (based on moving averages)
• Wave physics (modeled through phase energy and cosine functions)
• Hilbert Transform theory from signal processing
• The concept of a wavefunction from quantum mechanics, where price action is seen as a probabilistic energy wave—not just a trend.
✨ Key Features of WaveFunction MACD
• Wave Energy Logic : Instead of using just price and MA differences, this indicator computes phase-corrected momentum using the cosine of the wave phase angle — revealing the true energy behind market moves.
• Phase-Based Trend Detection : It reads cycle phases using Hilbert Transform-like logic, allowing you to spot momentum before it becomes visible in price.
• Ultra-Smooth Flow : The main line and histogram are built to follow price flow smoothly — eliminating much of the noise found in traditional MACD indicators.
• Signal Amplification via Energy Histogram : The histogram doesn’t just show momentum changes — it shows the intensity of wave energy, allowing you to confirm the strength of the trend.
• Physics-Driven Structure : The algorithm is rooted in real-world wave mechanics, bringing a scientific edge to trading — ideal for traders who believe in natural models like cycles and harmonics.
• Trend Confirmation & Early Reversals : It can confirm strong trends and also catch subtle shifts that often precede big reversals — giving you both reliability and anticipation.
• Ready for Fusion : Designed to work seamlessly with liquidity zones, price action, order blocks, and structure trading — a perfect fit for modern trading systems.
🧪 The Science Behind It
This tool blends:
• Hilbert Transform: Measures the phase of a waveform (price cycle) to detect turning points
• Cosine Phase Energy: Calculates true wave energy using the cosine of the phase angle, revealing the strength behind price movements
• Quantum Modeling: Views price like a wavefunction, offering predictive insight based on phase dynamics
Multi-Factor Reversal AnalyzerMulti-Factor Reversal Analyzer – Quantitative Reversal Signal System
OVERVIEW
Multi-Factor Reversal Analyzer is a comprehensive technical analysis toolkit designed to detect market tops and bottoms with high precision. It combines trend momentum analysis, price action behavior, wave oscillation structure, and volatility breakout potential into one unified indicator.
This indicator is not a random mix of tools — each module is carefully selected for a specific purpose. When combined, they form a multi-dimensional view of the market, merging trend analysis, momentum divergence, and volatility compression to produce high-confidence signals.
Why Combine These Modules?
Module Combination Ideas & How to Use Them
Factor A: Trend Detector + Gold Zone
Concept:
• The Trend Detector (light yellow histogram) evaluates market strength:
• Histogram trending downward or staying below 50 → bearish conditions;
• Trending upward or staying above 50 → bullish conditions.
• The Gold Zone identifies areas of volatility compression — typically a prelude to explosive market moves.
Practical Application:
• When the Gold Zone appears and the Trend Detector is bearish → likely downside move;
• When the Gold Zone appears and the Trend Detector is bullish → likely upside breakout.
• Note: The Gold Zone does not mean the bottom is in. It is not a buy signal on its own — always combine it with other modules for directional bias.
Factor B: PAI + Wave Trend
Concept:
• PAI (Price Action Index) is a custom oscillator that combines price momentum with volatility dispersion, displaying strength zones:
• Green area → bullish dominance;
• Red area → bearish pressure.
• Wave Trend offers smoothed crossover signals via the main and signal lines.
Practical Application:
• When PAI is in the green zone and Wave Trend makes a bullish crossover → potential reversal to the upside;
• When PAI is in the red zone and Wave Trend shows a bearish crossover → potential start of a downtrend.
Factor C: Trend Detector + PAI
Concept:
• Combines directional trend strength with price action strength to confirm setups via confluence.
Practical Application:
• Trend Detector histogram bottoms out + PAI enters the green zone → high chance of upward reversal;
• Histogram tops out + PAI in the red zone → increased likelihood of downside continuation.
Multi-Factor Confluence (Advanced Use)
• When Trend Detector, PAI, and Wave Trend all align in the same direction (bullish or bearish), the directional signal becomes significantly more reliable.
• This setup is especially useful for trend-following or swing trade entries.
KEY FEATURES
1. Multi-Layer Reversal Logic
• Combines trend scoring, oscillator divergence, and volatility squeezes for triangulated reversal detection.
• Helps traders distinguish between trend pullbacks and true reversals.
2. Advanced Divergence Detection
• Detects both regular and hidden divergences using pivot-based confirmation logic.
• Customizable lookback ranges and pivot sensitivity provide flexible tuning for different market styles.
3. Gold Zone Volatility Compression
• Highlights pre-breakout zones using custom oscillation models (RSI, harmonic, Karobein, etc.).
• Improves anticipation of breakout opportunities following low-volatility compressions.
4. Trend Direction Context
• PAI and Trend Score components provide top-down insight into prevailing bias.
• Built-in “Straddle Area” highlights consolidation zones; breakouts from this area often signal new trend phases.
5. Flexible Visualization
• Color-coded trend bars, reversal markers, normalized oscillator plots, and trend strength labels.
• Designed for both visual discretionary traders and data-driven system developers.
USAGE GUIDELINES
1. Applicable Markets
• Suitable for stocks, crypto, futures, and forex
• Supports reversal, mean-reversion, and breakout trading styles
2. Recommended Timeframes
• Short-term traders: 5m / 15m / 1H — use Wave Trend divergence + Gold Zone
• Swing traders: 4H / Daily — rely on Price Action Index and Trend Detector
• Macro trend context: use PAI HTF mode for higher timeframe overlays
3. Reversal Strategy Flow
• Watch for divergence (WT/PAI) + Gold Zone compression
• Confirm with Trend Score weakening or flipping
• Use Straddle Area breakout for final trigger
• Optional: enable bar coloring or labels for visual reinforcement
• The indicator performs optimally when used in conjunction with a harmonic pattern recognition tool
4. Additional Note on the Gold Zone
The “Gold Zone” does not directly indicate a market bottom. Since it is displayed at the bottom of the chart, it may be misunderstood as a bullish signal. In reality, the Gold Zone represents a compression of price momentum and volatility, suggesting that a significant directional move is about to occur. The direction of that move—upward or downward—should be determined by analyzing the histogram:
• If histogram momentum is weakening, the Gold Zone may precede a downward move.
• If histogram momentum is strengthening, it may signal an upcoming rebound or rally.
Treat the Gold Zone as a warning of impending volatility, and always combine it with trend indicators for accurate directional judgment.
RISK DISCLAIMER
• This indicator calculates trend direction based on historical data and cannot guarantee future market performance. When using this indicator for trading, always combine it with other technical analysis tools, fundamental analysis, and personal trading experience for comprehensive decision-making.
• Market conditions are uncertain, and trend signals may result in false positives or lag. Traders should avoid over-reliance on indicator signals and implement stop-loss strategies and risk management techniques to reduce potential losses.
• Leverage trading carries high risks and may result in rapid capital loss. If using this indicator in leveraged markets (such as futures, forex, or cryptocurrency derivatives), exercise caution, manage risks properly, and set reasonable stop-loss/take-profit levels to protect funds.
• All trading decisions are the sole responsibility of the trader. The developer is not liable for any trading losses. This indicator is for technical analysis reference only and does not constitute investment advice.
• Before live trading, it is recommended to use a demo account for testing to fully understand how to use the indicator and apply proper risk management strategies.
CHANGELOG
v1.0: Initial release featuring integrated Price Action Index, Trend Strength Scoring, Wave Trend Oscillator, Gold Zone Compression Detection, and dual-type divergence recognition. Supports higher timeframe (HTF) synchronization, visual signal markers, and diversified parameter configurations.
[blackcat] L2 Ehlers Autocorrelation Indicator V2OVERVIEW
The Ehlers Autocorrelation Indicator is a technical analysis tool developed by John F. Ehlers that measures the correlation between price data and its lagged versions to identify potential market cycles and reversals.
BACKGROUND
Originally introduced in Ehlers' "Cycle Analytics for Traders" (2013), this indicator leverages autocorrelation principles to detect patterns in market data that deviate from random noise or perfect sine waves.
FEATURES
• Calculates Pearson correlation coefficients for lags from 0 to 60 bars
• Visualizes correlations using colored bars ranging from red (negative correlation) to yellow (positive correlation)
• Provides minimum averaging option through AvgLength input parameter
• Displays sharp reversal signals at price turning points
• Shows variations in bar thickness and count over time
HOW TO USE
Add the indicator to your chart
Adjust the AvgLength input as needed:
• Set to 0 for no averaging
• Increase value for smoother results
Interpret the colored bars:
• Red: Negative correlation
• Yellow: Positive correlation
• Sharp transitions indicate potential reversal points
LIMITATIONS
• Requires sufficient historical data for accurate calculations
• Performance may vary across different market conditions
• Results depend on proper parameter settings
NOTES
• The indicator uses highpass filtering and super smoother filtering techniques
• Color intensity varies based on correlation strength
• Multiple lag periods are displayed simultaneously for comprehensive analysis
THANKS
This implementation is based on Ehlers' original work and has been adapted for TradingView's Pine Script platform.
TrendWave Bands [BigBeluga]This is a trend-following indicator that dynamically adapts to market trends using upper and lower bands. It visually highlights trend strength and duration through color intensity while providing additional wave bands for deeper trend analysis.
🔵Key Features:
Adaptive Trend Bands:
➣ Displays a lower band in uptrends and an upper band in downtrends to indicate trend direction.
➣ The bands act as dynamic support and resistance levels, helping traders identify potential entry and exit points.
Wave Bands for Additional Analysis:
➣ A dashed wave band appears opposite the main trend band for deeper trend confirmation.
➣ In an uptrend, the upper dashed wave band helps analyze momentum, while in a downtrend, the lower dashed wave band serves the same purpose.
Gradient Color Intensity:
➣ The trend bands have a color gradient that fades as the trend continues, helping traders visualize trend duration.
➣ The wave bands have an inverse gradient effect—starting with low intensity at the trend's beginning and increasing in intensity as the trend progresses.
Trend Change Signals:
➣ Circular markers appear at trend reversals, providing clear entry and exit points.
➣ These signals mark transitions between bullish and bearish phases based on price action.
🔵Usage:
Trend Following: Use the lower band for confirmation in uptrends and the upper band in downtrends to stay on the right side of the market.
Trend Duration Analysis: Gradient wavebands give an idea of the duration of the current trend — new trends will have high-intensity colored wavebands and as time goes on, trends will fade.
Trend Reversal Detection: Circular markers highlight trend shifts, making it easier to spot entry and exit opportunities.
Volatility Awareness: Volatility-based bands help traders adjust their strategies based on market volatility, ensuring better risk management.
TrendWave Bands is a powerful tool for traders seeking to follow market trends with enhanced visual clarity. By combining trend bands, wave bands, and gradient-based color scaling, it provides a detailed view of market dynamics and trend evolution.
Squeeze Momentum Indicator Strategy [LazyBear + PineIndicators]The Squeeze Momentum Indicator Strategy (SQZMOM_LB Strategy) is an automated trading strategy based on the Squeeze Momentum Indicator developed by LazyBear, which itself is a modification of John Carter's "TTM Squeeze" concept from his book Mastering the Trade (Chapter 11). This strategy is designed to identify low-volatility phases in the market, which often precede explosive price movements, and to enter trades in the direction of the prevailing momentum.
Concept & Indicator Breakdown
The strategy employs a combination of Bollinger Bands (BB) and Keltner Channels (KC) to detect market squeezes:
Squeeze Condition:
When Bollinger Bands are inside the Keltner Channels (Black Crosses), volatility is low, signaling a potential upcoming price breakout.
When Bollinger Bands move outside Keltner Channels (Gray Crosses), the squeeze is released, indicating an expansion in volatility.
Momentum Calculation:
A linear regression-based momentum value is used instead of traditional momentum indicators.
The momentum histogram is color-coded to show strength and direction:
Lime/Green: Increasing bullish momentum
Red/Maroon: Increasing bearish momentum
Signal Colors:
Black: Market is in a squeeze (low volatility).
Gray: Squeeze is released, and volatility is expanding.
Blue: No squeeze condition is present.
Strategy Logic
The script uses historical volatility conditions and momentum trends to generate buy/sell signals and manage positions.
1. Entry Conditions
Long Position (Buy)
The squeeze just released (Gray Cross after Black Cross).
The momentum value is increasing and positive.
The momentum is at a local low compared to the past 100 bars.
The price is above the 100-period EMA.
The closing price is higher than the previous close.
Short Position (Sell)
The squeeze just released (Gray Cross after Black Cross).
The momentum value is decreasing and negative.
The momentum is at a local high compared to the past 100 bars.
The price is below the 100-period EMA.
The closing price is lower than the previous close.
2. Exit Conditions
Long Exit:
The momentum value starts decreasing (momentum lower than previous bar).
Short Exit:
The momentum value starts increasing (momentum higher than previous bar).
Position Sizing
Position size is dynamically adjusted based on 8% of strategy equity, divided by the current closing price, ensuring risk-adjusted trade sizes.
How to Use This Strategy
Apply on Suitable Markets:
Best for stocks, indices, and forex pairs with momentum-driven price action.
Works on multiple timeframes but is most effective on higher timeframes (1H, 4H, Daily).
Confirm Entries with Additional Indicators:
The author recommends ADX or WaveTrend to refine entries and avoid false signals.
Risk Management:
Since the strategy dynamically sizes positions, it's advised to use stop-losses or risk-based exits to avoid excessive drawdowns.
Final Thoughts
The Squeeze Momentum Indicator Strategy provides a systematic approach to trading volatility expansions, leveraging the classic TTM Squeeze principles with a unique linear regression-based momentum calculation. Originally inspired by John Carter’s method, LazyBear's version and this strategy offer a refined, adaptable tool for traders looking to capitalize on market momentum shifts.
Adaptive Fourier Transform Supertrend [QuantAlgo]Discover a brand new way to analyze trend with Adaptive Fourier Transform Supertrend by QuantAlgo , an innovative technical indicator that combines the power of Fourier analysis with dynamic Supertrend methodology. In essence, it utilizes the frequency domain mathematics and the adaptive volatility control technique to transform complex wave patterns into clear and high probability signals—ideal for both sophisticated traders seeking mathematical precision and investors who appreciate robust trend confirmation!
🟢 Core Architecture
At its core, this indicator employs an adaptive Fourier Transform framework with dynamic volatility-controlled Supertrend bands. It utilizes multiple harmonic components that let you fine-tune how market frequencies influence trend detection. By combining wave analysis with adaptive volatility bands, the indicator creates a sophisticated yet clear framework for trend identification that dynamically adjusts to changing market conditions.
🟢 Technical Foundation
The indicator builds on three innovative components:
Fourier Wave Analysis: Decomposes price action into primary and harmonic components for precise trend detection
Adaptive Volatility Control: Dynamically adjusts Supertrend bands using combined ATR and standard deviation
Harmonic Integration: Merges multiple frequency components with decreasing weights for comprehensive trend analysis
🟢 Key Features & Signals
The Adaptive Fourier Transform Supertrend transforms complex wave calculations into clear visual signals with:
Dynamic trend bands that adapt to market volatility
Sophisticated cloud-fill visualization system
Strategic L/S markers at key trend reversals
Customizable bar coloring based on trend direction
Comprehensive alert system for trend shifts
🟢 Practical Usage Tips
Here's how you can get the most out of the Adaptive Fourier Transform Supertrend :
1/ Setup:
Add the indicator to your favorites, then apply it to your chart ⭐️
Start with close price as your base source
Use standard Fourier period (14) for balanced wave detection
Begin with default harmonic weight (0.5) for balanced sensitivity
Start with standard Supertrend multiplier (2.0) for reliable band width
2/ Signal Interpretation:
Monitor trend band crossovers for potential signals
Watch for convergence of price with Fourier trend
Use L/S markers for trade entry points
Monitor bar colors for trend confirmation
Configure alerts for significant trend reversals
🟢 Pro Tips
Fine-tune Fourier parameters for optimal sensitivity:
→ Lower Base Period (8-12) for more reactive analysis
→ Higher Base Period (15-30) to filter out noise
→ Adjust Harmonic Weight (0.3-0.7) to control shorter trend influence
Customize Supertrend settings:
→ Lower multiplier (1.5-2.0) for tighter bands
→ Higher multiplier (2.0-3.0) for wider bands
→ Adjust ATR length based on market volatility
Strategy Enhancement:
→ Compare signals across multiple timeframes
→ Combine with volume analysis
→ Use with support/resistance levels
→ Integrate with other momentum indicators
Quantum Transform - AynetQuantum Transform Trading Indicator: Explanation
This script is called a "Quantum Transform Trading Indicator" and aims to enhance market analysis by applying complex mathematical models. Written in Pine Script, the indicator includes the following elements:
1. General Structure
Quantum Parameters: Inspired by physical and mathematical concepts (Planck constant ℏ, wave function Ψ, time τ, etc.), it uses specific parameters.
Transformation Functions: Applies various mathematical operations to transform price data in different ways.
Signal Generation: Produces signals for long and short positions.
Visualization: Displays different price transformations and signals on the chart.
2. Core Parameters
The parameters allow users to control various transformations:
Planck Constant (ℏ): A scaling factor for wave modulation.
Wave (Ψ): Controls oscillation in price data.
Time (τ): The length of the lookback period for calculations.
Relativity (γ): Power factor in the Lorentz transformation.
Phase Shift (β): Manages phase shift in transformations.
Frequency (ω): Represents the frequency of price movements.
Dimensions (∇): Enables multi-dimensional field analysis.
3. Functions
a) Relativistic Transform
Inspired by the theory of relativity.
Calculates the Lorentz factor using the rate of price change.
Transforms price data to amplify the relativity effect.
b) Phase Transform
Calculates the phase of price data and applies wave modulation.
Creates phase and amplitude modulation based on the bar index.
c) Resonance Transform
Calculates resonance effects using natural frequency and oscillations.
Highlights periodic behaviors of price movements.
d) Field Transform
Applies multi-dimensional field calculations.
Combines strength, wave, and coherence aspects of price data.
e) Chaos Transform
Implements a chaos effect based on sensitivity analysis.
Simulates chaotic behaviors of price movements.
4. Main Calculations
Quantum Price: The average of all transformation functions.
Bands:
Upper Band: The highest level of quantum price.
Lower Band: The lowest level of quantum price.
Mid Band: The average of upper and lower bands.
Momentum: Calculates the rate of change in quantum price.
5. Signal Generation
Long Signal:
Triggered when the phase price crosses above the field price.
Momentum must be positive, and the price above the mid-band.
Short Signal:
Triggered when the phase price crosses below the field price.
Momentum must be negative, and the price below the mid-band.
Signal strength is calculated relative to the momentum moving average.
6. Visualization
Each transformation is displayed in a unique color.
Bands and Momentum: Visualize price behavior.
Signal Icons: Show buy/sell signals using up/down arrows on the chart.
7. Information Panel
A table in the top-right corner of the chart displays:
The current values of each transformation.
Signal strength (as a percentage).
The type of signal (⬆: Long, ⬇: Short).
Applications
Trend Following: Analyze trends with complex transformations.
Resonance and Chaos Analysis: Understand dynamic behaviors of price.
Signal Strategies: Create strong and reliable buy/sell signals.
If you have any additional questions or customization requests regarding this indicator, feel free to ask!
Sigma 2.0 - Advanced Buy and Sell Signal IndicatorOverview:
Sigma 2.0 is a sophisticated trading indicator designed to help traders identify potential buy and sell opportunities across various financial markets. By leveraging advanced mathematical calculations and incorporating multiple analytical tools, Sigma 2.0 aims to enhance trading strategies by providing precise entry and exit signals.
Key Features:
Advanced Sigma Calculations:
Utilizes a combination of Exponential Moving Averages (EMAs) and price deviations to calculate the Sigma lines (sigma1 and sigma2).
Detects potential trend reversals through the crossover of these Sigma lines.
Customizable Signal Filtering:
Offers the ability to filter buy and sell signals based on user-defined thresholds.
Helps reduce false signals in volatile markets by setting overbought and oversold levels.
Overbought and Oversold Detection:
Identifies extreme market conditions where price reversals are more likely.
Changes the background color of the chart to visually indicate overbought or oversold states.
Integration of Exponential Moving Averages (EMAs):
Includes EMAs of different lengths (10, 21, 55, 200) to assist in identifying market trends.
EMAs act as dynamic support and resistance levels.
Higher Timeframe Signal Incorporation:
Allows users to include signals from a higher timeframe to align trades with the broader market trend.
Enhances the reliability of signals by considering multiple timeframes.
Custom Alerts:
Provides alert conditions for both buy and sell signals.
Enables traders to receive notifications, ensuring timely decision-making.
How It Works:
Sigma Calculation Methodology:
The indicator calculates an average price (ap) and applies EMAs to derive the Sigma lines.
sigma1 represents the smoothed price deviation, while sigma2 is a moving average of sigma1.
A crossover of sigma1 above sigma2 generates a buy signal, indicating potential upward momentum.
Conversely, a crossover of sigma1 below sigma2 generates a sell signal.
Signal Filtering and Thresholds:
Users can enable filtering to only consider signals when sigma1 is below or above certain thresholds.
This helps in focusing on more significant market movements and reducing noise.
Overbought/Oversold Levels:
The indicator monitors sigma1 to detect when the market is in extreme conditions.
Background color changes provide a quick visual cue for these conditions.
EMA Analysis:
The plotted EMAs help in confirming the trend direction.
They can be used alongside Sigma signals to validate trade entries and exits.
Higher Timeframe Signals:
Incorporates signals from a user-selected higher timeframe.
Helps in aligning trades with the overall market trend, increasing the potential success rate.
How to Use:
Adding the Indicator to Your Chart:
Search for "Sigma 2.0" in the TradingView Indicators menu and add it to your chart.
Configuring the Settings:
Adjust the Sigma configurations (Channel Length, Average Length, Signal Line Length) to suit your trading style.
Set the overbought and oversold levels according to your risk tolerance.
Choose whether to filter signals by thresholds.
Select the higher timeframe for additional signal confirmation.
Interpreting the Signals:
Buy Signals:
Indicated by a green triangle below the price bar.
Occur when sigma1 crosses above sigma2 and other conditions are met.
Sell Signals:
Indicated by a red triangle above the price bar.
Occur when sigma1 crosses below sigma2 and other conditions are met.
Higher Timeframe Signals:
Plotted with lime (buy) and maroon (sell) triangles.
Help confirm signals in the current timeframe.
Utilizing EMAs:
Observe the EMAs to gauge the overall trend.
Consider aligning buy signals when the price is above key EMAs and sell signals when below.
Setting Up Alerts:
Use the built-in alert conditions to receive notifications for buy and sell signals.
Customize alert messages as needed.
Credits:
Original Concept Inspiration:
This indicator is inspired by the WaveTrend oscillator and other momentum-based indicators.
Special thanks to the original authors whose work laid the foundation for this enhanced version.
Disclaimer:
Trading involves significant risk, and past performance is not indicative of future results.
This indicator is a tool to assist in analysis and should not be the sole basis for any trading decision.
Always perform thorough analysis and consider multiple factors before entering a trade.
Note:
Ensure your chart is clean and only includes this indicator when publishing.
The script is open-source and can be modified to fit individual trading strategies.
For any questions or support, feel free to reach out or comment.
