Directional Matrix [LuxAlgo]Returns a dashboard showing the direction taken by 4 overlay indicators, SMA (simple moving average), TMA (triangular moving average), WMA (weighted moving average), and REG (linear regression), all using different length periods.
The user can select the minimum and maximum length of these indicators and introduce an increment.
1. Settings
Maximum Length: The end value of sequences of the indicator periods to analyze
Minimum Length: The starting value of sequences of the indicator periods to analyze
Step: Determines the spacing between each indicator periods values
Src: Data source for each of the 4 indicators
1.1 Style settings
Normalized Change Mode: Allows the user to access a different interpretation of the indicator by showing the normalized first differences of each indicator in the dashboard instead of their sign
Dashboard Location: Location of the dashboard on the chart
Dashboard Size: Size of the dashboard on the chart
Text/Frame Color: Determines the color of the frame grid as well as the text color
Bullish Cell Color: Determines the color of cell associated with a rising indicator direction
Bearish Cell Color: Determines the color of cell associated with a decreasing indicator direction
Cell Transparency: Transparency of each cell
2. Usage
Each of the indicators included in the dashboard aim to give an estimate of the underlying trend in the price. Knowing which direction they are taking can help us have a broader view regarding the direction of shorter/longer-term trends. We will later see that this is not the only kind of information that we can get from this indicator.
Rising indicators are represented by blue cells (or the color selected in the Bullish Cell Color setting) while decreasing indicators are represented by red cells (or the color selected in the Bearish Cell Color setting).
The percentage of bullish cells is given in the top-left cell of the dashboard.
2.1 Normalized change mode
Enabling the Normalized Change mode will display the normalized changes returned by the indicators over different length periods. This metric is within a range (0,1), with 1 indicating the highest change over the selected length periods, while 0 indicates the lowest one.
When enabling this mode the color of the cells makes use of a gradient with a color palette ranging from the color selected in the Bearish Cell setting to the color selected in the Bullish Cell setting.
2.1 Other Usage
The direction taken by certain indicators can give more information than one would think. Indeed, the sign of the change of one indicator can often be given by different indicators.
A positive change in a simple moving average indicates that the price is greater than the price p bars ago, where p is the period of the simple moving average.
A positive change in a triangular moving average indicates that a simple moving average of period p is above a simple moving average of period p × 2 , where p is the period of the triangular moving average (note that we assume here that the TMA is given by cascading two SMAs of period p ).
A positive change in a weighted moving average indicates that the price is above a simple moving average of period p+1 , where p is the period of the WMA.
Finally, a positive change in a linear regression indicates that a weighted moving average is above a simple moving average of period p , where p is the period of the linear regression.
In den Scripts nach "indicators" suchen
[blackcat] L2 Ehlers Super Smooth Stoch StrategyLevel: 2
Background
John F. Ehlers introuced Super Smooth Stochastic Indicator in Jan, 2014.
Function
In “Predictive And Successful Indicators” of in, 2014, John Ehlers presented another innovative way to eliminate noise from classic indicators and introduces some new smoothing indicators: the SuperSmoother filter, which is superior to moving averages for removing aliasing noise, and the MESA Stochastic oscillator, a stochastic successor that removes the effect of spectral dilation through the use of a roofing filter.
John Ehlers described a new method for smoothing market data while reducing the lag that most other smoothing techniques have. Ehlers had provided an approach for creating a strategy. For convenience, I made the same code available at tradingview pine v4 as well as an example strategy based on Ehlers’ description. Ehlers introduced a simple countertrend system that goes long when MESA Stochastic crosses below the oversold value and reverses the trade by taking a short position when the oscillator exceeds the overbought threshold.
Key Signal
MyStochastic --> Super Smooth Stochastic line
long ---> long entry signal
short ---> short entry signal
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 81th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Trend-Following Combo-SuperTrend, EMA, Aroon, DMI, Laguerre RSIThis is a trend-following indicator which condenses two SuperTrend indicators -- one based on analysis over a shorter period of time (1.5, 7), and one based on analysis over a longer period of time (1.65, 100) -- into a single indicator which appears on your chart only when both the shorter- and longer-term analysis indicates a "SuperTrend" in the same direction.
Additionally, potential trade entry indicators are displayed in the form of up and down arrows when (by default) three of the following five indicators suggest that the market is trending in the same direction as both the shorter- and longer-term SuperTrend indicators:
EMA Crossover (8, 15)
Aroon Indicator (8)
Aroon Oscillator (8)
Directional Movement Index (DI +/-) (8)
Laguerre RSI (13)
You may update the parameters of any of the indicators to match your own preferences.
Additionally, you may also adjust the "Threshold" of indicators that must be in agreement with the SuperTrend to show a potential trade entry arrow. Bear in mind that if you set the Indicator Threshold too low, you will see more frequent trade entry arrows, many of which will not be profitable if taken. Similarly, set this value too high, and you will see fewer trade entry arrows that may not appear until after most of the "juice" in the trend has evaporated. Ideal values for the threshold seem to be between 2-4, depending on the symbol you are trading.
The following image shows all of the indicators referenced above on a 5-minute chart of the SPY during a single trading day:
And, here is the same period of time showing only the Trend-Following Combo indicator with default settings:
This indicator would not have been possible save for work contributed by the following:
SuperTrend by Rajandran R
Aroon w/ crossovers highlighted by seiglerj
Aroon Oscillator by jcrewolinsky
Directional Movement Index by TradingView
Laguerre RSI (Self Adjusting Alpha with Fractals Energy) by everget
TRIX Histogram R1-12 by JustUncleLCreated by request.
Description:
This study is an implementation of the Standard TRIX indicator (a momentum oscillator), shown in coloured histogram format by default, with optional Bar colouring of TRIX zero cross overs. Other options include showing TRIX as a line graph instead of histogram and an optional TRIX signal line with difference histogram (to highlight signal line crosses).
References:
forex-indicators.net
"TRIX MA" by munkeefonix
BUY & SELL PRESSURE by RegressionBUY & SELL PRESSURE by Regression Analysis at candle price/volume (Rate-Of-Change)
Ver. 3 By Ricardo M Arjona @XeL_Arjona
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
WHAT'S THIS?
This is my 3rd. revision of the original implementation for AmiBroker by Karthik Marar's of it's BUY AND SELL PRESSURE INDICATORS but this time, constructed under a complete REGRESSIVE ANALYSIS premise based in Rate Of Change (A kind of Slope but measured in % Performance).
Some minimal adaptation's (and cleaning) have been made:
Instead of simple Range calculation at price, Rate Of Change (Regressive) is used.
Oscillator of Pressure can be deactivated in favor of a simple RoC Cumulative Pressures at candle.
Oscillator can read Volume data from external tickers for accurate Index calculation. ( NYA can use TVOL as example.)
Code is small, cleaner and faster =) !
Cheers!
Any feedback will be welcome...
@XeL_Arjona
TUX CandlesThis indicator has a lot of information. This is the first version so stay tuned for updates, and please let me know of any bugs.
Candlestick Indicators:
Doji
Shooting Star
Evening Star
Hammer
Hanging Man
Candlestick Formations
Tri-star
Bearish Harami
Bullish Harami
Bearish Harami Cross
Bullish Harami Cross
Bullish Engulfing
Bearish Engulfing
Rising Three
Falling Three
Bearish Abandoned Baby
Bullish Abandoned Baby
Three Black Crows
Three White Soldiers
Technical Indicators:
(You can set you MA periods)
Moving Average Cross
Move Average Crossover
Composite Momentum Index [LazyBear]This is a composite oscillator derived from modified 5/10/20 Chande's Dynamic Momentum Index values.
Volatility is factored in, by design. Look for OB/OS extremes and divergences.
I added the green/red ribbon look to make it easy to read :)
More info:
www.investopedia.com
List of my public indicators: bit.ly
List of my app-store indicators: blog.tradingview.com
Acceleration BandsPrice Headley\'s Acceleration Bands serve as a trading envelope that factor in a stock\'s typical volatility over standard settings of 20 or 80 bars. They can be used across any time frame, though Headley prefers to use them most across weekly and monthly timeframes as breakout indicators outside these bands, while using the shorter time frames to define likely support and resistance levels at the lower and upper Acceleration Bands. Acceleration Bands are plotted around a simple moving average as the midpoint, and the upper and lower bands are of equal distance from this midpoint.
www.swingtracker.com
forex-indicators.net
Universal Strategy Adapter - Connect Anything, Backtest EverythiDescription The Universal Strategy Adapter is a powerful utility that allows you to turn ANY indicator into a backtestable strategy without writing a single line of code. Whether you want to trade based on a simple crossover, a specific threshold, or complex multi-indicator confluence, this adapter handles the logic, execution, and risk management for you.
Key Features
Connect Up To 8 Indicators Plug in up to 8 different data sources using the input.source dropdowns. Mix and match indicators (e.g., RSI + MACD + Moving Average).
Advanced Logic Engine Mandatory vs. Optional : Distinct "Must Have" signals vs. "Nice to Have" confluence. Min Optionals Required : Require at least X optional indicators to fire before taking a trade. Lookback Persistence : Solves the "Sync" problem. If Indicator A fires on candle 1 and Indicator B fires on candle 3, the Lookback window ensures they still count as a confluence setup.
Flexible Conditions For each slot, choose how the signal is interpreted: Signal (!= 0) : Best for "Event" indicators like Golden Dots or Alerts. Price > Source : Trend Filters (e.g., Price above EMA 200). Source > Threshold : Value filters (e.g., RSI > 50). Rising / Falling : Momentum filters (e.g., RSI is trending up compared to 12 bars ago).
Risk Management & Cooldown Built-in Stop Loss and Take Profit (%) settings. Trade Cooldown : Prevent "Machine Gun" trades by enforcing a wait period after each entry.
How To Use Add your favorite indicators to the chart (e.g., "VuManChu Cipher B" and "EMA 200"). Add Universal Strategy Adapter to the chart. Open Settings > Inputs. Slot 1 (Trigger) : Source : Select the "Buy Signal" or "Golden Dot" plot from the first indicator. Condition : Signal (!= 0) Role : Mandatory Slot 2 (Filter) : Source : Select the "EMA 200" plot. Condition : Price > Source (Trades only taken when price is above EMA). Role : Mandatory Adjust SL/TP and Backtest Range as needed.
Why Use This? TradingView strategies are often hardcoded to specific indicators. This script breaks that barrier, giving you a universal "Container" to drop any logic into and see the raw backtest results immediately.
BE-QuantFlow: Adaptive Momentum Trading█ Overview: QuantFlow: Adaptive Momentum Trading
QuantFlow is a sophisticated algorithmic momentum trading method designed specifically for indices and high-beta stocks. However, its logic is universal; with appropriate parameter tuning, it adapts to various asset classes and timeframes.
While the standard momentum indicators (like RSI or MACD) simply measure how fast price is moving (Velocity), QuantFlow analyzes the quality and conviction of the trend . Features like Dynamic Volatility Filtering and Trend Shielding, combined with volatility weighting and a "Dual-Line" approach to distinguish between a sustainable institutional trend and a temporary retail spike, make the indicator unique and more powerful.
█ Why QuantFlow ?
Quant (The Engine): This replaces subjective guessing with objective math.
Instead of just seeing that the price is "up," we measure "how it got there". For example, a stock that rises 1 currency value every day for 10 days (smooth trend) gets a much higher score than a stock that jumps 10 currency value in one minute and does nothing else (erratic noise). This mathematical rigor provides the structure.
█ Core Logic & Philosophy
To understand how QuantFlow calculates momentum, imagine a "Tug-of-War" between Buyers (Bulls) and Sellers (Bears). Most indicators (like RSI) use a single line. If RSI is at 50, it means "Neutral." But "Neutral" can mean two very different things:
Peace: Nothing is happening. No one is buying or selling.
War: Buyers are pushing hard, but Sellers are pushing back equally hard. Volatility is massive.
A single line hides this reality. QuantFlow splits the market into two separate scores:
Bull Score (Green Line): How hard are the buyers pushing?
Bear Score (Red Line): How hard are the sellers pushing?
The Layman's Advantage:
If both lines are low = Sleepy Market (Avoid).
If Green is high and Red is low = Clean Uptrend (Buy).
If Red is high and Green is low = Clean Downtrend (Sell).
If both lines are high = Chaos/War Zone (Wait).
█ How it Weight "Sustenance" (The Critical Quality Check)
This is the most unique aspect of QuantFlow: Trend direction alone is not enough; Sustenance is weighed equally . Standard indicators treat every 10 currency value movements the same way with no distinction. However, QuantFlow asks, "Did you hold the ground you gained?"
Scenario A (High Sustenance) : A stock opens at 100, marches to 110, and closes at 110.
Verdict : Buyers pushed up and sustained the price.
QuantFlow Weight : 100%. This is a high-quality move.
Scenario B (Low Sustenance) : A stock opens at 100, spikes to 110, but gets sold off to close at 102.
Verdict : Buyers pushed up (Trend is Up), but failed to sustain it (Long Wick).
QuantFlow Weight : 20%. This is treated as "Noise" or a trap.
By mathematically weighing the Close Location Value (where the candle closes relative to its high/low), QuantFlow filters out "Gap-and-Fade" traps and exhaustion spikes that fool traditional indicators.
Comparisons: QuantFlow vs. The Rest
Calculation Logic : Standard RSI/MACD measures simple price change over time. QuantFlow measures Price Change 'times (x)' Conviction (Sustenance Weighting).
Visual Output : Standard tools show a single line (0-100), often hiding market conflict. QuantFlow displays Dual Lines (Bull vs Bear Intensity) to reveal the true state of the battle.
Trap Handling : Standard indicators are often fooled by sharp spikes. QuantFlow ignores "Gap-and-Fade" moves with poor closing conviction.
Adaptability : Standard tools use static levels (e.g., Overbought > 70). QuantFlow uses Dynamic Bands that adjust automatically to recent volatility.
█ Dynamic Volatility Filtering
Unlike standard indicators that use fixed levels (e.g., "Buy if RSI > 50"), QuantFlow acknowledges that "50" means something different in a quiet market versus a crashing market. This section explains the statistical engine driving the signals.
The Problem with Static Levels : In a low-volatility environment, a momentum score of 55 might indicate a massive breakout. In a high-volatility environment, a score of 55 might just be random noise. A fixed threshold cannot handle both scenarios.
The Solution: Adaptive Statistics : The script maintains a memory of the Momentum Events. It doesn't just look at price; it looks at where the momentum occurred in the past and draws a "Noise Zone" (Grey Band). This logic acts as a "Smart Gatekeeper" for trade entries:
Scenario A: Inside the Noise (The Filter)
If a new momentum signal happens inside the Noise Zone, the script assumes it is likely chop or noise.
Action : It forces a wait period. The signal is delayed until the trend sustains itself for Confirm Bars; else the signal is cancelled. This filters out ~70% of false signals in sideways markets.
Scenario B: Outside the Noise (The Breakout)
If a new momentum signal happens outside the Noise Zone (or the momentum score smashes through the Upper Band), it is statistically significant (an outlier event).
Action: It triggers an Immediate Entry. No waiting is required because the move is powerful enough to escape the historical noise zone.
█ The ⚠️ "Warning" System (Heads-up for Smart Reversals)
While you are directional if there is potential reversal signal, it provides the heads-up warning for a better decision-making
█ Special Utility: Ghost Mode
For intraday traders, the biggest disruption to "Flow" is the mandatory broker square-off at 3:15 PM (considering Indian Market). Often, a trend continues overnight, and the trader misses the gap-up opening the next morning because their algo was flat.
Ghost Mode is a unique feature that runs silently in the background:
At Square-off: The strategy closes your official position to satisfy the broker.
In the Background: It keeps the trade "alive" virtually (Ghost).
Next Morning: If the market opens in the trend's favor, the strategy re-enters the trade automatically. This approach ensures you capture the full swing of the trend, even if you are forced to exit at the previous session.
█ Advice on this indicator:
Parameter Calibration: The default settings are optimized for BankNifty on 5-minute charts. If you trade stocks, crypto, commodities, or any higher timeframes (e.g., 15-min or hourly), you must adjust these.
Low Volatility Assets: Reduce Stop Multiplier to 2.0.
High Volatility Assets: Increase Momentum Lookback to 50 to filter noise.
Confluence (Additional Confirmation): While QuantFlow is a complete system, using it alongside Key Support/Resistance Levels or Volume Profile provides the highest probability setups.
Victor aimstar past strategy -v1Introducing the ultimate all-in-one DIY strategy builder indicator, With over 30+ famous indicators (some with custom configuration/settings) indicators included, you now have the power to mix and match to create your own custom strategy for shorter time or longer time frames depending on your trading style. Say goodbye to cluttered charts and manual/visual confirmation of multiple indicators and hello to endless possibilities with this indicator.
What it does
==================
This indicator basically help users to do 2 things:
1) Strategy Builder
With more than 30 indicators available, you can select any combination you prefer and the indicator will generate buy and sell signals accordingly. Alternative to the time-consuming process of manually confirming signals from multiple indicators! This indicator streamlines the process by automatically printing buy and sell signals based on your chosen combination of indicators. No more staring at the screen for hours on end, simply set up alerts and let the indicator do the work for you.
Flux-Tensor Singularity [FTS]Flux-Tensor Singularity - Multi-Factor Market Pressure Indicator
The Flux-Tensor Singularity (FTS) is an advanced multi-factor oscillator that combines volume analysis, momentum tracking, and volatility-weighted normalization to identify critical market inflection points. Unlike traditional single-factor indicators, FTS synthesizes price velocity, volume mass, and volatility context into a unified framework that adapts to changing market regimes.
This indicator identifies extreme market conditions (termed "singularities") where multiple confirming factors converge, then uses a sophisticated scoring system to determine directional bias. It is designed for traders seeking high-probability setups with built-in confluence requirements.
THEORETICAL FOUNDATION
The indicator is built on the premise that market time is not constant - different market conditions contain varying levels of information density. A 1-minute bar during a major news event contains far more actionable information than a 1-minute bar during overnight low-volume trading. Traditional indicators treat all bars equally; FTS does not.
The theoretical framework draws conceptual parallels to physics (purely as a mental model, not literal physics):
Volume as Mass: Large volume represents significant market participation and "weight" behind price moves. Just as massive objects have stronger gravitational effects, high-volume moves carry more significance.
Price Change as Velocity: The rate of price movement through price space represents momentum and directional force.
Volatility as Time Dilation: When volatility is high relative to its historical norm, the "information density" of each bar increases. The indicator weights these periods more heavily, similar to how time dilates near massive objects in physics.
This is a pedagogical metaphor to create a coherent mental model - the underlying mathematics are standard financial calculations combined in a novel way.
MATHEMATICAL FRAMEWORK
The indicator calculates a composite singularity value through four distinct steps:
Step 1: Raw Singularity Calculation
S_raw = (ΔP × V) × γ²
Where:
ΔP = Price Velocity = close - close
V = Volume Mass = log(volume + 1)
γ² = Time Dilation Factor = (ATR_local / ATR_global)²
Volume Transformation: Volume is log-transformed because raw volume can have extreme outliers (10x-100x normal). The logarithm compresses these spikes while preserving their significance. This is standard practice in volume analysis.
Volatility Weighting: The ratio of short-term ATR (5 periods) to long-term ATR (user-defined lookback) is squared to create a volatility amplification factor. When local volatility exceeds global volatility, this ratio increases, amplifying the raw singularity value. This makes the indicator regime-aware.
Step 2: Normalization
The raw singularity values are normalized to a 0-100 scale using a stochastic-style calculation:
S_normalized = ((S_raw - S_min) / (S_max - S_min)) × 100
Where S_min and S_max are the lowest and highest raw singularity values over the lookback period.
Step 3: Epsilon Compression
S_compressed = 50 + ((S_normalized - 50) / ε)
This is the critical innovation that makes the sensitivity control functional. By applying compression AFTER normalization, the epsilon parameter actually affects the final output:
ε < 1.0: Expands range (more signals)
ε = 1.0: No change (default)
ε > 1.0: Compresses toward 50 (fewer, higher-quality signals)
For example, with ε = 2.0, a normalized value of 90 becomes 70, making threshold breaches rarer and more significant.
Step 4: Smoothing
S_final = EMA(S_compressed, smoothing_period)
An exponential moving average removes high-frequency noise while preserving trend.
SIGNAL GENERATION LOGIC
When the tensor crosses above the upper threshold (default 90) or below the lower threshold (default 10), an extreme event is detected. However, the indicator does NOT immediately generate a buy or sell signal. Instead, it analyzes market context through a multi-factor scoring system:
Scoring Components:
Price Structure (+1 point): Current bar bullish/bearish
Momentum (+1 point): Price higher/lower than N bars ago
Trend Context (+2 points): Fast EMA above/below slow EMA (weighted heavier)
Acceleration (+1 point): Rate of change increasing/decreasing
Volume Multiplier (×1.5): If volume > average, multiply score
The highest score (bullish vs bearish) determines signal direction. This prevents the common indicator failure mode of "overbought can stay overbought" by requiring directional confirmation.
Signal Conditions:
A BUY signal requires:
Extreme event detection (tensor crosses threshold)
Bullish score > Bearish score
Price confirmation: Bullish candle (optional, user-controlled)
Volume confirmation: Volume > average (optional, user-controlled)
Momentum confirmation: Positive momentum (optional, user-controlled)
A SELL signal requires the inverse conditions.
INPUTS EXPLAINED - Core Parameters:
Global Horizon (Context): Default 20. Lookback period for normalization and volatility comparison. Higher values = smoother but less responsive. Lower values = more signals but potentially more noise.
Tensor Smoothing: Default 3. EMA period applied to final output. Removes "quantum foam" (high-frequency noise). Range 1-20.
Singularity Threshold: Default 90. Values above this (or below 100-threshold) trigger extreme event detection. Higher = rarer, stronger signals.
Signal Sensitivity (Epsilon): Default 1.0. Post-normalization compression factor. This is the key innovation - it actually works because it's applied AFTER normalization. Range 0.1-5.0.
Signal Interpreter Toggles:
Require Price Confirmation: Default ON. Only generates buy signals on bullish candles, sell signals on bearish candles. Reduces false signals but may delay entry.
Require Volume Confirmation: Default ON. Only signals when volume > average. Critical for stocks/crypto, less important for forex (unreliable volume data).
Use Momentum Filter: Default ON. Requires momentum agreement with signal direction. Prevents counter-trend signals.
Momentum Lookback: Default 5. Number of bars for momentum calculation. Shorter = more responsive, longer = trend-following bias.
Visual Controls:
Colors: Customizable colors for bullish flux, bearish flux, background, and event horizon.
Visual Transparency: Default 85. Master control for all visual elements (accretion disk, field lines, particles, etc.). Range 50-99. Signals and dashboard have separate controls.
Visibility Toggles: Individual on/off switches for:
Gravitational field lines (trend EMAs)
Field reversals (trend crossovers)
Accretion disk (background gradient)
Singularity diamonds (neutral extreme events)
Energy particles (volume bursts)
Event horizon flash (extreme event background)
Signal background flash
Signal Size: Tiny/Small/Normal triangle size
Signal Offsets: Separate controls for buy and sell signal vertical positioning (percentage of price)
Dashboard Settings:
Show Dashboard: Toggle on/off
Position: 9 placement options (all corners, centers, middles)
Text Size: Tiny/Small/Normal/Large
Background Transparency: 0-50, separate from visual transparency
VISUAL ELEMENTS EXPLAINED
1. Accretion Disk (Background Gradient):
A three-layer gradient background that intensifies as the tensor approaches extremes. The outer disk appears at any non-neutral reading, the inner disk activates above 70 or below 30, and the core layer appears above 85 or below 15. Color indicates direction (cyan = bullish, red = bearish). This provides instant visual feedback on market pressure intensity.
2. Gravitational Field Lines (EMAs):
Two trend-following EMAs (10 and 30 period) visualized as colored lines. These represent the "curvature" of market trend - when they diverge, trend is strong; when they converge, trend is weakening. Crossovers mark potential trend reversals.
3. Field Reversals (Circles):
Small circles appear when the fast EMA crosses the slow EMA, indicating a potential trend change. These are distinct from extreme events and appear at normal market structure shifts.
4. Singularity Diamonds:
Small diamond shapes appear when the tensor reaches extreme levels (>90 or <10) but doesn't meet the full signal criteria. These are "watch" events - extreme pressure exists but directional confirmation is lacking.
5. Energy Particles (Dots):
Tiny dots appear when volume exceeds 2× average, indicating significant participation. Color matches bar direction. These highlight genuine high-conviction moves versus low-volume drifts.
6. Event Horizon Flash:
A golden background flash appears the instant any extreme threshold is breached, before directional analysis. This alerts you to pay attention.
7. Signal Background Flash:
When a full buy/sell signal is confirmed, the background flashes cyan (buy) or red (sell). This is your primary alert that all conditions are met.
8. Signal Triangles:
The actual buy (▲) and sell (▼) markers. These only appear when ALL selected confirmation criteria are satisfied. Position is offset from bars to avoid overlap with other indicators.
DASHBOARD METRICS EXPLAINED
The dashboard displays real-time calculated values:
Event Density: Current tensor value (0-100). Above 90 or below 10 = critical. Icon changes: 🔥 (extreme high), ❄️ (extreme low), ○ (neutral).
Time Dilation (γ): Current volatility ratio squared. Values >2.0 indicate extreme volatility environments. >1.5 = elevated, >1.0 = above average. Icon: ⚡ (extreme), ⚠ (elevated), ○ (normal).
Mass (Vol): Log-transformed volume value. Compared to volume ratio (current/average). Icon: ● (>2× avg), ◐ (>1× avg), ○ (below avg).
Velocity (ΔP): Raw price change. Direction arrow indicates momentum direction. Shows the actual price delta value.
Bullish Flux: Current bullish context score. Displayed as both a bar chart (visual) and numeric value. Brighter when bullish score dominates.
Bearish Flux: Current bearish context score. Same visualization as bullish flux. These scores compete - the winner determines signal direction.
Field: Trend direction based on EMA relationship. "Repulsive" (uptrend), "Attractive" (downtrend), "Neutral" (ranging). Icon: ⬆⬇↔
State: Current market condition:
🚀 EJECTION: Buy signal active
💥 COLLAPSE: Sell signal active
⚠ CRITICAL: Extreme event, no directional confirmation
● STABLE: Normal market conditions
HOW TO USE THE INDICATOR
1. Wait for Extreme Events:
The indicator is designed to be selective. Don't trade every fluctuation - wait for tensor to reach >90 or <10. This alone is not a signal.
2. Check Context Scores:
Look at the Bullish Flux vs Bearish Flux in the dashboard. If scores are close (within 1-2 points), the market is indecisive - skip the trade.
3. Confirm with Signals:
Only act when a full triangle signal appears (▲ or ▼). This means ALL your selected confirmation criteria have been met.
4. Use with Price Structure:
Combine with support/resistance levels. A buy signal AT support is higher probability than a buy signal in the middle of nowhere.
5. Respect the Dashboard State:
When State shows "CRITICAL" (⚠), it means extreme pressure exists but direction is unclear. These are the most dangerous moments - wait for resolution.
6. Volume Matters:
Energy particles (dots) and the Mass metric tell you if institutions are participating. Signals without volume confirmation are lower probability.
MARKET AND TIMEFRAME RECOMMENDATIONS
Scalping (1m-5m):
Lookback: 10-14
Smoothing: 5-7
Threshold: 85
Epsilon: 0.5-0.7
Note: Expect more noise. Confirm with Level 2 data. Best on highly liquid instruments.
Intraday (15m-1h):
Lookback: 20-30 (default settings work well)
Smoothing: 3-5
Threshold: 90
Epsilon: 1.0
Note: Sweet spot for the indicator. High win rate on liquid stocks, forex majors, and crypto.
Swing Trading (4h-1D):
Lookback: 30-50
Smoothing: 3
Threshold: 90-95
Epsilon: 1.5-2.0
Note: Signals are rare but high conviction. Combine with higher timeframe trend analysis.
Position Trading (1D-1W):
Lookback: 50-100
Smoothing: 5-7
Threshold: 95
Epsilon: 2.0-3.0
Note: Extremely rare signals. Only trade the most extreme events. Expect massive moves.
Market-Specific Settings:
Forex (EUR/USD, GBP/USD, etc.):
Volume data is unreliable (spot forex has no centralized volume)
Disable "Require Volume Confirmation"
Focus on momentum and trend filters
News events create extreme singularities
Best on 15m-1h timeframes
Stocks (High-Volume Equities):
Volume confirmation is CRITICAL - keep it ON
Works excellently on AAPL, TSLA, SPY, etc.
Morning session (9:30-11:00 ET) shows highest event density
Earnings announcements create guaranteed extreme events
Best on 5m-1h for day trading, 1D for swing trading
Crypto (BTC, ETH, major alts):
Reduce threshold to 85 (crypto has constant high volatility)
Volume spikes are THE primary signal - keep volume confirmation ON
Works exceptionally well due to 24/7 trading and high volatility
Epsilon can be reduced to 0.7-0.8 for more signals
Best on 15m-4h timeframes
Commodities (Gold, Oil, etc.):
Gold responds to macro events (Fed announcements, geopolitical events)
Oil responds to supply shocks
Use daily timeframe minimum
Increase lookback to 50+
These are slow-moving markets - be patient
Indices (SPX, NDX, etc.):
Institutional volume matters - keep volume confirmation ON
Opening hour (9:30-10:30 ET) = highest singularity probability
Strong correlation with VIX - high VIX = more extreme events
Best on 15m-1h for day trading
WHAT MAKES THIS INDICATOR UNIQUE
1. Post-Normalization Sensitivity Control:
Unlike most oscillators where sensitivity controls don't actually work (they're applied before normalization, which then rescales everything), FTS applies epsilon compression AFTER normalization. This means the sensitivity parameter genuinely affects signal frequency. This is a novel implementation not found in standard oscillators.
2. Multi-Factor Confluence Requirement:
The indicator doesn't just detect "overbought" or "oversold" - it detects extreme conditions AND THEN analyzes context through five separate factors (price structure, momentum, trend, acceleration, volume). Most indicators are single-factor; FTS requires confluence.
3. Volatility-Weighted Normalization:
By squaring the ATR ratio (local/global), the indicator adapts to changing market regimes. A 1% move in a low-volatility environment is treated differently than a 1% move in a high-volatility environment. Traditional indicators treat all moves equally regardless of context.
4. Volume Integration at the Core:
Volume isn't an afterthought or optional filter - it's baked into the fundamental equation as "mass." The log transformation handles outliers elegantly while preserving significance. Most price-based indicators completely ignore volume.
5. Adaptive Scoring System:
Rather than fixed buy/sell rules ("RSI >70 = sell"), FTS uses competitive scoring where bullish and bearish evidence compete. The winner determines direction. This solves the classic problem of "overbought markets can stay overbought during strong uptrends."
6. Comprehensive Visual Feedback:
The multi-layer visualization system (accretion disk, field lines, particles, flashes) provides instant intuitive feedback on market state without requiring dashboard reading. You can see pressure building before extreme thresholds are hit.
7. Separate Extreme Detection and Signal Generation:
"Singularity diamonds" show extreme events that don't meet full criteria, while "signal triangles" only appear when ALL conditions are met. This distinction helps traders understand when pressure exists versus when it's actionable.
COMPARISON TO EXISTING INDICATORS
vs. RSI/Stochastic:
These normalize price relative to recent range. FTS normalizes (price change × log volume × volatility ratio) - a composite metric, not just price position.
vs. Chaikin Money Flow:
CMF combines price and volume but lacks volatility context and doesn't use adaptive normalization or post-normalization compression.
vs. Bollinger Bands + Volume:
Bollinger Bands show volatility but don't integrate volume or create a unified oscillator. They're separate components, not synthesized.
vs. MACD:
MACD is pure momentum. FTS combines momentum with volume weighting and volatility context, plus provides a normalized 0-100 scale.
The specific combination of log-volume weighting, squared volatility amplification, post-normalization epsilon compression, and multi-factor directional scoring is unique to this indicator.
LIMITATIONS AND PROPER DISCLOSURE
Not a Holy Grail:
No indicator is perfect. This tool identifies high-probability setups but cannot predict the future. Losses will occur. Use proper risk management.
Requires Confirmation:
Best used in conjunction with price action analysis, support/resistance levels, and higher timeframe trend. Don't trade signals blindly.
Volume Data Dependency:
On forex (spot) and some low-volume instruments, volume data is unreliable or tick-volume only. Disable volume confirmation in these cases.
Lagging Components:
The EMA smoothing and trend filters are inherently lagging. In extremely fast moves, signals may appear after the initial thrust.
Extreme Event Rarity:
With conservative settings (high threshold, high epsilon), signals can be rare. This is by design - quality over quantity. If you need more frequent signals, reduce threshold to 85 and epsilon to 0.7.
Not Financial Advice:
This indicator is an analytical tool. All trading decisions and their consequences are solely your responsibility. Past performance does not guarantee future results.
BEST PRACTICES
Don't trade every singularity - wait for context confirmation
Higher timeframes = higher reliability
Combine with support/resistance for entry refinement
Volume confirmation is CRITICAL for stocks/crypto (toggle off only for forex)
During major news events, singularities are inevitable but direction may be uncertain - use wider stops
When bullish and bearish flux scores are close, skip the trade
Test settings on your specific instrument/timeframe before live trading
Use the dashboard actively - it contains critical diagnostic information
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
VSLRT with DivergencesOverview
This indicator combines Volume-Synchronized Linear Regression Trend (VSLRT) analysis with multi-indicator divergence detection to provide comprehensive market momentum and reversal signals. It displays volume-weighted price trends in both short-term and long-term timeframes, while simultaneously detecting divergences across 10 different technical indicators.
Key Features
VSLRT (Volume-Synchronized Linear Regression Trend):
Short-term and long-term trend analysis using linear regression
Volume-weighted calculations that account for buying vs selling pressure
Color-coded histogram showing trend strength and direction
Forecast projection showing anticipated trend continuation
Divergence-adjusted forecasting for enhanced prediction accuracy
Multi-Indicator Divergence Detection:
The indicator simultaneously monitors divergences across:
MACD (Moving Average Convergence Divergence)
MACD Histogram
RSI (Relative Strength Index)
Stochastic Oscillator
CCI (Commodity Channel Index)
Momentum
OBV (On-Balance Volume)
Volume-Weighted MACD
Chaikin Money Flow
Money Flow Index
Divergence Types:
Regular Bullish Divergence (potential reversal to upside)
Regular Bearish Divergence (potential reversal to downside)
Hidden Bullish Divergence (trend continuation upward)
Hidden Bearish Divergence (trend continuation downward)
How It Works
VSLRT Calculations:
The indicator calculates linear regression slopes for both price and volume, separating buying volume from selling volume. The histogram displays:
Green columns: Bullish price movement with strong buying volume
Red columns: Bearish price movement with strong selling volume
Shaded columns: Weaker conviction in the current trend
Thick line: Long-term trend direction
Divergence Detection:
The script automatically scans for divergences by comparing:
Price action (higher highs/lower lows)
Indicator values at pivot points
When price and indicators move in opposite directions, a divergence is detected
Divergences are displayed as labels on the histogram showing:
Which indicators are diverging
Number of simultaneous divergences (stronger signal when multiple indicators agree)
Color-coded by divergence type
Customizable Settings
VSLRT Settings:
Short-term length (default: 20)
Long-term length (default: 50)
Forecast bars (1-50, default: 10)
Divergence forecast adjustment factor
Custom colors for all trend states
Divergence Settings:
Pivot period for divergence detection
Source (Close or High/Low)
Divergence type (Regular, Hidden, or Both)
Minimum number of divergences to display
Maximum pivot points and bars to check
Toggle individual indicators on/off
Custom colors for each divergence type
Label display options (Full names, First letter, or Don't show)
Show divergence count option
Trading Applications
Trend Following:
Use VSLRT histogram to identify trend direction and strength
Enter trades when short-term and long-term trends align
Monitor forecast bars for potential trend continuation
Reversal Trading:
Watch for multiple regular divergences (3+ indicators)
Confirm with VSLRT color changes
Higher divergence count = stronger reversal signal
Trend Continuation:
Hidden divergences suggest trend will continue
Use during pullbacks in strong trends
Combine with VSLRT forecast for entry timing
Risk Management:
Divergence alerts can signal potential exits
VSLRT color changes can indicate stop-loss levels
Forecast helps anticipate trend exhaustion
Alert Conditions
Built-in alert conditions for:
Positive Regular Divergence Detected
Negative Regular Divergence Detected
Positive Hidden Divergence Detected
Negative Hidden Divergence Detected
Any Positive Divergence
Any Negative Divergence
Tips for Best Results
Multiple Timeframe Analysis: Check divergences on higher timeframes for more reliable signals
Confirmation: Wait for bar close (enabled by default) to avoid false signals
Volume Context: Stronger VSLRT signals occur during high volume periods
Divergence Count: More simultaneous divergences = higher probability signal
Trend Alignment: Best results when divergences align with overall trend direction
Tristan's Tri-band StrategyTristan's Tri-band Strategy - Confluence Trading System
Strategy Overview:
This strategy combines three powerful technical indicators - RSI, Williams %R, and Bollinger Bands - into a single visual trading system. Instead of cluttering your chart with separate indicator panels, all signals are displayed directly on the price chart using color-coded gradient overlays, making it easy to spot high-probability trade setups at a glance.
How It Works:
The strategy identifies trading opportunities when multiple indicators align (confluence), suggesting strong momentum shifts:
📈 Long Entry Signals:
RSI drops to 30 or below (oversold)
Williams %R reaches -80 to -100 range (oversold)
Price touches or breaks below the lower Bollinger Band
All three conditions must align during your selected trading session
📉 Short Entry Signals:
RSI rises to 70 or above (overbought)
Williams %R reaches 0 to -20 range (overbought)
Price touches or breaks above the upper Bollinger Band
All three conditions must align during your selected trading session
Visual Indicators:
(faint) Green gradients below candles = Bullish oversold conditions (buying opportunity)
(faint) Red/Orange gradients above candles = Bearish overbought conditions (selling opportunity)
Stacked/brighter gradients = Multiple indicators confirming the same signal (higher probability) will stack and show brighter / less faint
Blue Bollinger Bands = Volatility boundaries and mean reversion zones
Exit Strategy:
Long trades exit when price reaches the upper Bollinger Band OR RSI becomes overbought (≥70)
Short trades exit when price reaches the lower Bollinger Band OR RSI becomes oversold (≤30)
Key Features:
✅ Session Filters - Trade only during NY (9:30 AM-4 PM), London (3 AM-11:30 AM), or Asia (7 PM-1 AM EST) sessions
✅ No Repainting - Signals are confirmed on candle close for realistic backtesting and live trading
✅ Customizable Parameters - Adjust RSI levels, BB standard deviations, Williams %R periods, and gradient visibility
✅ Visual Clarity - See all three indicators at once without switching between panels
✅ Built-in Alerts - Get notified when entry and exit conditions are met
How to Use Effectively:
Choose Your Trading Session - For day trading US stocks, enable only the NY session. For forex or 24-hour markets, select the sessions that match your schedule.
Look for Gradient Stacking - The brightest, most visible gradients occur when both RSI and Williams %R signal together. These are your highest-probability setups.
Confirm with Price Action - Wait for the candle to close before entering. The strategy enters on the next bar's open to prevent repainting.
Respect the Bollinger Bands - Entries occur at the outer bands (price extremes), and exits occur at the opposite band or when momentum reverses.
Backtest First - Test the strategy on your preferred instruments and timeframes. Works best on liquid assets with clear trends and mean reversion patterns (stocks, major forex pairs, indices).
Adjust Gradient Visibility - Use the "Gradient Strength" slider (lower = more visible) to make signals stand out on your chart style.
Best Timeframes: 5-minute to 1-hour charts for intraday trading; 4-hour to daily for swing trading (I have also found the 3 hour timeframe to work really well for some stocks / ETFs.)
Best Markets: Liquid instruments with volatility - SPY, QQQ, major stocks, EUR/USD, GBP/USD, major indices
Risk Management: This is a mean reversion strategy that works best in ranging or choppy markets. In strong trends, signals may appear less frequently. Always use proper position sizing and stop losses based on your risk tolerance.
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Note: Past performance does not guarantee future results. This strategy is provided for educational purposes. Always backtest thoroughly and practice proper risk management before live trading.RetryClaude can make mistakes. Please double-check responses. Sonnet 4.5
Market Spiralyst [Hapharmonic]Hello, traders and creators! 👋
Market Spiralyst: Let's change the way we look at analysis, shall we? I've got to admit, I scratched my head on this for weeks, Haha :). What you're seeing is an exploration of what's possible when code meets art on financial charts. I wanted to try blending art with trading, to do something new and break away from the same old boring perspectives. The goal was to create a visual experience that's not just analytical, but also relaxing and aesthetically pleasing.
This work is intended as a guide and a design example for all developers, born from the spirit of learning and a deep love for understanding the Pine Script™ language. I hope it inspires you as much as it challenged me!
🧐 Core Concept: How It Works
Spiralyst is built on two distinct but interconnected engines:
The Generative Art Engine: At its core, this indicator uses a wide range of mathematical formulas—from simple polygons to exotic curves like Torus Knots and Spirographs—to draw beautiful, intricate shapes directly onto your chart. This provides a unique and dynamic visual backdrop for your analysis.
The Market Pulse Engine: This is where analysis meets art. The engine takes real-time data from standard technical indicators (RSI and MACD in this version) and translates their states into a simple, powerful "Pulse Score." This score directly influences the appearance of the "Scatter Points" orbiting the main shape, turning the entire artwork into a living, breathing representation of market momentum.
🎨 Unleash Your Creativity! This Is Your Playground
We've included 25 preset shapes for you... but that's just the starting point !
The real magic happens when you start tweaking the settings yourself. A tiny adjustment can make a familiar shape come alive and transform in ways you never expected.
I'm genuinely excited to see what your imagination can conjure up! If you create a shape you're particularly proud of or one that looks completely unique, I would love to see it. Please feel free to share a screenshot in the comments below. I can't wait to see what you discover! :)
Here's the default shape to get you started:
The Dynamic Scatter Points: Reading the Pulse
This is where the magic happens! The small points scattered around the main shape are not just decorative; they are the visual representation of the Market Pulse Score.
The points have two forms:
A small asterisk (`*`): Represents a low or neutral market pulse.
A larger, more prominent circle (`o`): Represents a high, strong market pulse.
Here’s how to read them:
The indicator calculates the Pulse Strength as a percentage (from 0% to 100%) based on the total score from the active indicators (RSI and MACD). This percentage determines the ratio of circles to asterisks.
High Pulse Strength (e.g., 80-100%): Most of the scatter points will transform into large circles (`o`). This indicates that the underlying momentum is strong and It could be an uptrend. It's a visual cue that the market is gaining strength and might be worth paying closer attention to.
Low Pulse Strength (e.g., 0-20%): Most or all of the scatter points will remain as small asterisks (`*`). This suggests weak, neutral, or bearish momentum.
The key takeaway: The more circles you see, the stronger the bullish momentum is according to the active indicators. Watch the artwork "breathe" as the circles appear and disappear with the market's rhythm!
And don't worry about the shape you choose; the scatter points will intelligently adapt and always follow the outer boundary of whatever beautiful form you've selected.
How to Use
Getting started with Spiralyst is simple:
Choose Your Canvas: Start by going into the settings and picking a `Shape` and `Palette` from the "Shape Selection & Palette" group that you find visually appealing. This is your canvas.
Tune Your Engine: Go to the "Market Pulse Engine" settings. Here, you can enable or disable the RSI and MACD scoring engines. Want to see the pulse based only on RSI? Just uncheck the MACD box. You can also fine-tune the parameters for each indicator to match your trading style.
Read the Vibe: Observe the scatter points. Are they mostly small asterisks or are they transforming into large, vibrant circles? Use this visual feedback as a high-level gauge of market momentum.
Check the Dashboard: For a precise breakdown, look at the "Market Pulse Analysis" table on the top-right. It gives you the exact values, scores, and total strength percentage.
Explore & Experiment: Play with the different shapes and color palettes! The core analysis remains the same, but the visual experience can be completely different.
⚙️ Settings & Customization
Spiralyst is designed to be highly customizable.
Shape Selection & Palette: This is your main control panel. Choose from over 25 unique shapes, select a color palette, and adjust the line extension style ( `extend` ) or horizontal position ( `offsetXInput` ).
scatterLabelsInput: This setting controls the total number of points (both asterisks and circles) that orbit the main shape. Think of it as adjusting the density or visual granularity of the market pulse feedback.
The Market Pulse engine will always calculate its strength as a percentage (e.g., 75%). This percentage is then applied to the `scatterLabelsInput` number you've set to determine how many points transform into large circles.
Example: If the Pulse Strength is 75% and you set this to `100` , approximately 75 points will become circles. If you increase it to `200` , approximately 150 points will transform.
A higher number provides a more detailed, high-resolution view of the market pulse, while a lower number offers a cleaner, more minimalist look. Feel free to adjust this to your personal visual preference; the underlying analytical percentage remains the same.
Market Pulse Engine:
`⚙️ RSI Settings` & `⚙️ MACD Settings`: Each indicator has its own group.
Enable Scoring: Use the checkbox at the top of each group to include or exclude that indicator from the Pulse Score calculation. If you only want to use RSI, simply uncheck "Enable MACD Scoring."
Parameters: All standard parameters (Length, Source, Fast/Slow/Signal) are fully adjustable.
Individual Shape Parameters (01-25): Each of the 25+ shapes has its own dedicated group of settings, allowing you to fine-tune every aspect of its geometry, from the number of petals on a flower to the windings of a knot. Feel free to experiment!
For Developers & Pine Script™ Enthusiasts
If you are a developer and wish to add more indicators (e.g., Stochastic, CCI, ADX), you can easily do so by following the modular structure of the code. You would primarily need to:
Add a new `PulseIndicator` object for your new indicator in the `f_getMarketPulse()` function.
Add the logic for its scoring inside the `calculateScore()` method.
The `calculateTotals()` method and the dashboard table are designed to be dynamic and will automatically adapt to include your new indicator!
One of the core design philosophies behind Spiralyst is modularity and scalability . The Market Pulse engine was intentionally built using User-Defined Types (UDTs) and an array-based structure so that adding new indicators is incredibly simple and doesn't require rewriting the main logic.
If you want to add a new indicator to the scoring engine—let's use the Stochastic Oscillator as a detailed example—you only need to modify three small sections of the code. The rest of the script, including the adaptive dashboard, will update automatically.
Here’s your step-by-step guide:
#### Step 1: Add the User Inputs
First, you need to give users control over your new indicator. Find the `USER INTERFACE: INPUTS` section and add a new group for the Stochastic settings, right after the MACD group.
Create a new group name: `string GRP_STOCH = "⚙️ Stochastic Settings"`
Add the inputs: Create a boolean to enable/disable it, and then add the necessary parameters (`%K`, `%D`, `Smooth`). Use the `active` parameter to link them to the enable/disable checkbox.
// Add this code block right after the GRP_MACD and MACD inputs
string GRP_STOCH = "⚙️ Stochastic Settings"
bool stochEnabledInput = input.bool(true, "Enable Stochastic Scoring", group = GRP_STOCH)
int stochKInput = input.int(14, "%K Length", minval=1, group = GRP_STOCH, active = stochEnabledInput)
int stochDInput = input.int(3, "%D Smoothing", minval=1, group = GRP_STOCH, active = stochEnabledInput)
int stochSmoothInput = input.int(3, "Smooth", minval=1, group = GRP_STOCH, active = stochEnabledInput)
#### Step 2: Integrate into the Pulse Engine (The "Factory")
Next, go to the `f_getMarketPulse()` function. This function acts as a "factory" that builds and configures the entire market pulse object. You need to teach it how to build your new Stochastic indicator.
Update the function signature: Add the new `stochEnabledInput` boolean as a parameter.
Calculate the indicator: Add the `ta.stoch()` calculation.
Create a `PulseIndicator` object: Create a new object for the Stochastic, populating it with its name, parameters, calculated value, and whether it's enabled.
Add it to the array: Simply add your new `stochPulse` object to the `array.from()` list.
Here is the complete, updated `f_getMarketPulse()` function :
// Factory function to create and calculate the entire MarketPulse object.
f_getMarketPulse(bool rsiEnabled, bool macdEnabled, bool stochEnabled) =>
// 1. Calculate indicator values
float rsiVal = ta.rsi(rsiSourceInput, rsiLengthInput)
= ta.macd(close, macdFastInput, macdSlowInput, macdSignalInput)
float stochVal = ta.sma(ta.stoch(close, high, low, stochKInput), stochDInput) // We'll use the main line for scoring
// 2. Create individual PulseIndicator objects
PulseIndicator rsiPulse = PulseIndicator.new("RSI", str.tostring(rsiLengthInput), rsiVal, na, 0, rsiEnabled)
PulseIndicator macdPulse = PulseIndicator.new("MACD", str.format("{0},{1},{2}", macdFastInput, macdSlowInput, macdSignalInput), macdVal, signalVal, 0, macdEnabled)
PulseIndicator stochPulse = PulseIndicator.new("Stoch", str.format("{0},{1},{2}", stochKInput, stochDInput, stochSmoothInput), stochVal, na, 0, stochEnabled)
// 3. Calculate score for each
rsiPulse.calculateScore()
macdPulse.calculateScore()
stochPulse.calculateScore()
// 4. Add the new indicator to the array
array indicatorArray = array.from(rsiPulse, macdPulse, stochPulse)
MarketPulse pulse = MarketPulse.new(indicatorArray, 0, 0.0)
// 5. Calculate final totals
pulse.calculateTotals()
pulse
// Finally, update the function call in the main orchestration section:
MarketPulse marketPulse = f_getMarketPulse(rsiEnabledInput, macdEnabledInput, stochEnabledInput)
#### Step 3: Define the Scoring Logic
Now, you need to define how the Stochastic contributes to the score. Go to the `calculateScore()` method and add a new case to the `switch` statement for your indicator.
Here's a sample scoring logic for the Stochastic, which gives a strong bullish score in oversold conditions and a strong bearish score in overbought conditions.
Here is the complete, updated `calculateScore()` method :
// Method to calculate the score for this specific indicator.
method calculateScore(PulseIndicator this) =>
if not this.isEnabled
this.score := 0
else
this.score := switch this.name
"RSI" => this.value > 65 ? 2 : this.value > 50 ? 1 : this.value < 35 ? -2 : this.value < 50 ? -1 : 0
"MACD" => this.value > this.signalValue and this.value > 0 ? 2 : this.value > this.signalValue ? 1 : this.value < this.signalValue and this.value < 0 ? -2 : this.value < this.signalValue ? -1 : 0
"Stoch" => this.value > 80 ? -2 : this.value > 50 ? 1 : this.value < 20 ? 2 : this.value < 50 ? -1 : 0
=> 0
this
#### That's It!
You're done. You do not need to modify the dashboard table or the total score calculation.
Because the `MarketPulse` object holds its indicators in an array , the rest of the script is designed to be adaptive:
The `calculateTotals()` method automatically loops through every indicator in the array to sum the scores and calculate the final percentage.
The dashboard code loops through the `enabledIndicators` array to draw the table. Since your new Stochastic indicator is now part of that array, it will appear automatically when enabled!
---
Remember, this is your playground! I'm genuinely excited to see the unique shapes you discover. If you create something you're proud of, feel free to share it in the comments below.
Happy analyzing, and may your charts be both insightful and beautiful! 💛
AshishBediSPLAshishBediSPL: Dynamic Premium Analysis with Integrated Signals
This indicator provides a comprehensive view of combined options premiums by aggregating data from Call and Put contracts for a selected index and expiry. It integrates multiple popular technical indicators like EMA Crossover, Supertrend, VWAP, RSI, and SMA, allowing users to select their preferred tools for generating dynamic buy and sell signals directly on the premium chart.
AshishBediSPL" is a powerful TradingView indicator designed to analyze options premiums. It calculates a real-time combined premium for a chosen index (NIFTY, BANKNIFTY, FINNIFTY, etc.) and specific expiry date. You have the flexibility to visualize the premium of Call options, Put options, or a combined premium of both.
The indicator then overlays several popular technical analysis tools, which you can selectively enable:
EMA Crossover: Identify trend changes with configurable fast and slow Exponential Moving Averages.
Supertrend: Detect trend direction and potential reversal points.
VWAP (Volume Weighted Average Price): Understand the average price of the premium considering trading volume.
RSI (Relative Strength Index): Gauge momentum and identify overbought/oversold conditions.
SMA (Simple Moving Average): Analyze price smoothing and trend identification.
Based on your selected indicators, the tool generates clear "Buy" and "Sell" signals directly on the chart, helping you identify potential entry and exit points. Customizable alerts are also available to keep you informed.
Unlock a new perspective on options trading with "AshishBediSPL." This indicator focuses on the combined value of options premiums, giving you a consolidated view of market sentiment for a chosen index and expiry.
Instead of just looking at individual option prices, "AshishBediSPL" blends the Call and Put premiums (or focuses on one, based on your preference) and empowers you with a suite of built-in technical indicators: EMA, Supertrend, VWAP, RSI, and SMA. Pick the indicators that resonate with your strategy, and let the tool generate actionable buy and sell signals right on your chart. With customizable alerts, you'll never miss a crucial market move. Gain deeper insights and make more informed trading decisions with "AshishBediSPL.
Combined options premium: This accurately describes what your indicator calculates.
Selected index and expiry: Essential inputs for the indicator.
Call/Put options or combined: Explains the flexibility in data display.
Multiple technical indicators (EMA Crossover, Supertrend, VWAP, RSI, SMA): Lists the analysis tools included.
Buy/Sell signals: The primary output of the indicator.
Customizable alerts: A valuable feature for users.
3D Surface Modeling [PhenLabs]📊 3D Surface Modeling
Version: PineScript™ v6
📌 Description
The 3D Surface Modeling indicator revolutionizes technical analysis by generating three-dimensional visualizations of multiple technical indicators across various timeframes. This advanced analytical tool processes and renders complex indicator data through a sophisticated matrix-based calculation system, creating an intuitive 3D surface representation of market dynamics.
The indicator employs array-based computations to simultaneously analyze multiple instances of selected technical indicators, mapping their behavior patterns across different temporal dimensions. This unique approach enables traders to identify complex market patterns and relationships that may be invisible in traditional 2D charts.
🚀 Points of Innovation
Matrix-Based Computation Engine: Processes up to 500 concurrent indicator calculations in real-time
Dynamic 3D Rendering System: Creates depth perception through sophisticated line arrays and color gradients
Multi-Indicator Integration: Seamlessly combines VWAP, Hurst, RSI, Stochastic, CCI, MFI, and Fractal Dimension analyses
Adaptive Scaling Algorithm: Automatically adjusts visualization parameters based on indicator type and market conditions
🔧 Core Components
Indicator Processing Module: Handles real-time calculation of multiple technical indicators using array-based mathematics
3D Visualization Engine: Converts indicator data into three-dimensional surfaces using line arrays and color mapping
Dynamic Scaling System: Implements custom normalization algorithms for different indicator types
Color Gradient Generator: Creates depth perception through programmatic color transitions
🔥 Key Features
Multi-Indicator Support: Comprehensive analysis across seven different technical indicators
Customizable Visualization: User-defined color schemes and line width parameters
Real-time Processing: Continuous calculation and rendering of 3D surfaces
Cross-Timeframe Analysis: Simultaneous visualization of indicator behavior across multiple periods
🎨 Visualization
Surface Plot: Three-dimensional representation using up to 500 lines with dynamic color gradients
Depth Indicators: Color intensity variations showing indicator value magnitude
Pattern Recognition: Visual identification of market structures across multiple timeframes
📖 Usage Guidelines
Indicator Selection
Type: VWAP, Hurst, RSI, Stochastic, CCI, MFI, Fractal Dimension
Default: VWAP
Starting Length: Minimum 5 periods
Default: 10
Step Size: Interval between calculations
Range: 1-10
Visualization Parameters
Color Scheme: Green, Red, Blue options
Line Width: 1-5 pixels
Surface Resolution: Up to 500 lines
✅ Best Use Cases
Multi-timeframe market analysis
Pattern recognition across different technical indicators
Trend strength assessment through 3D visualization
Market behavior study across multiple periods
⚠️ Limitations
High computational resource requirements
Maximum 500 line restriction
Requires substantial historical data
Complex visualization learning curve
🔬 How It Works
1. Data Processing:
Calculates selected indicator values across multiple timeframes
Stores results in multi-dimensional arrays
Applies custom scaling algorithms
2. Visualization Generation:
Creates line arrays for 3D surface representation
Applies color gradients based on value magnitude
Renders real-time updates to surface plot
3. Display Integration:
Synchronizes with chart timeframe
Updates surface plot dynamically
Maintains visual consistency across updates
🌟 Credits:
Inspired by LonesomeTheBlue (modified for multiple indicator types with scaling fixes and additional unique mappings)
💡 Note:
Optimal performance requires sufficient computing resources and historical data. Users should start with default settings and gradually adjust parameters based on their analysis requirements and system capabilities.
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Ultimate Scalping Tool[BullByte]Overview
The Ultimate Scalping Tool is an open-source TradingView indicator built for scalpers and short-term traders released under the Mozilla Public License 2.0. It uses a custom Quantum Flux Candle (QFC) oscillator to combine multiple market forces into one visual signal. In plain terms, the script reads momentum, trend strength, volatility, and volume together and plots a special “candlestick” each bar (the QFC) that reflects the overall market bias. This unified view makes it easier to spot entries and exits: the tool labels signals as Strong Buy/Sell, Pullback (a brief retracement in a trend), Early Entry, or Exit Warning . It also provides color-coded alerts and a small dashboard of metrics. In practice, traders see green/red oscillator bars and symbols on the chart when conditions align, helping them scalp or trend-follow without reading multiple separate indicators.
Core Components
Quantum Flux Candle (QFC) Construction
The QFC is the heart of the indicator. Rather than using raw price, it creates a candlestick-like bar from the underlying oscillator values. Each QFC bar has an “open,” “high/low,” and “close” derived from calculated momentum and volatility inputs for that period . In effect, this turns the oscillator into intuitive candle patterns so traders can recognize momentum shifts visually. (For comparison, note that Heikin-Ashi candles “have a smoother look because take an average of the movement”. The QFC instead represents exact oscillator readings, so it reflects true momentum changes without hiding price action.) Colors of QFC bars change dynamically (e.g. green for bullish momentum, red for bearish) to highlight shifts. This is the first open-source QFC oscillator that dynamically weights four non-correlated indicators with moving thresholds, which makes it a unique indicator on its own.
Oscillator Normalization & Adaptive Weights
The script normalizes its oscillator to a fixed scale (for example, a 0–100 range much like the RSI) so that various inputs can be compared fairly. It then applies adaptive weighting: the relative influence of trend, momentum, volatility or volume signals is automatically adjusted based on current market conditions. For instance, in very volatile markets the script might weight volatility more heavily, or in a strong trend it might give extra weight to trend direction. Normalizing data and adjusting weights helps keep the QFC sensitive but stable (normalization ensures all inputs fit a common scale).
Trend/Momentum/Volume/Volatility Fusion
Unlike a typical single-factor oscillator, the QFC oscillator fuses four aspects at once. It may compute, for example, a trend indicator (such as an ADX or moving average slope), a momentum measure (like RSI or Rate-of-Change), a volume-based pressure (similar to MFI/OBV), and a volatility measure (like ATR) . These different values are combined into one composite oscillator. This “multi-dimensional” approach follows best practices of using non-correlated indicators (trend, momentum, volume, volatility) for confirmation. By encoding all these signals in one line, a high QFC reading means that trend, momentum, and volume are all aligned, whereas a neutral reading might mean mixed conditions. This gives traders a comprehensive picture of market strength.
Signal Classification
The script interprets the QFC oscillator to label trades. For example:
• Strong Buy/Sell : Triggered when the oscillator crosses a high-confidence threshold (e.g. breaks clearly above zero with strong slope), indicating a well-confirmed move. This is like seeing a big green/red QFC candle aligned with the trend.
• Pullbacks : Identified when the trend is up but momentum dips briefly. A Pullback Buy appears if the overall trend is bullish but the oscillator has a short retracement – a typical buying opportunity in an uptrend. (A pullback is “a brief decline or pause in a generally upward price trend”.)
• Early Buy/Sell : Marks an initial swing in the oscillator suggesting a possible new trend, before it is fully confirmed. It’s a hint of momentum building (an early-warning signal), not as strong as the confirmed “Strong” signal.
• Exit Warnings : Issued when momentum peaks or reverses. For instance, if the QFC bars reach a high and start turning red/green opposite, the indicator warns that the move may be ending. In other words, a Momentum Peak is the point of maximum strength after which weakness may follow.
These categories correspond to typical trading concepts: Pullback (temporary reversal in an uptrend), Early Buy (an initial bullish cross), Strong Buy (confirmed bullish momentum), and Momentum Peak (peak oscillator value suggesting exhaustion).
Filters (DI Reversal, Dynamic Thresholds, HTF EMA/ADX)
Extra filters help avoid bad trades. A DI Reversal filter uses the +DI/–DI lines (from the ADX system) to require that the trend direction confirms the signal . For example, it might ignore a buy signal if the +DI is still below –DI. Dynamic Thresholds adjust signal levels on-the-fly: rather than fixed “overbought” lines, they move with volatility so signals happen under appropriate market stress. An optional High-Timeframe EMA or ADX filter adds a check against a larger timeframe trend: for instance, only taking a trade if price is above the weekly EMA or if weekly ADX shows a strong trend. (Notably, the ADX is “a technical indicator used by traders to determine the strength of a price trend”, so requiring a high-timeframe ADX avoids trading against the bigger trend.)
Dashboard Metrics & Color Logic
The Dashboard in the Ultimate Scalping Tool (UST) serves as a centralized information hub, providing traders with real-time insights into market conditions, trend strength, momentum, volume pressure, and trade signals. It is highly customizable, allowing users to adjust its appearance and content based on their preferences.
1. Dashboard Layout & Customization
Short vs. Extended Mode : Users can toggle between a compact view (9 rows) and an extended view (13 rows) via the `Short Dashboard` input.
Text Size Options : The dashboard supports three text sizes— Tiny, Small, and Normal —adjustable via the `Dashboard Text Size` input.
Positioning : The dashboard is positioned in the top-right corner by default but can be moved if modified in the script.
2. Key Metrics Displayed
The dashboard presents critical trading metrics in a structured table format:
Trend (TF) : Indicates the current trend direction (Strong Bullish, Moderate Bullish, Sideways, Moderate Bearish, Strong Bearish) based on normalized trend strength (normTrend) .
Momentum (TF) : Displays momentum status (Strong Bullish/Bearish or Neutral) derived from the oscillator's position relative to dynamic thresholds.
Volume (CMF) : Shows buying/selling pressure levels (Very High Buying, High Selling, Neutral, etc.) based on the Chaikin Money Flow (CMF) indicator.
Basic & Advanced Signals:
Basic Signal : Provides simple trade signals (Strong Buy, Strong Sell, Pullback Buy, Pullback Sell, No Trade).
Advanced Signal : Offers nuanced signals (Early Buy/Sell, Momentum Peak, Weakening Momentum, etc.) with color-coded alerts.
RSI : Displays the Relative Strength Index (RSI) value, colored based on overbought (>70), oversold (<30), or neutral conditions.
HTF Filter : Indicates the higher timeframe trend status (Bullish, Bearish, Neutral) when using the Leading HTF Filter.
VWAP : Shows the V olume-Weighted Average Price and whether the current price is above (bullish) or below (bearish) it.
ADX : Displays the Average Directional Index (ADX) value, with color highlighting whether it is rising (green) or falling (red).
Market Mode : Shows the selected market type (Crypto, Stocks, Options, Forex, Custom).
Regime : Indicates volatility conditions (High, Low, Moderate) based on the **ATR ratio**.
3. Filters Status Panel
A secondary panel displays the status of active filters, helping traders quickly assess which conditions are influencing signals:
- DI Reversal Filter: On/Off (confirms reversals before generating signals).
- Dynamic Thresholds: On/Off (adjusts buy/sell thresholds based on volatility).
- Adaptive Weighting: On/Off (auto-adjusts oscillator weights for trend/momentum/volatility).
- Early Signal: On/Off (enables early momentum-based signals).
- Leading HTF Filter: On/Off (applies higher timeframe trend confirmation).
4. Visual Enhancements
Color-Coded Cells : Each metric is color-coded (green for bullish, red for bearish, gray for neutral) for quick interpretation.
Dynamic Background : The dashboard background adapts to market conditions (bullish/bearish/neutral) based on ADX and DI trends.
Customizable Reference Lines : Users can enable/disable fixed reference lines for the oscillator.
How It(QFC) Differs from Traditional Indicators
Quantum Flux Candle (QFC) Versus Heikin-Ashi
Heikin-Ashi candles smooth price by averaging (HA’s open/close use averages) so they show trend clearly but hide true price (the current HA bar’s close is not the real price). QFC candles are different: they are oscillator values, not price averages . A Heikin-Ashi chart “has a smoother look because it is essentially taking an average of the movement”, which can cause lag. The QFC instead shows the raw combined momentum each bar, allowing faster recognition of shifts. In short, HA is a smoothed price chart; QFC is a momentum-based chart.
Versus Standard Oscillators
Common oscillators like RSI or MACD use fixed formulas on price (or price+volume). For example, RSI “compares gains and losses and normalizes this value on a scale from 0 to 100”, reflecting pure price momentum. MFI is similar but adds volume. These indicators each show one dimension: momentum or volume. The Ultimate Scalping Tool’s QFC goes further by integrating trend strength and volatility too. In practice, this means a move that looks strong on RSI might be downplayed by low volume or weak trend in QFC. As one source notes, using multiple non-correlated indicators (trend, momentum, volume, volatility) provides a more complete market picture. The QFC’s multi-factor fusion is unique – it is effectively a multi-dimensional oscillator rather than a traditional single-input one.
Signal Style
Traditional oscillators often use crossovers (RSI crossing 50) or fixed zones (MACD above zero) for signals. The Ultimate Scalping Tool’s signals are custom-classified: it explicitly labels pullbacks, early entries, and strong moves. These terms go beyond a typical indicator’s generic “buy”/“sell.” In other words, it packages a strategy around the oscillator, which traders can backtest or observe without reading code.
Key Term Definitions
• Pullback : A short-term dip or consolidation in an uptrend. In this script, a Pullback Buy appears when price is generally rising but shows a brief retracement. (As defined by Investopedia, a pullback is “a brief decline or pause in a generally upward price trend”.)
• Early Buy/Sell : An initial or tentative entry signal. It means the oscillator first starts turning positive (or negative) before a full trend has developed. It’s an early indication that a trend might be starting.
• Strong Buy/Sell : A confident entry signal when multiple conditions align. This label is used when momentum is already strong and confirmed by trend/volume filters, offering a higher-probability trade.
• Momentum Peak : The point where bullish (or bearish) momentum reaches its maximum before weakening. When the oscillator value stops rising (or falling) and begins to reverse, the script flags it as a peak – signaling that the current move could be overextended.
What is the Flux MA?
The Flux MA (Moving Average) is an Exponential Moving Average (EMA) applied to a normalized oscillator, referred to as FM . Its purpose is to smooth out the fluctuations of the oscillator, providing a clearer picture of the underlying trend direction and strength. Think of it as a dynamic baseline that the oscillator moves above or below, helping you determine whether the market is trending bullish or bearish.
How it’s calculated (Flux MA):
1.The oscillator is normalized (scaled to a range, typically between 0 and 1, using a default scale factor of 100.0).
2.An EMA is applied to this normalized value (FM) over a user-defined period (default is 10 periods).
3.The result is rescaled back to the oscillator’s original range for plotting.
Why it matters : The Flux MA acts like a support or resistance level for the oscillator, making it easier to spot trend shifts.
Color of the Flux Candle
The Quantum Flux Candle visualizes the normalized oscillator (FM) as candlesticks, with colors that indicate specific market conditions based on the relationship between the FM and the Flux MA. Here’s what each color means:
• Green : The FM is above the Flux MA, signaling bullish momentum. This suggests the market is trending upward.
• Red : The FM is below the Flux MA, signaling bearish momentum. This suggests the market is trending downward.
• Yellow : Indicates strong buy conditions (e.g., a "Strong Buy" signal combined with a positive trend). This is a high-confidence signal to go long.
• Purple : Indicates strong sell conditions (e.g., a "Strong Sell" signal combined with a negative trend). This is a high-confidence signal to go short.
The candle mode shows the oscillator’s open, high, low, and close values for each period, similar to price candlesticks, but it’s the color that provides the quick visual cue for trading decisions.
How to Trade the Flux MA with Respect to the Candle
Trading with the Flux MA and Quantum Flux Candle involves using the MA as a trend indicator and the candle colors as entry and exit signals. Here’s a step-by-step guide:
1. Identify the Trend Direction
• Bullish Trend : The Flux Candle is green and positioned above the Flux MA. This indicates upward momentum.
• Bearish Trend : The Flux Candle is red and positioned below the Flux MA. This indicates downward momentum.
The Flux MA serves as the reference line—candles above it suggest buying pressure, while candles below it suggest selling pressure.
2. Interpret Candle Colors for Trade Signals
• Green Candle : General bullish momentum. Consider entering or holding a long position.
• Red Candle : General bearish momentum. Consider entering or holding a short position.
• Yellow Candle : A strong buy signal. This is an ideal time to enter a long trade.
• Purple Candle : A strong sell signal. This is an ideal time to enter a short trade.
3. Enter Trades Based on Crossovers and Colors
• Long Entry : Enter a buy position when the Flux Candle turns green and crosses above the Flux MA. If it turns yellow, this is an even stronger signal to go long.
• Short Entry : Enter a sell position when the Flux Candle turns red and crosses below the Flux MA. If it turns purple, this is an even stronger signal to go short.
4. Exit Trades
• Exit Long : Close your buy position when the Flux Candle turns red or crosses below the Flux MA, indicating the bullish trend may be reversing.
• Exit Short : Close your sell position when the Flux Candle turns green or crosses above the Flux MA, indicating the bearish trend may be reversing.
•You might also exit a long trade if the candle changes from yellow to green (weakening strong buy signal) or a short trade from purple to red (weakening strong sell signal).
5. Use Additional Confirmation
To avoid false signals, combine the Flux MA and candle signals with other indicators or dashboard metrics (e.g., trend strength, momentum, or volume pressure). For example:
•A yellow candle with a " Strong Bullish " trend and high buying volume is a robust long signal.
•A red candle with a " Moderate Bearish " trend and neutral momentum might need more confirmation before shorting.
Practical Example
Imagine you’re scalping a cryptocurrency:
• Long Trade : The Flux Candle turns yellow and is above the Flux MA, with the dashboard showing "Strong Buy" and high buying volume. You enter a long position. You exit when the candle turns red and dips below the Flux MA.
• Short Trade : The Flux Candle turns purple and crosses below the Flux MA, with a "Strong Sell" signal on the dashboard. You enter a short position. You exit when the candle turns green and crosses above the Flux MA.
Market Presets and Adaptation
This indicator is designed to work on any market with candlestick price data (stocks, crypto, forex, indices, etc.). To handle different behavior, it provides presets for major asset classes. Selecting a “Stocks,” “Crypto,” “Forex,” or “Options” preset automatically loads a set of parameter values optimized for that market . For example, a crypto preset might use a shorter lookback or higher sensitivity to account for crypto’s high volatility, while a stocks preset might use slightly longer smoothing since stocks often trend more slowly. In practice, this means the same core QFC logic applies across markets, but the thresholds and smoothing adjust so signals remain relevant for each asset type.
Usage Guidelines
• Recommended Timeframes : Optimized for 1 minute to 15 minute intraday charts. Can also be used on higher timeframes for short term swings.
• Market Types : Select “Crypto,” “Stocks,” “Forex,” or “Options” to auto tune periods, thresholds and weights. Use “Custom” to manually adjust all inputs.
• Interpreting Signals : Always confirm a signal by checking that trend, volume, and VWAP agree on the dashboard. A green “Strong Buy” arrow with green trend, green volume, and price > VWAP is highest probability.
• Adjusting Sensitivity : To reduce false signals in fast markets, enable DI Reversal Confirmation and Dynamic Thresholds. For more frequent entries in trending environments, enable Early Entry Trigger.
• Risk Management : This tool does not plot stop loss or take profit levels. Users should define their own risk parameters based on support/resistance or volatility bands.
Background Shading
To give you an at-a-glance sense of market regime without reading numbers, the indicator automatically tints the chart background in three modes—neutral, bullish and bearish—with two levels of intensity (light vs. dark):
Neutral (Gray)
When ADX is below 20 the market is considered “no trend” or too weak to trade. The background fills with a light gray (high transparency) so you know to sit on your hands.
Bullish (Green)
As soon as ADX rises above 20 and +DI exceeds –DI, the background turns a semi-transparent green, signaling an emerging uptrend. When ADX climbs above 30 (strong trend), the green becomes more opaque—reminding you that trend-following signals (Strong Buy, Pullback) carry extra weight.
Bearish (Red)
Similarly, if –DI exceeds +DI with ADX >20, you get a light red tint for a developing downtrend, and a darker, more solid red once ADX surpasses 30.
By dynamically varying both hue (green vs. red vs. gray) and opacity (light vs. dark), the background instantly communicates trend strength and direction—so you always know whether to favor breakout-style entries (in a strong trend) or stay flat during choppy, low-ADX conditions.
The setup shown in the above chart snapshot is BTCUSD 15 min chart : Binance for reference.
Disclaimer
No indicator guarantees profits. Backtest or paper trade this tool to understand its behavior in your market. Always use proper position sizing and stop loss orders.
Good luck!
- BullByte
Combined EMA Technical AnalysisThis script is written in Pine Script (version 5) for TradingView and creates a comprehensive technical analysis indicator called "Combined EMA Technical Analysis." It overlays multiple technical indicators on a price chart, including Exponential Moving Averages (EMAs), VWAP, MACD, PSAR, RSI, Bollinger Bands, ADX, and external data from the S&P 500 (SPX) and VIX indices. The script also provides visual cues through colors, shapes, and a customizable table to help traders interpret market conditions.
Here’s a breakdown of the script:
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### **1. Purpose**
- The script combines several popular technical indicators to analyze price trends, momentum, volatility, and market sentiment.
- It uses color coding (green for bullish, red for bearish, gray/white for neutral) and a table to display key information.
---
### **2. Custom Colors**
- Defines custom RGB colors for bullish (`customGreen`), bearish (`customRed`), and neutral (`neutralGray`) signals to enhance visual clarity.
---
### **3. User Inputs**
- **EMA Colors**: Users can customize the colors of five EMAs (8, 20, 9, 21, 50 periods).
- **MACD Settings**: Adjustable short length (12), long length (26), and signal length (9).
- **RSI Settings**: Adjustable length (14).
- **Bollinger Bands Settings**: Length (20), multiplier (2), and proximity threshold (0.1% of band width).
- **ADX Settings**: Adjustable length (14).
- **Table Settings**: Position (e.g., "Bottom Right") and text size (e.g., "Small").
---
### **4. Indicator Calculations**
#### **Exponential Moving Averages (EMAs)**
- Calculates five EMAs: 8, 20, 9, 21, and 50 periods based on the closing price.
- Used to identify short-term and long-term trends.
#### **Volume Weighted Average Price (VWAP)**
- Resets daily and calculates the average price weighted by volume.
- Color-coded: green if price > VWAP (bullish), red if price < VWAP (bearish), white if neutral.
#### **MACD (Moving Average Convergence Divergence)**
- Uses short (12) and long (26) EMAs to compute the MACD line, with a 9-period signal line.
- Displays "Bullish" (green) if MACD > signal, "Bearish" (red) if MACD < signal.
#### **Parabolic SAR (PSAR)**
- Calculated with acceleration factors (start: 0.02, increment: 0.02, max: 0.2).
- Indicates trend direction: green if price > PSAR (bullish), red if price < PSAR (bearish).
#### **Relative Strength Index (RSI)**
- Measures momentum over 14 periods.
- Highlighted in green if > 70 (overbought), red if < 30 (oversold), white otherwise.
#### **Bollinger Bands (BB)**
- Uses a 20-period SMA with a 2-standard-deviation multiplier.
- Color-coded based on price position:
- Green: Above upper band or close to it.
- Red: Below lower band or close to it.
- Gray: Neutral (within bands).
#### **Average Directional Index (ADX)**
- Manually calculates ADX to measure trend strength:
- Strong trend: ADX > 25.
- Very strong trend: ADX > 50.
- Direction: Bullish if +DI > -DI, bearish if -DI > +DI.
#### **EMA Crosses**
- Detects bullish (crossover) and bearish (crossunder) events for:
- EMA 9 vs. EMA 21.
- EMA 8 vs. EMA 20.
- Visualized with green (bullish) or red (bearish) circles.
#### **SPX and VIX Data**
- Fetches daily closing prices for the S&P 500 (SPX) and VIX (volatility index).
- SPX trend: Bullish if EMA 9 > EMA 21, bearish if EMA 9 < EMA 21.
- VIX levels: High (> 25, fear), Low (< 15, stability).
- VIX color: Green if SPX bullish and VIX low, red if SPX bearish and VIX high, white otherwise.
---
### **5. Visual Outputs**
#### **Plots**
- EMAs, VWAP, and PSAR are plotted on the chart with their respective colors.
- EMA crosses are marked with circles (green for bullish, red for bearish).
#### **Table**
- Displays a summary of indicators in a customizable position and size.
- Indicators shown (if enabled):
- EMA 8/20, 9/21, 50: Green dot if bullish, red if bearish.
- VWAP: Green if price > VWAP, red if price < VWAP.
- MACD: Green if bullish, red if bearish.
- MACD Zero: Green if MACD > 0, red if MACD < 0.
- PSAR: Green if price > PSAR, red if price < PSAR.
- ADX: Arrows for very strong trends (↑/↓), dots for weaker trends, colored by direction.
- Bollinger Bands: Arrows (↑/↓) or dots based on price position.
- RSI: Numeric value, colored by overbought/oversold levels.
- VIX: Numeric value, colored based on SPX trend and VIX level.
---
### **6. Alerts**
- Triggers alerts for EMA 8/20 crosses:
- Bullish: "EMA 8/20 Bullish Cross on Candle Close!"
- Bearish: "EMA 8/20 Bearish Cross on Candle Close!"
---
### **7. Key Features**
- **Flexibility**: Users can toggle indicators on/off in the table and adjust parameters.
- **Visual Clarity**: Consistent use of green (bullish), red (bearish), and neutral colors.
- **Comprehensive**: Combines trend, momentum, volatility, and market sentiment indicators.
---
### **How to Use**
1. Add the script to TradingView.
2. Customize inputs (colors, lengths, table position) as needed.
3. Interpret the chart and table:
- Green signals suggest bullish conditions.
- Red signals suggest bearish conditions.
- Neutral signals indicate indecision or consolidation.
4. Set up alerts for EMA crosses to catch trend changes.
This script is ideal for traders who want a multi-indicator dashboard to monitor price action and market conditions efficiently.
Optimized WPR Strategy with Filters (Debug)Identifying Market Trends:
The 200-period EMA is used to determine the short-term trend of the market.
When the price is above the 200-period EMA, it suggests a potential bullish market and an uptrend, and the strategy will only look for buying opportunities.
When the price is below the 200-period EMA, it suggests a potential bearish market and a downtrend, and the strategy will only look for selling opportunities.
When the 200-period EMA intersects with the price, it indicates that the market may be in a directionless consolidation phase.
Identifying Potential Reversal Points:
The strategy employs two Williams %R (WPR) indicators: one with a 9-period (fast WPR) and another with a 28-period (slow WPR).
WPR is a momentum indicator used to identify overbought and oversold conditions in the market. Its value oscillates between -100 and 0, with values near -100 indicating oversold conditions and values near 0 indicating overbought conditions.
In an uptrend (when the price is above the 200 EMA), the strategy seeks buying opportunities when both WPR indicators cross above -80 (the oversold zone) from below. This is considered a bullish signal, suggesting the market may be about to rebound. Sell signals are ignored at this time.
In a downtrend (when the price is below the 200 EMA), the strategy seeks selling opportunities when both WPR indicators cross below -20 (the overbought zone) from above. This is considered a bearish signal, suggesting the market may be about to reverse downward. Buy signals are ignored at this time.
Summary:
In summary, this strategy first uses the 200-period EMA to determine the overall trend direction of the market. Then, within the confirmed trend direction, it utilizes the simultaneous crossing of the overbought or oversold zones by the dual WPR indicators to identify potential reversal points as entry signals for trading. The strategy emphasizes that trading signals are only valid when both WPR indicators meet the conditions.
[GYTS-CE] Market Regime Detector🧊 Market Regime Detector (Community Edition)
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is the Market Regime Detector?
The Market Regime Detector is an advanced, consensus-based indicator that identifies the current market state to increase the probability of profitable trades. By distinguishing between trending (bullish or bearish) and cyclic (range-bound) market conditions, this detector helps you select appropriate tactics for different environments. Instead of forcing a single strategy across all market conditions, our detector allows you to adapt your approach based on real-time market behaviour.
💮 The Importance of Market Regimes
Markets constantly shift between different behavioural states or "regimes":
• Bullish trending markets - characterised by sustained upward price movement
• Bearish trending markets - characterised by sustained downward price movement
• Cyclic markets - characterised by range-bound, oscillating behaviour
Each regime requires fundamentally different trading approaches. Trend-following strategies excel in trending markets but fail in cyclic ones, while mean-reversion strategies shine in cyclic markets but underperform in trending conditions. Detecting these regimes is essential for successful trading, which is why we've developed the Market Regime Detector to accurately identify market states using complementary detection methods.
🌸 --------- KEY FEATURES --------- 🌸
💮 Consensus-Based Detection
Rather than relying on a single method, our detector employs two complementary detection methodologies that analyse different aspects of market behaviour:
• Dominant Cycle Average (DCA) - analyzes price movement relative to its lookback period, a proxy for the dominant cycle
• Volatility Channel - examines price behaviour within adaptive volatility bands
These diverse perspectives are synthesised into a robust consensus that minimises false signals while maintaining responsiveness to genuine regime changes.
💮 Dominant Cycle Framework
The Market Regime Detector uses the concept of dominant cycles to establish a reference framework. You can input the dominant cycle period that best represents the natural rhythm of your market, providing a stable foundation for regime detection across different timeframes.
💮 Intuitive Parameter System
We've distilled complex technical parameters into intuitive controls that traders can easily understand:
• Adaptability - how quickly the detector responds to changing market conditions
• Sensitivity - how readily the detector identifies transitions between regimes
• Consensus requirement - how much agreement is needed among detection methods
This approach makes the detector accessible to traders of all experience levels while preserving the power of the underlying algorithms.
💮 Visual Market Feedback
The detector provides clear visual feedback about the current market regime through:
• Colour-coded chart backgrounds (purple shades for bullish, pink for bearish, yellow for cyclic)
• Colour-coded price bars
• Strength indicators showing the degree of consensus
• Customizable colour schemes to match your preferences or trading system
💮 Integration in the GYTS suite
The Market Regime Detector is compatible with the GYTS Suite , i.e. it passes the regime into the 🎼 Order Orchestrator where you can set how to trade the trending and cyclic regime.
🌸 --------- CONFIGURATION SETTINGS --------- 🌸
💮 Adaptability
Controls how quickly the Market Regime detector adapts to changing market conditions. You can see it as a low-frequency, long-term change parameter:
Very Low: Very slow adaptation, most stable but may miss regime changes
Low: Slower adaptation, more stability but less responsiveness
Normal: Balanced between stability and responsiveness
High: Faster adaptation, more responsive but less stable
Very High: Very fast adaptation, highly responsive but may generate false signals
This setting affects lookback periods and filter parameters across all detection methods.
💮 Sensitivity
Controls how sensitive the detector is to market regime transitions. This acts as a high-frequency, short-term change parameter:
Very Low: Requires substantial evidence to identify a regime change
Low: Less sensitive, reduces false signals but may miss some transitions
Normal: Balanced sensitivity suitable for most markets
High: More sensitive, detects subtle regime changes but may have more noise
Very High: Very sensitive, detects minor fluctuations but may produce frequent changes
This setting affects thresholds for regime detection across all methods.
💮 Dominant Cycle Period
This parameter allows you to specify the market's natural rhythm in bars. This represents a complete market cycle (up and down movement). Finding the right value for your specific market and timeframe might require some experimentation, but it's a crucial parameter that helps the detector accurately identify regime changes. Most of the times the cycle is between 20 and 40 bars.
💮 Consensus Mode
Determines how the signals from both detection methods are combined to produce the final market regime:
• Any Method (OR) : Signals bullish/bearish if either method detects that regime. If methods conflict (one bullish, one bearish), the stronger signal wins. More sensitive, catches more regime changes but may produce more false signals.
• All Methods (AND) : Signals only when both methods agree on the regime. More conservative, reduces false signals but might miss some legitimate regime changes.
• Weighted Decision : Balances both methods with equal weighting. Provides a middle ground between sensitivity and stability.
Each mode also calculates a continuous regime strength value that's used for colour intensity in the 'unconstrained' display mode.
💮 Display Mode
Choose how to display the market regime colours:
• Unconstrained regime: Shows the regime strength as a continuous gradient. This provides more nuanced visualisation where the intensity of the colour indicates the strength of the trend.
• Consensus only: Shows only the final consensus regime with fixed colours based on the detected regime type.
The background and bar colours will change to indicate the current market regime:
• Purple shades: Bullish trending market (darker purple indicates stronger bullish trend)
• Pink shades: Bearish trending market (darker pink indicates stronger bearish trend)
• Yellow: Cyclic (range-bound) market
💮 Custom Colour Options
The Market Regime Detector allows you to customize the colour scheme to match your personal preferences or to coordinate with other indicators:
• Use custom colours: Toggle to enable your own colour choices instead of the default scheme
• Transparency: Adjust the transparency level of all regime colours
• Bullish colours: Define custom colours for strong, medium, weak, and very weak bullish trends
• Bearish colours: Define custom colours for strong, medium, weak, and very weak bearish trends
• Cyclic colour: Define a custom colour for cyclic (range-bound) market conditions
🌸 --------- DETECTION METHODS --------- 🌸
💮 Dominant Cycle Average (DCA)
The Dominant Cycle Average method forms a key part of our detection system:
1. Theoretical Foundation :
The DCA method builds on cycle analysis and the observation that in trending markets, price consistently remains on one side of a moving average calculated using the dominant cycle period. In contrast, during cyclic markets, price oscillates around this average.
2. Calculation Process :
• We calculate a Simple Moving Average (SMA) using the specified lookback period - a proxy for the dominant cycle period
• We then analyse the proportion of time that price spends above or below this SMA over a lookback window. The theory is that the price should cross the SMA each half cycle, assuming that the dominant cycle period is correct and price follows a sinusoid.
• This lookback window is adaptive, scaling with the dominant cycle period (controlled by the Adaptability setting)
• The different values are standardised and normalised to possess more resolving power and to be more robust to noise.
3. Regime Classification :
• When the normalised proportion exceeds a positive threshold (determined by Sensitivity setting), the market is classified as bullish trending
• When it falls below a negative threshold, the market is classified as bearish trending
• When the proportion remains between these thresholds, the market is classified as cyclic
💮 Volatility Channel
The Volatility Channel method complements the DCA method by focusing on price movement relative to adaptive volatility bands:
1. Theoretical Foundation :
This method is based on the observation that trending markets tend to sustain movement outside of normal volatility ranges, while cyclic markets tend to remain contained within these ranges. By creating adaptive bands that adjust to current market volatility, we can detect when price behaviour indicates a trending or cyclic regime.
2. Calculation Process :
• We first calculate a smooth base channel center using a low pass filter, creating a noise-reduced centreline for price
• True Range (TR) is used to measure market volatility, which is then smoothed and scaled by the deviation factor (controlled by Sensitivity)
• Upper and lower bands are created by adding and subtracting this scaled volatility from the centreline
• Price is smoothed using an adaptive A2RMA filter, which has a very flat and stable behaviour, to reduce noise while preserving trend characteristics
• The position of this smoothed price relative to the bands is continuously monitored
3. Regime Classification :
• When smoothed price moves above the upper band, the market is classified as bullish trending
• When smoothed price moves below the lower band, the market is classified as bearish trending
• When price remains between the bands, the market is classified as cyclic
• The magnitude of price's excursion beyond the bands is used to determine trend strength
4. Adaptive Behaviour :
• The smoothing periods and deviation calculations automatically adjust based on the Adaptability setting
• The measured volatility is calculated over a period proportional to the dominant cycle, ensuring the detector works across different timeframes
• Both the center line and the bands adapt dynamically to changing market conditions, making the detector responsive yet stable
This method provides a unique perspective that complements the DCA approach, with the consensus mechanism synthesising insights from both methods.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Starting with Default Settings
The default settings (Normal for Adaptability and Sensitivity, Weighted Decision for Consensus Mode) provide a balanced starting point suitable for most markets and timeframes. Begin by observing how these settings identify regimes in your preferred instruments.
💮 Finding the Optimal Dominant Cycle
The dominant cycle period is a critical parameter. Here are some approaches to finding an appropriate value:
• Start with typical values, usually something around 25 works well
• Visually identify the average distance between significant peaks and troughs
• Experiment with different values and observe which provides the most stable regime identification
• Consider using cycle-finding indicators to help identify the natural rhythm of your market
💮 Adjusting Parameters
• If you notice too many regime changes → Decrease Sensitivity or increase Consensus requirement
• If regime changes seem delayed → Increase Adaptability
• If a trending regime is not detected, the market is automatically assigned to be in a cyclic state
• If you want to see more nuanced regime transitions → Try the "unconstrained" display mode (note that this will not affect the output to other indicators)
💮 Trading Applications
Regime-Specific Strategies:
• Bullish Trending Regime - Use trend-following strategies, trail stops wider, focus on breakouts, consider holding positions longer, and emphasize buying dips
• Bearish Trending Regime - Consider shorts, tighter stops, focus on breakdown points, sell rallies, implement downside protection, and reduce position sizes
• Cyclic Regime - Apply mean-reversion strategies, trade range boundaries, apply oscillators, target definable support/resistance levels, and use profit-taking at extremes
Strategy Switching:
Create a set of rules for each market regime and switch between them based on the detector's signal. This approach can significantly improve performance compared to applying a single strategy across all market conditions.
GYTS Suite Integration:
• In the GYTS 🎼 Order Orchestrator, select the '🔗 STREAM-int 🧊 Market Regime' as the market regime source
• Note that the consensus output (i.e. not the "unconstrained" display) will be used in this stream
• Create different strategies for trending (bullish/bearish) and cyclic regimes. The GYTS 🎼 Order Orchestrator is specifically made for this.
• The output stream is actually very simple, and can possibly be used in indicators and strategies as well. It outputs 1 for bullish, -1 for bearish and 0 for cyclic regime.
🌸 --------- FINAL NOTES --------- 🌸
💮 Development Philosophy
The Market Regime Detector has been developed with several key principles in mind:
1. Robustness - The detection methods have been rigorously tested across diverse markets and timeframes to ensure reliable performance.
2. Adaptability - The detector automatically adjusts to changing market conditions, requiring minimal manual intervention.
3. Complementarity - Each detection method provides a unique perspective, with the collective consensus being more reliable than any individual method.
4. Intuitiveness - Complex technical parameters have been abstracted into easily understood controls.
💮 Ongoing Refinement
The Market Regime Detector is under continuous development. We regularly:
• Fine-tune parameters based on expanded market data
• Research and integrate new detection methodologies
• Optimise computational efficiency for real-time analysis
Your feedback and suggestions are very important in this ongoing refinement process!
*Auto Backtest & Optimize EngineFull-featured Engine for Automatic Backtesting and parameter optimization. Allows you to test millions of different combinations of stop-loss and take profit parameters, including on any connected indicators.
⭕️ Key Futures
Quickly identify the optimal parameters for your strategy.
Automatically generate and test thousands of parameter combinations.
A simple Genetic Algorithm for result selection.
Saves time on manual testing of multiple parameters.
Detailed analysis, sorting, filtering and statistics of results.
Detailed control panel with many tooltips.
Display of key metrics: Profit, Win Rate, etc..
Comprehensive Strategy Score calculation.
In-depth analysis of the performance of different types of stop-losses.
Possibility to use to calculate the best Stop-Take parameters for your position.
Ability to test your own functions and signals.
Customizable visualization of results.
Flexible Stop-Loss Settings:
• Auto ━ Allows you to test all types of Stop Losses at once(listed below).
• S.VOLATY ━ Static stop based on volatility (Fixed, ATR, STDEV).
• Trailing ━ Classic trailing stop following the price.
• Fast Trail ━ Accelerated trailing stop that reacts faster to price movements.
• Volatility ━ Dynamic stop based on volatility indicators.
• Chandelier ━ Stop based on price extremes.
• Activator ━ Dynamic stop based on SAR.
• MA ━ Stop based on moving averages (9 different types).
• SAR ━ Parabolic SAR (Stop and Reverse).
Advanced Take-Profit Options:
• R:R: Risk/Reward ━ sets TP based on SL size.
• T.VOLATY ━ Calculation based on volatility indicators (Fixed, ATR, STDEV).
Testing Modes:
• Stops ━ Cyclical stop-loss testing
• Pivot Point Example ━ Example of using pivot points
• External Example ━ Built-in example how test functions with different parameters
• External Signal ━ Using external signals
⭕️ Usage
━ First Steps:
When opening, select any point on the chart. It will not affect anything until you turn on Manual Start mode (more on this below).
The chart will immediately show the best results of the default Auto mode. You can switch Part's to try to find even better results in the table.
Now you can display any result from the table on the chart by entering its ID in the settings.
Repeat steps 3-4 until you determine which type of Stop Loss you like best. Then set it in the settings instead of Auto mode.
* Example: I flipped through 14 parts before I liked the first result and entered its ID so I could visually evaluate it on the chart.
Then select the stop loss type, choose it in place of Auto mode and repeat steps 3-4 or immediately follow the recommendations of the algorithm.
Now the Genetic Algorithm at the bottom right will prompt you to enter the Parameters you need to search for and select even better results.
Parameters must be entered All at once before they are updated. Enter recommendations strictly in fields with the same names.
Repeat steps 5-6 until there are approximately 10 Part's left or as you like. And after that, easily pour through the remaining Parts and select the best parameters.
━ Example of the finished result.
━ Example of use with Takes
You can also test at the same time along with Take Profit. In this example, I simply enabled Risk/Reward mode and immediately specified in the TP field Maximum RR, Minimum RR and Step. So in this example I can test (3-1) / 0.1 = 20 Takes of different sizes. There are additional tips in the settings.
━
* Soon you will start to understand how the system works and things will become much easier.
* If something doesn't work, just reset the engine settings and start over again.
* Use the tips I have left in the settings and on the Panel.
━ Details:
Sort ━ Sorting results by Score, Profit, Trades, etc..
Filter ━ Filtring results by Score, Profit, Trades, etc..
Trade Type ━ Ability to disable Long\Short but only from statistics.
BackWin ━ Backtest Window Number of Candle the script can test.
Manual Start ━ Enabling it will allow you to call a Stop from a selected point. which you selected when you started the engine.
* If you have a real open position then this mode can help to save good Stop\Take for it.
1 - 9 Сheckboxs ━ Allow you to disable any stop from Auto mode.
Ex Source - Allow you to test Stops/Takes from connected indicators.
Connection guide:
//@version=6
indicator("My script")
rsi = ta.rsi(close, 14)
buy = not na(rsi) and ta.crossover (rsi, 40) // OS = 40
sell = not na(rsi) and ta.crossunder(rsi, 60) // OB = 60
Signal = buy ? +1 : sell ? -1 : 0
plot(Signal, "🔌Connector🔌", display = display.none)
* Format the signal for your indicator in a similar style and then select it in Ex Source.
⭕️ How it Works
Hypothesis of Uniform Distribution of Rare Elements After Mixing.
'This hypothesis states that if an array of N elements contains K valid elements, then after mixing, these valid elements will be approximately uniformly distributed.'
'This means that in a random sample of k elements, the proportion of valid elements should closely match their proportion in the original array, with some random variation.'
'According to the central limit theorem, repeated sampling will result in an average count of valid elements following a normal distribution.'
'This supports the assumption that the valid elements are evenly spread across the array.'
'To test this hypothesis, we can conduct an experiment:'
'Create an array of 1,000,000 elements.'
'Select 1,000 random elements (1%) for validation.'
'Shuffle the array and divide it into groups of 1,000 elements.'
'If the hypothesis holds, each group should contain, on average, 1~ valid element, with minor variations.'
* I'd like to attach more details to My hypothesis but it won't be very relevant here. Since this is a whole separate topic, I will leave the minimum part for understanding the engine.
Practical Application
To apply this hypothesis, I needed a way to generate and thoroughly mix numerous possible combinations. Within Pine, generating over 100,000 combinations presents significant challenges, and storing millions of combinations requires excessive resources.
I developed an efficient mechanism that generates combinations in random order to address these limitations. While conventional methods often produce duplicates or require generating a complete list first, my approach guarantees that the first 10% of possible combinations are both unique and well-distributed. Based on my hypothesis, this sampling is sufficient to determine optimal testing parameters.
Most generators and randomizers fail to accommodate both my hypothesis and Pine's constraints. My solution utilizes a simple Linear Congruential Generator (LCG) for pseudo-randomization, enhanced with prime numbers to increase entropy during generation. I pre-generate the entire parameter range and then apply systematic mixing. This approach, combined with a hybrid combinatorial array-filling technique with linear distribution, delivers excellent generation quality.
My engine can efficiently generate and verify 300 unique combinations per batch. Based on the above, to determine optimal values, only 10-20 Parts need to be manually scrolled through to find the appropriate value or range, eliminating the need for exhaustive testing of millions of parameter combinations.
For the Score statistic I applied all the same, generated a range of Weights, distributed them randomly for each type of statistic to avoid manual distribution.
Score ━ based on Trade, Profit, WinRate, Profit Factor, Drawdown, Sharpe & Sortino & Omega & Calmar Ratio.
⭕️ Notes
For attentive users, a little tricks :)
To save time, switch parts every 3 seconds without waiting for it to load. After 10-20 parts, stop and wait for loading. If the pause is correct, you can switch between the rest of the parts without loading, as they will be cached. This used to work without having to wait for a pause, but now it does slower. This will save a lot of time if you are going to do a deeper backtest.
Sometimes you'll get the error “The scripts take too long to execute.”
For a quick fix you just need to switch the TF or Ticker back and forth and most likely everything will load.
The error appears because of problems on the side of the site because the engine is very heavy. It can also appear if you set too long a period for testing in BackWin or use a heavy indicator for testing.
Manual Start - Allow you to Start you Result from any point. Which in turn can help you choose a good stop-stick for your real position.
* It took me half a year from idea to current realization. This seems to be one of the few ways to build something automatic in backtest format and in this particular Pine environment. There are already better projects in other languages, and they are created much easier and faster because there are no limitations except for personal PC. If you see solutions to improve this system I would be glad if you share the code. At the moment I am tired and will continue him not soon.
Also You can use my previosly big Backtest project with more manual settings(updated soon)
