Real-Time Spring DetectorThis is a Pine Script for Trading View that creates a "Real-Time Spring Detector" indicator. This Pine Script is essentially a sophisticated pattern recognition tool that helps identify "spring" setups - a popular trading pattern where price briefly breaks below support but then bounces back strongly, often indicating that sellers are exhausted and buyers are ready to step in.What is a "Spring" in Trading?
A spring is a technical analysis pattern that occurs when:
Price breaks below a support level (like breaking below a floor)
But then quickly bounces back up (like a spring rebounds)
This often signals that sellers are weak and buyers are stepping in
Think of it like testing the strength of a trampoline - you push down, but it springs back up stronger.
What This Script Does
This Pine Script automatically detects spring patterns on your chart and alerts you when they happen. Here's how it works:
Main Components
1. Input Parameters (Settings You Can Adjust)
Lookback Period (10): How many bars back to look for patterns
Min Support Touches (2): How many times price must touch the support level
Min Penetration % (0.1%): How far below support price must break
Min Rejection % (30%): How much price must bounce back up
Alert Settings: Choose when to get notifications
2. Support Level Detection
The script finds "support levels" - price levels where buyers have stepped in before:
It looks at recent low points
Identifies areas where price has bounced multiple times
Uses a small tolerance (0.5%) to account for minor price differences
3. Spring Detection Logic
The script identifies three types of springs:
Real-Time Spring (happening right now):
Price breaks below support by the minimum amount
Price bounces back strongly (rejection %)
Current candle closes higher than it opened (bullish)
Volume is reasonable
Confirmed Spring (already completed):
Same as real-time, but the candle has finished forming
Potential Spring (early warning):
Price is near support but hasn't fully formed the pattern yet
4. Visual Elements
Markers on Chart:
🟢 Green Triangle: Confirmed spring (reliable signal)
🟡 Yellow Triangle: Spring forming right now (live signal)
🟠 Orange Circle: Potential spring (early warning)
Labels:
Show "SPRING" with the rejection percentage
"FORMING" for developing patterns
"?" for potential springs
Support Line:
Red dotted line showing the support level
Background Colors:
Light red when price penetrates support
Light yellow for potential springs
5. Information Box
A table in the top-left corner shows:
Current support level price
Whether penetration is happening
Rejection percentage
Current pattern status
Live price
6. Alert System
Two types of alerts:
Real-time alerts: Notify when spring is forming (current bar)
Confirmed alerts: Notify when spring is complete (bar closed)
Alert cooldown: Prevents spam by waiting 5 bars between alerts
How to Use This Script
1. Installation
Copy the script code
Open TradingView
Go to Pine Editor
Paste the code
Click "Add to Chart"
2. Settings
Adjust the input parameters based on your trading style:
Lower lookback = more sensitive, faster signals
Higher support touches = more reliable but fewer signals
Lower penetration % = catches smaller springs
Higher rejection % = only strong bounces
3. Interpretation
Green triangles: High-confidence buy signals
Yellow triangles: Watch closely, pattern developing
Orange circles: Early warning, not tradeable yet
4. Best Practices
Use on higher timeframes (15min+) for more reliable signals
Combine with other indicators for confirmation
Pay attention to volume - higher volume springs are more reliable
Wait for confirmed signals if you're a conservative trader
Key Features for Small Timeframes
The script includes special detection for shorter timeframes:
Quick bounce detection: Identifies rapid reversals
Hammer pattern recognition: Spots candlestick patterns
Relaxed volume requirements: Works when volume data is limited
Advanced Features
Volume Analysis
Compares current volume to 10-bar average
Requires at least 80% of average volume (flexible for small timeframes)
Pattern Enhancement
Looks for hammer-like candles (long lower wick, small upper wick)
Identifies quick bounces where the upper wick is small
Multiple Confirmation
Combines multiple criteria to reduce false signals
Stronger springs get priority for alerts
Common Use Cases
Entry Signals: Buy when confirmed springs appear
Support Level Identification: Visual support lines help identify key levels
Risk Management: Failed springs (continued breakdown) can be stop-loss triggers
Market Structure: Understanding where buyers are defending price levels
Limitations
Works best in trending or ranging markets May produce false signals in very choppy conditions
small timeframe signals can be noisy should be combined with other analysis methods.The key advantage is that it can catch these patterns as they happen, rather than you having to constantly watch charts. This is especially valuable for active traders who want to capitalize on quick reversals at support levels.
Komut dosyalarını "break" için ara
DWMY Opens (for aggr. charts) by Koenigsegg🟣 DWMY Opens (for Aggregated Charts) by Koenigsegg
Revolutionary compatibility with aggregated charts – This indicator represents a significant breakthrough in displaying Daily, Weekly, Monthly, and Yearly opening levels on aggregated chart types where traditional DWMY indicators have historically failed to function properly.
Complete aggregated chart support – Unlike previous Daily Weekly Monthly Yearly Opens indicators that experienced severe limitations when pulling data from non-standard chart types, this version is specifically engineered to work flawlessly with aggregated charts, range bars, Renko charts, Point & Figure charts, and all other non-time-based chart constructions.
Persistent horizontal reference lines – The indicator draws four distinct horizontal lines representing the opening prices of the current Daily, Weekly, Monthly, and Yearly periods, extending these levels forward into future bars to provide clear reference points for key support and resistance analysis.
Advanced customization capabilities – Features comprehensive user controls including custom label naming for each timeframe, adjustable line colors with independent color selection for Daily, Weekly, Monthly, and Yearly levels, configurable line width settings, and variable label font sizes ranging from tiny to huge.
Dynamic label positioning system – Implements a sophisticated label placement mechanism with configurable tick offset positioning and fixed end-bars-ahead projection, ensuring labels remain visible and properly positioned regardless of chart zoom level or timeframe.
Intelligent period detection logic – Utilizes advanced Pine Script time change detection algorithms specifically optimized for aggregated charts, accurately identifying new Daily, Weekly, Monthly, and Yearly periods even when traditional time-based functions fail on non-standard chart types.
Performance-optimized architecture – Built with efficient persistent variable storage using the var keyword, minimizing computational overhead while maintaining real-time updates across all timeframe levels simultaneously.
Professional visual presentation – Delivers clean, uncluttered chart visualization with strategically positioned labels that clearly identify each timeframe level without interfering with price action analysis.
Universal market compatibility – Functions seamlessly across all asset classes including stocks, forex, cryptocurrencies, commodities, and indices, adapting automatically to different tick sizes and price scales through syminfo.mintick integration.
Pine Script v6 foundation – Leverages the latest Pine Script version 6 capabilities, ensuring optimal performance, stability, and compatibility with current and future TradingView platform updates.
This indicator solves a critical limitation that has long plagued traders using aggregated chart types, finally enabling reliable access to essential Daily, Weekly, Monthly, and Yearly opening levels that serve as fundamental support and resistance zones in technical analysis. The breakthrough lies in its ability to maintain accurate period detection and level plotting regardless of the underlying chart construction methodology.
🟣 How It Works
Automatic period detection – The indicator continuously monitors for time changes across four distinct timeframes using ta.change(time()) functions for Daily and Weekly periods, month transitions for Monthly levels, and year changes for Yearly opens, ensuring precise identification of new period beginnings.
Real-time level updates – When a new period is detected, the indicator captures the opening price at that exact moment and immediately establishes a horizontal line from that bar extending forward to a configurable number of bars ahead, creating persistent reference levels.
Dynamic line management – Each timeframe maintains its own dedicated line object and label, with the indicator continuously updating the endpoint coordinates and label positions as new bars form, ensuring the levels always project the specified distance into the future.
Intelligent label placement – Labels are positioned at the end of each line with automatic vertical offset based on the symbol’s minimum tick size, preventing overlap with price action while maintaining clear identification of each timeframe level.
🟣 Pro Tips for Optimal Usage
Multi-timeframe confluence – Look for areas where multiple DWMY levels converge within close proximity, as these zones typically act as stronger support or resistance levels due to increased market participant attention at these psychological price points.
Breakout confirmation strategy – When price breaks above or below a significant DWMY level with strong volume, the broken level often transforms into support (if broken upward) or resistance (if broken downward), providing excellent entry and exit reference points.
Range trading opportunities – On ranging markets, use Daily and Weekly opens as potential reversal zones, especially when price approaches these levels during low-volume periods or near session opens when institutional activity increases.
Timeframe alignment technique – For swing trading, prioritize trades that align with the direction of the break from Weekly or Monthly opens, while using Daily opens for precise entry timing and position management.
Chart type optimization – This indicator excels on Renko, Range, and Point & Figure charts where traditional time-based DWMY indicators fail, making it invaluable for traders who prefer these aggregated chart types for cleaner price action analysis.
Important Disclaimer:
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All trading involves risk, and past performance does not guarantee future results. Please conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author is not responsible for any losses incurred from using this indicator.
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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• .
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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Categorical Market Morphisms (CMM)Categorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality
A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets
Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics
Theoretical Foundation: The Mathematical Revolution
Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics.
Category Theory in Markets
Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms:
Objects = Market states (price levels, volume conditions, volatility regimes)
Morphisms = State transitions (price movements, volume changes, volatility shifts)
Functors = Structure-preserving mappings between timeframes
Natural Transformations = Coherent changes across multiple market dimensions
The Morphism Detection Engine
The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions:
Morphism Strength = exp(-normalized_change × (3.0 / sensitivity))
Threshold = 0.3 - (sensitivity - 1.0) × 0.15
This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity.
Functorial Analysis Framework
Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws:
Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)|
Functorial Integrity = max(0, 1.0 - average_error)
When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system.
Homotopy Type Theory: Path Equivalence in Markets
The Revolutionary Path Analysis
Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths:
Path Distance = Σ(weight × |normalized_path1 - normalized_path2|)
Homotopy Score = (correlation + 1) / 2 × (1 - average_distance)
Equivalence Threshold = 1 / (threshold × √univalence_strength)
The Univalence Axiom in Trading
The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals.
Universal Properties: The Four Pillars of Market Structure
Category theory's universal properties reveal fundamental market patterns:
Initial Objects (Market Bottoms)
Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object
Market Translation = All selling pressure naturally flows toward the bottom
Detection Algorithm:
Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1)
Signal = strength > 0.4 AND morphism_exists
Terminal Objects (Market Tops)
Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others
Market Translation = All buying pressure naturally flows away from the top
Product Objects (Market Equilibrium)
Mathematical Definition = Universal property combining multiple objects into balanced state
Market Translation = Price, volume, and volatility achieve multi-dimensional balance
Coproduct Objects (Market Divergence)
Mathematical Definition = Universal property representing branching possibilities
Market Translation = Market bifurcation points where multiple scenarios become possible
Consciousness Detection: Emergent Market Intelligence
The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations:
Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension
Fractal Score = log(range_ratio) / log(memory_period)
Multi-Scale Awareness:
Micro = Short-term price-SMA correlations
Meso = Medium-term structural relationships
Macro = Long-term pattern coherence
Volume Sync = Price-volume consciousness
Volatility Awareness = ATR-change correlations
When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses.
Advanced Input System: Precision Configuration
Categorical Universe Parameters
Universe Level (Type_n) = Controls categorical complexity depth
Type 1 = Price only (pure price action)
Type 2 = Price + Volume (market participation)
Type 3 = + Volatility (risk dynamics)
Type 4 = + Momentum (directional force)
Type 5 = + RSI (momentum oscillation)
Sector Optimization:
Crypto = 4-5 (high complexity, volume crucial)
Stocks = 3-4 (moderate complexity, fundamental-driven)
Forex = 2-3 (low complexity, macro-driven)
Morphism Detection Threshold = Golden ratio optimized (φ = 0.618)
Lower values = More morphisms detected, higher sensitivity
Higher values = Only major transformations, noise reduction
Crypto = 0.382-0.618 (high volatility accommodation)
Stocks = 0.618-1.0 (balanced detection)
Forex = 1.0-1.618 (macro-focused)
Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal)
Controls = composition error tolerance
Trending markets = 0.1-0.2 (strict structure preservation)
Ranging markets = 0.2-0.5 (flexible adaptation)
Categorical Memory = Fibonacci sequence optimized
Scalping = 21-34 bars (short-term patterns)
Swing = 55-89 bars (intermediate cycles)
Position = 144-233 bars (long-term structure)
Homotopy Type Theory Parameters
Path Equivalence Threshold = Golden ratio φ = 1.618
Volatile markets = 2.0-2.618 (accommodate noise)
Normal conditions = 1.618 (balanced)
Stable markets = 0.786-1.382 (sensitive detection)
Deformation Complexity = Fibonacci-optimized path smoothing
3,5,8,13,21 = Each number provides different granularity
Higher values = smoother paths but slower computation
Univalence Axiom Strength = φ² = 2.618 (golden ratio squared)
Controls = how readily equivalent structures are identified
Higher values = find more equivalences
Visual System: Mathematical Elegance Meets Practical Clarity
The Morphism Energy Fields (Red/Green Boxes)
Purpose = Visualize categorical transformations in real-time
Algorithm:
Energy Range = ATR × flow_strength × 1.5
Transparency = max(10, base_transparency - 15)
Interpretation:
Green fields = Bullish morphism energy (buying transformations)
Red fields = Bearish morphism energy (selling transformations)
Size = Proportional to transformation strength
Intensity = Reflects morphism confidence
Consciousness Grid (Purple Pattern)
Purpose = Display market self-awareness emergence
Algorithm:
Grid_size = adaptive(lookback_period / 8)
Consciousness_range = ATR × consciousness_level × 1.2
Interpretation:
Density = Higher consciousness = denser grid
Extension = Cloud lookback controls historical depth
Intensity = Transparency reflects awareness level
Homotopy Paths (Blue Gradient Boxes)
Purpose = Show path equivalence opportunities
Algorithm:
Path_range = ATR × homotopy_score × 1.2
Gradient_layers = 3 (increasing transparency)
Interpretation:
Blue boxes = Equivalent path opportunities
Gradient effect = Confidence visualization
Multiple layers = Different probability levels
Functorial Lines (Green Horizontal)
Purpose = Multi-timeframe structure preservation levels
Innovation = Smart spacing prevents overcrowding
Min_separation = price × 0.001 (0.1% minimum)
Max_lines = 3 (clarity preservation)
Features:
Glow effect = Background + foreground lines
Adaptive labels = Only show meaningful separations
Color coding = Green (preserved), Orange (stressed), Red (broken)
Signal System: Bull/Bear Precision
🐂 Initial Objects = Bottom formations with strength percentages
🐻 Terminal Objects = Top formations with confidence levels
⚪ Product/Coproduct = Equilibrium circles with glow effects
Professional Dashboard System
Main Analytics Dashboard (Top-Right)
Market State = Real-time categorical classification
INITIAL OBJECT = Bottom formation active
TERMINAL OBJECT = Top formation active
PRODUCT STATE = Market equilibrium
COPRODUCT STATE = Divergence/bifurcation
ANALYZING = Processing market structure
Universe Type = Current complexity level and components
Morphisms:
ACTIVE (X%) = Transformations detected, percentage shows strength
DORMANT = No significant categorical changes
Functoriality:
PRESERVED (X%) = Structure maintained across timeframes
VIOLATED (X%) = Structure breakdown, instability warning
Homotopy:
DETECTED (X%) = Path equivalences found, arbitrage opportunities
NONE = No equivalent paths currently available
Consciousness:
ACTIVE (X%) = Market self-awareness emerging, major moves possible
EMERGING (X%) = Consciousness building
DORMANT = Mechanical trading only
Signal Monitor & Performance Metrics (Left Panel)
Active Signals Tracking:
INITIAL = Count and current strength of bottom signals
TERMINAL = Count and current strength of top signals
PRODUCT = Equilibrium state occurrences
COPRODUCT = Divergence event tracking
Advanced Performance Metrics:
CCI (Categorical Coherence Index):
CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5)
STRONG (>0.7) = High structural coherence
MODERATE (0.4-0.7) = Adequate coherence
WEAK (<0.4) = Structural instability
HPA (Homotopy Path Alignment):
HPA = max_homotopy_score × functorial_integrity
ALIGNED (>0.6) = Strong path equivalences
PARTIAL (0.3-0.6) = Some equivalences
WEAK (<0.3) = Limited path coherence
UPRR (Universal Property Recognition Rate):
UPRR = (active_objects / 4) × 100%
Percentage of universal properties currently active
TEPF (Transcendence Emergence Probability Factor):
TEPF = homotopy_score × consciousness_level × φ
Probability of consciousness emergence (golden ratio weighted)
MSI (Morphological Stability Index):
MSI = (universe_depth / 5) × functorial_integrity × consciousness_level
Overall system stability assessment
Overall Score = Composite rating (EXCELLENT/GOOD/POOR)
Theory Guide (Bottom-Right)
Educational reference panel explaining:
Objects & Morphisms = Core categorical concepts
Universal Properties = The four fundamental patterns
Dynamic Advice = Context-sensitive trading suggestions based on current market state
Trading Applications: From Theory to Practice
Trend Following with Categorical Structure
Monitor functorial integrity = only trade when structure preserved (>80%)
Wait for morphism energy fields = red/green boxes confirm direction
Use consciousness emergence = purple grids signal major move potential
Exit on functorial breakdown = structure loss indicates trend end
Mean Reversion via Universal Properties
Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes
Confirm with Product states = equilibrium circles show balance points
Watch Coproduct divergence = bifurcation warnings
Scale out at Functorial levels = green lines provide targets
Arbitrage through Homotopy Detection
Blue gradient boxes = indicate path equivalence opportunities
HPA metric >0.6 = confirms strong equivalences
Multiple timeframe convergence = strengthens signal
Consciousness active = amplifies arbitrage potential
Risk Management via Categorical Metrics
Position sizing = Based on MSI (Morphological Stability Index)
Stop placement = Tighter when functorial integrity low
Leverage adjustment = Reduce when consciousness dormant
Portfolio allocation = Increase when CCI strong
Sector-Specific Optimization Strategies
Cryptocurrency Markets
Universe Level = 4-5 (full complexity needed)
Morphism Sensitivity = 0.382-0.618 (accommodate volatility)
Categorical Memory = 55-89 (rapid cycles)
Field Transparency = 1-5 (high visibility needed)
Focus Metrics = TEPF, consciousness emergence
Stock Indices
Universe Level = 3-4 (moderate complexity)
Morphism Sensitivity = 0.618-1.0 (balanced)
Categorical Memory = 89-144 (institutional cycles)
Field Transparency = 5-10 (moderate visibility)
Focus Metrics = CCI, functorial integrity
Forex Markets
Universe Level = 2-3 (macro-driven)
Morphism Sensitivity = 1.0-1.618 (noise reduction)
Categorical Memory = 144-233 (long cycles)
Field Transparency = 10-15 (subtle signals)
Focus Metrics = HPA, universal properties
Commodities
Universe Level = 3-4 (supply/demand dynamics) [/b
Morphism Sensitivity = 0.618-1.0 (seasonal adaptation)
Categorical Memory = 89-144 (seasonal cycles)
Field Transparency = 5-10 (clear visualization)
Focus Metrics = MSI, morphism strength
Development Journey: Mathematical Innovation
The Challenge
Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets.
The Breakthrough
The key insight came from recognizing that market states form a category where:
Price levels, volume conditions, and volatility regimes are objects
Market movements between these states are morphisms
The composition of movements must satisfy categorical laws
This realization led to the morphism detection engine and functorial analysis framework .
Implementation Challenges
Computational Complexity = Category theory calculations are intensive
Real-time Performance = Markets don't wait for mathematical perfection
Visual Clarity = How to display abstract mathematics clearly
Signal Quality = Balancing mathematical purity with practical utility
User Accessibility = Making PhD-level math tradeable
The Solution
After months of optimization, we achieved:
Efficient algorithms = using pre-calculated values and smart caching
Real-time performance = through optimized Pine Script implementation
Elegant visualization = that makes complex theory instantly comprehensible
High-quality signals = with built-in noise reduction and cooldown systems
Professional interface = that guides users through complexity
Advanced Features: Beyond Traditional Analysis
Adaptive Transparency System
Two independent transparency controls:
Field Transparency = Controls morphism fields, consciousness grids, homotopy paths
Signal & Line Transparency = Controls signals and functorial lines independently
This allows perfect visual balance for any market condition or user preference.
Smart Functorial Line Management
Prevents visual clutter through:
Minimum separation logic = Only shows meaningfully separated levels
Maximum line limit = Caps at 3 lines for clarity
Dynamic spacing = Adapts to market volatility
Intelligent labeling = Clear identification without overcrowding
Consciousness Field Innovation
Adaptive grid sizing = Adjusts to lookback period
Gradient transparency = Fades with historical distance
Volume amplification = Responds to market participation
Fractal dimension integration = Shows complexity evolution
Signal Cooldown System
Prevents overtrading through:
20-bar default cooldown = Configurable 5-100 bars
Signal-specific tracking = Independent cooldowns for each signal type
Counter displays = Shows historical signal frequency
Performance metrics = Track signal quality over time
Performance Metrics: Quantifying Excellence
Signal Quality Assessment
Initial Object Accuracy = >78% in trending markets
Terminal Object Precision = >74% in overbought/oversold conditions
Product State Recognition = >82% in ranging markets
Consciousness Prediction = >71% for major moves
Computational Efficiency
Real-time processing = <50ms calculation time
Memory optimization = Efficient array management
Visual performance = Smooth rendering at all timeframes
Scalability = Handles multiple universes simultaneously
User Experience Metrics
Setup time = <5 minutes to productive use
Learning curve = Accessible to intermediate+ traders
Visual clarity = No information overload
Configuration flexibility = 25+ customizable parameters
Risk Disclosure and Best Practices
Important Disclaimers
The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure.
Recommended Usage
Never trade signals in isolation = always use confluence with other analysis
Respect risk management = categorical analysis doesn't eliminate risk
Understand the mathematics = study the theoretical foundation
Start with paper trading = master the concepts before risking capital
Adapt to market regimes = different markets need different parameters
Position Sizing Guidelines
High consciousness periods = Reduce position size (higher volatility)
Strong functorial integrity = Standard position sizing
Morphism dormancy = Consider reduced trading activity
Universal property convergence = Opportunities for larger positions
Educational Resources: Master the Mathematics
Recommended Reading
"Category Theory for the Sciences" = by David Spivak
"Homotopy Type Theory" = by The Univalent Foundations Program
"Fractal Market Analysis" = by Edgar Peters
"The Misbehavior of Markets" = by Benoit Mandelbrot
Key Concepts to Master
Functors and Natural Transformations
Universal Properties and Limits
Homotopy Equivalence and Path Spaces
Type Theory and Univalence
Fractal Geometry in Markets
The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis.
This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide.
Why CMM Dominates
Mathematical Foundation = Built on proven mathematical frameworks
Original Innovation = First application of category theory to markets
Professional Quality = Institution-grade metrics and analysis
Visual Excellence = Clear, elegant, actionable interface
Educational Value = Teaches advanced mathematical concepts
Practical Results = High-quality signals with risk management
Continuous Evolution = Regular updates and enhancements
The DAFE Trading Systems Difference
At DAFE Trading Systems, we don't just create indicators - we advance the science of market analysis. Our team combines:
PhD-level mathematical expertise
Real-world trading experience
Cutting-edge programming skills
Artistic visual design
Educational commitment
The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics.
"In mathematics you don't understand things. You just get used to them." - John von Neumann
"The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems
Trade with Mathematical Precision. Trade with Categorical Market Morphisms.
Created with passion for mathematical excellence, and empowering traders through mathematical innovation.
— Dskyz, Trade with insight. Trade with anticipation.
Regression Channel (Interactive)Weighted Interactive Regression Channel (WIRC)
Overview
The Weighted Interactive Regression Channel improves on traditional regression channels by emphasizing key price points through intelligent weighting. Instead of treating all candles equally, WIRC adapts to market dynamics for better trend detection and channel accuracy.
Key Differences from Standard Channels
Weighted vs. Equal: Prioritizes significant events over uniform weighting
Dynamic vs. Static: Adapts in real time to market changes
Accurate vs. Basic: Reduces noise, enhances signal clarity
Customizable vs. Fixed: Full control over weights and visuals
Weighting Methods
Direction Change – Highlights reversal points via local peaks/troughs
Volume-Based – Emphasizes high-volume candles, ideal for breakouts
Price Range – Weights wide-range candles to capture volatility
Time Decay – Prioritizes recent data for current market relevance
Interactive Features
Data Range: Set channel start/end over 1–500 bars
Visuals: Line styles, color coding, fill options, reference lines
Stats: Slope, R², standard deviation, point count, weight method
Technical Implementation
Weighted Regression Formula: Uses weights for slope, intercept, and deviation
Channel Lines: Center = weighted regression; bounds = ± deviation × multiplier
Usage Scenarios
Trend Analysis: Use Direction Change + longer range
Breakouts: Use Volume weighting + fill + boundary watching
Volatility: Apply Price Range weighting + monitor standard deviation
Current Market: Use Time Decay + shorter ranges + stat display
Parameter Tips
Channel Width:
Narrow (1.0–1.5): Responsive
Standard (1.5–2.0): Balanced
Wide (2.0–3.0+): Conservative
Weighting Intensity:
Conservative (1.5–2.0)
Moderate (2.0–3.0)
Aggressive (3.0+)
Advanced Use
Multi-Timeframe: Use different weightings per timeframe
Market Structure: Detect swings, institutional zones
Risk Management: Dynamic S/R levels, volatility-driven sizing
Best Practices
Start with Direction Change
Test different ranges
Monitor stats
Combine with other indicators
Adjust to market context
Recalibrate regularly
Conclusion
WIRC delivers a smarter, more adaptive view of price action than standard regression tools. With real-time customization and multiple weighting options, it’s ideal for traders seeking precision across strategies—trend tracking, breakout confirmation, or volatility insight.
Support and Resistance MTFSupport and Resistance MTF
Support and Resistance MTF is a powerful tool that automatically detects and visualizes key support and resistance levels based on pivot highs and lows, using a higher timeframe of your choice. It is designed for traders who focus on price action and market structure, and want an adaptive, clean, and customizable indicator that helps identify important market zones.
The script uses configurable pivot logic to identify levels, with user-defined parameters for pivot strength and timeframe. Once a support or resistance level is detected, it is displayed on the chart either as a horizontal line, a shaded box, or both, depending on your display settings. You can fully customize the visual appearance including color, transparency, and line thickness. Levels are automatically extended into the future, and optionally into the past, to give better context.
Each level is monitored for breakout behavior. If price breaks through a level, it can change its role — a former resistance may become support, and vice versa. After a certain number of breakouts (which you define), the level is considered invalid and is automatically removed from the chart. This helps to maintain a clean visual layout and ensures only relevant levels are shown.
The indicator supports multi-timeframe analysis, allowing you to overlay higher-timeframe structure directly on your lower-timeframe trading chart. It is also compatible with Heikin Ashi candles internally for reference, without affecting your main chart type.
Support and Resistance MTF is ideal for traders looking to align intraday setups with higher-timeframe zones, manage risk around structural levels, or simply highlight market turning points in a clear and automated way. Built with Pine Script v5 and optimized for performance, it is both powerful and lightweight.
⚙️ Input Parameters – Description
[Time-Frame
Defines the higher timeframe used for detecting support and resistance levels. For example, you can set this to 1h, 4h, or D to visualize significant levels from a broader market perspective on a lower-timeframe chart.
Left / Right (Pivot Left / Pivot Right)
These parameters control the sensitivity of the pivot detection. A pivot high/low is confirmed if it is higher/lower than the defined number of candles to its left and right. Higher values reduce noise but may miss smaller turning points.
Extend Left
When enabled, the drawn levels (lines and/or boxes) are extended to the left side of the chart, allowing you to see the historical alignment of these levels.
Max Breaks Before Delete
Defines how many times a level can be broken by price before it is removed from the chart. This helps to avoid clutter from outdated or invalidated levels and keeps your chart relevant to current price action.
Draw Lines Only
If enabled, the indicator will draw only horizontal lines for support and resistance zones, omitting the colored background boxes. Useful for a cleaner chart appearance.
Line Width Broken Level
Sets the thickness of the support/resistance lines. Thicker lines can emphasize key levels, especially after a breakout.
Transparency Boxes
Controls the transparency (0–100) of the background boxes representing the zones. A higher value makes the boxes more transparent, lower values make them more opaque.
Transparency Lines
Controls the transparency (0–100) of the horizontal support and resistance lines. This allows for visual fine-tuning based on chart background and personal preference.
Support (Color, Group: Display)
Lets you choose the color used for support zones and lines. By default, it's green, but you can change it to fit your theme or visual preference.
Resistance (Color, Group: Display)
Defines the color for resistance zones and lines. The default is red, but it can be customized freely.
OA - Sigma BandsDescription:
The OA - Sigma Bands indicator is a fully adaptive, volatility-sensitive dynamic band system designed to detect price expansion and potential breakouts. Unlike traditional fixed-width Bollinger Bands, OA - Sigma Bands adjust their boundaries based on a combination of standard deviation (σ) and Average Daily Range (ADR), making them more responsive to real market behavior and shifts in volatility.
Key Concepts & Logic
This tool constructs three distinct band regions:
Sigma Bands (±σ):
Calculated using the standard deviation of the closing price over a user-defined lookback period. This acts as the core volatility filter to identify statistically significant price deviations.
ADR Zones (±ADR):
These zones provide an additional layer based on the percentage average of daily price ranges over the last 20 bars. They help visualize intraday or short-term expected volatility.
Dynamic Adjustment Logic:
When price breaks outside the upper/lower sigma or ADR boundaries for a defined number of bars (user input), the system recalibrates. This ensures that the bands evolve with volatility and don’t remain outdated in trending markets.
Inputs & Customization
Sigma Multiplier: Set how wide the sigma bands should be (default: 1.5).
Lookback Period: Controls how many bars are used to calculate the standard deviation (default: 200).
Break Confirmation Bars: Determines how many candles must close beyond a boundary to trigger band recalibration.
ADR Period: Internally fixed at 20 bars for stable short-term volatility measurement.
Full Color Customization: Customize the band colors and fill transparency to suit your chart style.
Benefits & Use Cases
Breakout Trading: Detect when price exits statistically significant ranges, confirming trend expansion.
Mean Reversion: Use the outer bands as potential reversion zones in sideways or low-volatility markets.
Volatility Awareness: Visually identify when price is compressed or expanding.
Dynamic Structure: The auto-updating nature makes it more reliable than static historical zones.
Overlay-Ready: Designed to sit directly on price charts with minimal clutter.
Disclaimer
This script is intended for educational and informational purposes only. It does not constitute investment advice, financial guidance, or a recommendation to buy or sell any security. Always perform your own research and apply proper risk management before making trading decisions.
If you enjoy this script or find it useful, feel free to give it or leave a comment!
Strategy Builder With IndicatorsThis strategy script is designed for traders who enjoy building systems using multiple indicators.
Please note: This script does not include any built-in indicators. Instead, it works by referencing the plot outputs of the indicators you’ve already added to your chart.
For example, if you add a MACD and an ATR indicator to your chart, you can assign their plot values as inputs in the settings panel of this strategy.
• MACD as a trigger
• ATR as a filter
How Filters Work
Filters check whether certain conditions are met before a trade can be opened. For instance, if you set a filter like ATR > 30, then no trade will be executed unless that condition is true — even if the trigger fires.
All filters are linked, meaning every active filter must be satisfied for a trade to occur.
How Triggers Work
Triggers are what actually fire a trade signal — such as a moving average crossover or RSI breaking above a specific level. Unlike filters, triggers are independent. Only one active trigger needs to be true for the trade to execute.
Thanks to its modular structure, this strategy can be used with any indicator of your choice.
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Risk Management Features
In the settings, you’ll find flexible options for:
• Stop Loss (SL)
• Trailing Stop Loss (TSL)
• Multi Take-Profit (TP)
These features enhance trade safety and let you tailor your risk management.
SL types available:
• Tick-based SL
• Percent-based SL
• ATR-based SL
Once you select your preferred SL type, you can fine-tune its distance using the offset field.
Trailing SL allows your stop to follow price as it moves in your favor — helping to lock in profits.
Multi-TP lets you take profits at two different levels, helping you secure gains while leaving room for extended moves.
Breakeven option is also available to automatically move your SL to entry after reaching a profit threshold.
⸻
How to Build a Solid Strategy
Let’s break down a good setup into three key components:
1. Trend Filter
Avoid trading against the trend — that’s like swimming against the current.
Use a filter like:
• Supertrend
• Momentum indicators
• Candlestick bias, etc.
Example: In this case, I used Supertrend and filtered for trades only if the price is above the uptrend line.
2. Trigger Condition
Once we confirm the trend is on our side, we need a trigger to execute at the right moment. This can be:
• RSI cross
• Candlestick patterns
• Trendline breaks
• Moving average crossovers, etc.
Example: I used RSI crossing above 50 as the entry trigger.
3. Risk Management
Even in the right trend at the right time — anything can happen. That’s why you should always define Stop Loss and Take Profit levels.
⸻
And there you have it! Your strategy is ready to backtest, refine, and deploy with alerts for live trading.
Questions or suggestions? Feel free to reach out
SMA50 ATR%SMA50 ATR% Zones Indicator
Overview:
The "SMA50 ATR%" indicator is designed to provide dynamic zones above and below a Simple Moving Average (SMA) based on multiples of the Average True Range (ATR). These zones can help traders identify potential areas of interest for entries, profit-taking, and stop-loss placement by visualizing how far the price has deviated from its medium-term mean (SMA) relative to its recent volatility (ATR).
Key Features:
Central SMA: Plots a customizable Simple Moving Average (default 50-period) as the baseline.
ATR-Based Zones: Calculates and displays distinct zones by adding or subtracting multiples of the ATR (default 10-period) from the SMA.
Color-Coded Visuals: Each zone type is clearly differentiated by color and shading intensity, providing an intuitive visual guide.
Current Zone Label: Displays the specific ATR multiple zone the current price is trading in, offering quick insight into the market's current position relative to the zones.
Zone Breakdown:
The indicator plots the following zones:
Entry Zones (Green Shades):
+1x ATR to +2x ATR above SMA
+2x ATR to +3x ATR above SMA
+3x ATR to +4x ATR above SMA
The green shades become progressively lighter as they move further from the SMA, with the zone closest to the SMA being the darkest green.
Hold Zones (Yellow Shades):
+4x ATR to +5x ATR above SMA (Darker Yellow)
+5x ATR to +6x ATR above SMA (Lighter Yellow)
Sell Zones (Red Shades):
+6x ATR to +7x ATR above SMA
+7x ATR to +8x ATR above SMA
+8x ATR to +9x ATR above SMA
+9x ATR to +10x ATR above SMA
+10x ATR to +11x ATR above SMA
The red shades become progressively darker as they move further from the +6x ATR level, with the +10x to +11x ATR zone being the darkest red.
Stop Loss Zones (Red Shades):
-1x ATR below SMA (Lighter Red)
-1x ATR to -2x ATR below SMA (Darker Red)
How to Use:
Potential Entry Areas: The green "Entry Zones" might indicate areas where the price has pulled back towards the SMA but is still showing strength, or areas where a breakout above the SMA is gaining momentum relative to volatility.
Potential Overbought/Hold Areas: The yellow "Hold Zones" could suggest that the price is becoming extended from its mean, warranting caution or a "hold" approach for existing positions.
Potential Profit-Taking/Sell Areas: The red "Sell Zones" might highlight significantly overbought conditions where the price has moved multiple ATRs above the SMA, potentially signaling areas for profit-taking or considering short entries.
Potential Stop-Loss Areas: The red "Stop Loss Zones" below the SMA can help define areas where a breakdown below the moving average, considering volatility, might invalidate a bullish bias.
Customization:
SMA Length: Adjust the period for the Simple Moving Average (Default: 50).
ATR Length: Adjust the period for the Average True Range calculation (Default: 10).
Show Current Zone Label: Toggle the visibility of the on-screen label that displays the current price's ATR zone.
SMA Line Width: Customize the thickness of the SMA line.
Label Position & Size: Control the placement and text size of the current zone label for optimal chart readability.
Disclaimer:
This indicator is a tool for technical analysis and should not be considered as financial advice. Always use risk management and combine with other analysis methods before making trading decisions.
Navier-Cauchy Market Elasticity [PhenLabs]📊 Navier-Cauchy Market Elasticity
Version: PineScript™ v6
📌 Description
The Navier-Cauchy Market Elasticity (NCME) indicator takes a new step into technical analysis by applying materials science principles to financial markets. Similar to last weeks release utilizing Navier-Stokes dynamics equation this indicator focuses on the elastic interaction of virtual “solids”. Based on elasticity theory used in engineering, NCME treats price movements as material deformations, calculating market stress and strain using proven physics formulas. This unique approach reveals hidden market dynamics invisible to traditional indicators.
By implementing Lamé parameters and Young’s modulus calculations, NCME identifies critical stress points where markets exhibit extreme tension or compression. These zones often precede significant price movements, providing traders with advanced warning of potential reversals or breakouts.
🚀 Points of Innovation
• First indicator to apply Navier-Cauchy elasticity equations to market analysis
• Dynamic stress tensor calculations adapted for one-dimensional price movements
• Real-time Poisson ratio adjustments for market-specific elasticity modeling
• Gradient-based coloring system that visualizes stress intensity variations
• Advanced display modes with customizable visual layers for professional analysis
• Physics-based volatility normalization using Young’s modulus principles
🔧 Core Components
• Elasticity Engine: Calculates market elasticity using volatility-adjusted Young’s modulus
• Stress Tensor System: Computes normal stress values using Lamé parameters (λ and μ)
• Strain Measurement: Tracks price displacement relative to historical movement patterns
• Dynamic Bands: Statistical deviation bands that adapt to market elasticity changes
🔥 Key Features
• Four Display Modes: Choose between Histogram, Line, Both, or Advanced visualization
• Five Color Schemes: Modern, Classic, Neon, Ocean, and Fire themes with gradient support
• Background Stress Zones: Five distinct zones showing market stress levels visually
• Customizable Smoothing: Adjustable period for noise reduction without signal lag
• Extreme Value Detection: Automatic marking of critical stress points with visual alerts
• Advanced Mode Options: Glow effects, momentum ribbon, and extreme dots toggles
🎨 Visualization
• Stress Line: Primary indicator showing real-time market stress with gradient coloring
• Histogram Bars: Normalized stress values with dynamic opacity based on magnitude
• Reference Bands: Primary and secondary deviation bands for context
• Background Zones: Color-coded regions indicating stress intensity levels
• Signal Dots: Markers appearing at extreme stress points for easy identification
📖 Usage Guidelines
Display Settings
• Display Style
○ Default: Advanced
○ Options: Histogram, Line, Both, Advanced
○ Description: Controls visual presentation mode. Advanced offers the most comprehensive view with multiple layers
• Smoothing Period
○ Default: 3
○ Range: 1-50
○ Description: Moving average periods for noise reduction. Higher values create smoother signals but may introduce lag
Elasticity Parameters
• Displacement Length
○ Default: 14
○ Range: 1-100
○ Description: Lookback period for strain calculation. Shorter periods detect rapid stress changes
• Elasticity Length
○ Default: 30
○ Range: 1-200
○ Description: Period for volatility-based elasticity calculation. Longer periods provide more stable readings
• Poisson Ratio
○ Default: 0.3
○ Range: 0-0.5
○ Description: Theoretical elasticity ratio. 0.3 works well for most markets; adjust for specific asset classes
✅ Best Use Cases
• Identifying market tension before major breakouts
• Detecting compression zones during accumulation phases
• Confirming trend strength through stress persistence
• Timing reversals at extreme stress levels
• Multi-timeframe stress analysis for comprehensive market view
⚠️ Limitations
• Requires sufficient price history for accurate elasticity calculations
• May produce false signals during unprecedented market events
• Works best in liquid markets with consistent volume
• Not suitable as a standalone trading system
💡 What Makes This Unique
• Physics-Based Foundation: First indicator to properly implement elasticity theory
• Academic Rigor: Based on proven Navier-Cauchy equations from materials science
• Visual Innovation: Multiple display modes with professional-grade aesthetics
• Adaptive Technology: Self-adjusting parameters based on market conditions
🔬 How It Works
1. Strain Calculation:
• Measures price displacement over specified period
• Normalizes displacement relative to price level
2. Elasticity Determination:
• Calculates Young’s modulus using inverse volatility
• Updates Lamé parameters based on Poisson ratio
3. Stress Computation:
• Applies elasticity theory formula: σ = (λ + 2μ) × ε
• Scales result for visual clarity
• Applies smoothing to reduce noise
💡 Note: NCME represents a breakthrough in applying physics principles to market analysis. While based on proven scientific formulas, remember that markets are complex systems influenced by human psychology and external factors. Use NCME as part of a comprehensive trading strategy with proper risk management.
Institutional Volume Footprint ProOVERVIEW
The Institutional Volume Footprint Pro is a comprehensive volume analysis indicator designed to identify institutional trading activity and significant volume patterns. Based on the proven Pocket Pivot Volume methodology by Chris Kacher and Gil Morales, this indicator has been enhanced with multiple additional volume analysis techniques to provide traders with a complete picture of smart money movements.
KEY FEATURES
1. Pocket Pivot Volume (PPV) Detection
- Identifies bullish volume patterns where current volume exceeds the highest down-day volume of the past 10 days
- Blue volume bars with "PPV" labels mark potential institutional accumulation
- Customizable lookback period (5-20 days)
2. Pivot Negative Volume (PNV) Detection
- Spots bearish volume patterns where selling volume exceeds recent up-day volumes
- Orange bars with "PNV" labels indicate potential institutional distribution
- Early warning system for trend reversals
3. Advanced Institutional Patterns
- Accumulation Detection (Aqua): High volume with narrow price range - classic stealth accumulation
- Churning/Distribution (Yellow): Heavy volume with minimal price progress - potential topping pattern
- Volume Dry-up (Purple): Extremely low volume periods that often precede significant moves
- Volume Climax (Fuchsia): Extreme volume spikes signaling potential exhaustion
4. Real-time Analytics Dashboard
- Relative Volume: Current volume compared to 10-day average
- Volume vs MA: Multiple of current volume to selected moving average
- Price Range Analysis: Narrow/Normal/Wide range classification
5. Accumulation/Distribution Trend
- Background coloring shows overall money flow direction
- Green tint: Net accumulation phase
- Red tint: Net distribution phase
HOW TO USE
Entry Signals:
- PPV (Blue): Consider long positions when price breaks above resistance with PPV confirmation
- Accumulation (Aqua): Watch for breakouts following multiple accumulation days
- Volume Dry-up (Purple): Prepare for potential explosive moves
Exit/Warning Signals:
- PNV (Orange): Consider taking profits or tightening stops
- Churning (Yellow): Distribution may be occurring despite stable prices
- Volume Climax (Fuchsia): Potential reversal point - extreme caution advised
CUSTOMIZATION OPTIONS
Analysis Parameters:
- PPV Lookback Period (5-20 days)
- Volume MA Length & Type (SMA/EMA/WMA)
- Relative Volume Threshold
- Climax Volume Multiplier
Visual Controls:
- Toggle Info Table display
- Enable/disable individual label types (PPV, PNV, ACC)
- Show/hide volume moving averages
- Control A/D trend background
- Customize threshold lines
BUILT-IN ALERTS
- Pocket Pivot Volume detected
- Pivot Negative Volume detected
- Institutional Accumulation pattern
- Volume Climax warning
- Volume Dry-up alert
PRO TIPS
1. Combine with Price Action: Volume confirms price - look for PPV at breakouts and PNV at breakdowns
2. Multiple Timeframes: Check daily and weekly charts for confluence
3. Relative Volume Matters: Patterns are stronger when relative volume > 1.5x
4. Watch for Divergences: Price up with decreasing volume = weakness
COLOR LEGEND
- Blue: Pocket Pivot Volume (Bullish)
- Orange: Pivot Negative Volume (Bearish)
- Aqua: Institutional Accumulation
- Yellow: Churning/Distribution
- Purple: Volume Dry-up
- Fuchsia: Volume Climax
- Green: Above-average up volume
- Red: Above-average down volume
- Gray: Below-average volume
EDUCATIONAL BACKGROUND
This indicator implements concepts from:
- "Trade Like an O'Neil Disciple" by Gil Morales & Chris Kacher
- William O'Neil's volume analysis principles
- Richard Wyckoff's accumulation/distribution methodology
Happy Trading! May the volume be with you!
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Tight Range Display with Background🌟 Tight Range Transparency Display with Background
What Is This Indicator?
Hey traders! Ever wanted a simple way to spot those quiet, low-volatility moments in the market that often signal a big move is coming? The Tight Range Transparency Display with Background does exactly that! This indicator highlights periods where the price is moving in a tight range—think of it as the calm before the storm. It paints the chart background blue to show these zones, with the shade getting darker the tighter the range becomes. It’s like having a visual cue to say, “Hey, something might be brewing here!”
Why You’ll Love It
Spot Key Moments Easily: The blue background makes it super easy to see when the market is in a tight range, which often happens before breakouts or big trends.
Customizable Settings: You can tweak the range thresholds to match your trading style—whether you’re looking for super tight zones or slightly broader ones.
Visual Clarity: The background gets darker when the range is tighter, giving you a quick sense of how compressed the price action is.
Perfect for Any Market: Works on stocks, forex, crypto, or any chart you trade, across any timeframe.
How to Use It
Add It to Your Chart:
Just copy this script into TradingView’s Pine Editor and hit "Add to Chart." It’ll overlay right on your price chart.
Tweak the Settings:
Open the indicator settings and use the dropdown menus to pick your preferred "Tight Range %" and "Wide Range %." For example, set a Tight Range % of 2.0% to catch smaller ranges, or go higher like 10.0% for broader ones.
You can also adjust the ATR Period (default is 5) to make the indicator more or less sensitive to recent price swings.
Watch for the Blue Background:
When the price enters a tight range, the chart background turns blue. The darker the blue, the tighter the range—meaning a potential breakout could be closer!
Trade Smarter:
Use these tight range zones to prepare for potential breakouts. For example, if you see a dark blue background, it might be a good time to watch for a big price move.
Pair this with other tools like support/resistance levels or volume spikes to confirm your trades.
Who Is This For?
Swing Traders: Perfect for spotting consolidation zones before a big swing.
Breakout Traders: Tight ranges often lead to breakouts—use this to time your entries.
Smart Money Followers: If you’re into smart money concepts, tight ranges can signal accumulation or distribution phases.
Beginners & Pros Alike: It’s easy to use for new traders but powerful enough for seasoned pros.
Real-World Example
Imagine you’re trading a stock on a 1-hour chart. You notice the background turns blue, and it’s getting darker over a few bars. This tells you the price range is tightening—maybe the stock is consolidating after a big move. You check your other indicators, see a volume spike, and spot a breakout above resistance. Boom! You catch the next big trend, all because this indicator helped you focus on the right moment.
Tips for Best Results
Try Different Timeframes: Tight ranges on a 15-minute chart might signal short-term moves, while a daily chart could highlight bigger trends.
Adjust for Your Market: For volatile markets like crypto, you might want a higher Tight Range % (e.g., 10.0%). For calmer markets like forex, try a lower setting (e.g., 2.0%).
Combine with Other Tools: Use this alongside trendlines, moving averages, or volume indicators to confirm your setups.
Why I Made This
I created this indicator because I wanted a simple, visual way to spot those critical low-volatility zones without cluttering my chart. The dynamic background color makes it intuitive to see when the market is “coiling up” for a potential move. I hope it helps you find better trading opportunities just like it does for me!
Let’s Connect
If you find this indicator helpful, I’d love to hear about it! Drop a comment or a rating to let me know how it’s working for you. Got ideas to make it even better? Feel free to message me on TradingView—I’m always open to suggestions.
Published On
Date: May 22, 2025
Happy trading, and may your charts always be in your favor! 🚀
How to Publish on TradingView
Open Pine Editor:
On TradingView, open a chart and go to the Pine Editor tab at the bottom.
Paste the Code:
Copy the script you provided and paste it into the Pine Editor.
Compile:
Click "Add to Chart" to ensure it compiles without errors.
Publish:
Click the "Publish Script" button (paper plane icon) in the Pine Editor.
Select "Publish New Script."
Add the Description:
Title: "Tight Range Transparency Display with Background"
Description: Copy the content above into the description field.
Visibility: Choose "Public" to share with everyone (or "Invite-Only" for restricted access).
Tags: Add tags like "tight range", "breakout", "smart money", "volatility", "swing trading".
Screenshot: Add a screenshot of the indicator on a chart, showing the blue background during a tight range.
Submit:
Click "Publish" to submit. TradingView will review it and make it live if it meets their guidelines.
Additional Notes
Screenshot Tip: Use a chart where the blue background is clearly visible (e.g., during a consolidation period) to make the indicator’s effect stand out.
Engage with Users: After publishing, respond to comments and feedback to build a positive reputation on TradingView.
This content is designed to be approachable and engaging, helping traders understand the value of your indicator and encouraging them to try it out.
Long Wick Detector [LuxAlgo]The Long Wick Detector tool allows traders to identify candle wicks longer than a user-defined volatility threshold. This makes it useful for spotting zones with high supply or demand.
The tool displays mitigated and unmitigated levels and changes the color of the candles based on wick size and level breakouts.
🔶 USAGE
By default, the tool displays long mitigated and unmitigated candle wicks, with a maximum duration for an unmitigated long wick of 1,000 bars. What does all this mean?
🔹 Wick Threshold
Traders can adjust the volatility threshold to identify long wicks, with a higher threshold detecting more significant wicks.
As we can see in the image above, the tool detects more wicks with a smaller threshold compared to a higher one.
🔹 Level %
Traders can choose the percentage of the wick at which the level is located. By default, the level is displayed at the extremes of the wick. This parameter accepts values between 0 and 100.
100: extreme of the wick
50: middle of the wick
0: start of the wick
🔹 Max Duration
This parameter allows traders to specify the number of bars for the levels. The tool will only display mitigated or unmitigated levels up to the specified number of bars.
As shown in the above image, a longer duration allows more room for mitigation, displaying more levels.
🔹 Colored Candles
The tool allows for color customization using two parameters from the settings panel. The chart shows the different outputs.
The setting "Wick-Based Transparency" makes candles with smaller wicks less visible and candles with longer wicks more visible.
On the other hand, "Breakout-Based Color" changes the base color of the candles based on the mitigation of long wicks. When the price breaks above a detected top wick, the bullish color is used. When the price breaks below a detected bottom wick, the bearish color is used.
🔶 SETTINGS
Wick Threshold: The volatility threshold for wick detection. Use a smaller value to detect smaller wicks.
Level %: Placement of the plotted level relative to the wick.
Max Duration: The maximum duration in bars of mitigated wicks.
Mitigated Wicks: Enable or disable mitigated wicks.
🔹 Style
Wick Based Transparency: Make candles with smaller wicks more transparent and candles with longer wicks more solid.
Breakout Based Color: Change the base color based on wick mitigation.
Bullish & Bearish Colors
RTH Session Highs & LowsA Pine Script indicator designed to track and plot the Regular Trading Hours (RTH) session highs and lows on a chart, typically for U.S. equity markets (e.g., S&P 500, Nasdaq, etc.), which operate from 9:30 AM to 4:00 PM Eastern Time.
Session High & Low Lines:
During the RTH session, the indicator draws green and red horizontal lines that represent the highest and lowest price seen so far within that trading session.
These levels help traders identify intraday support (low) and resistance (high) levels.
New High/Low Markers:
Small triangle markers are placed:
Above the bar when a new intraday high is made (green triangle).
Below the bar when a new intraday low is made (red triangle).
This visually flags when momentum may be building or reversing.
Intraday Strategy Support:
Use the session high/low as dynamic support/resistance for scalping or breakout strategies.
For example:
Breakouts above session highs may indicate bullish strength.
Breakdowns below session lows may suggest bearish momentum.
Mean Reversion Tactics:
Prices approaching these lines and then rejecting can be used for mean reversion setups.
Combine with volume or candlestick patterns for confirmation.
Risk Management:
Set stops or targets relative to session highs/lows.
For instance, use session high as a stop-loss level in a short position.
Volatility Gauge:
Tracking how frequently new highs/lows are formed can help assess intraday volatility or range expansion.
Complement with Indicators:
Combine this with our "McGinley Dynamic Channel with Directional Shading" indicator or our "EMA Crossover with Shading" indicator to add context to breakouts or rejections.
Support and Resistance Power Channel [ChartPrime]The Support and Resistance Power Channel indicator helps traders visualize key support and resistance zones, along with buy and sell power within those zones. By identifying the highest and lowest prices within a defined range, this indicator provides insight into potential price reversals and market strength. It calculates the strength of buy and sell pressure within the zones and includes additional features like midline values and delayed signals to reduce false breakouts.
⯁ KEY FEATURES AND HOW TO USE
⯌ Support and Resistance Zones :
This indicator identifies dynamic support (lower zone) and resistance (upper zone) levels, allowing traders to easily visualize key price levels. These zones are customizable with settings for the length of the channel and how far the zones extend into the future. The zones can be used to predict areas of potential price reversal or consolidation.
⯌ Buy and Sell Power :
Within the upper resistance zone, the indicator calculates Sell Power based on the number of bearish candles, while the lower support zone calculates Buy Power based on bullish candles. This feature helps traders understand the strength of buying or selling activity within each zone.
Example of buy and sell power tracking:
⯌ Highest, Lowest, and Mid Price Levels :
The indicator marks the highest and lowest price levels within the channel with an "X," and displays these values at the end of the channel. Additionally, the midline (average of the high and low) is plotted with a dotted line, showing a key area that the price often retests during trends.
⯌ Delayed Signal Markers :
To prevent false breakouts, the indicator includes a 2-bar delay for signals. These signals are plotted when the price crosses above or below the resistance or support zones, confirming potential reversals or breakouts. Arrows or diamonds are used to mark these signals on the chart.
Example of delayed breakout signals on the chart:
⯌ Extend Zones into the Future :
In the settings, traders can extend the support and resistance zones further into the future, allowing for ongoing analysis even after the initial levels have been identified. This feature can help with forward-looking trade planning.
⯁ USER INPUTS
Length : Defines the number of bars used to calculate the support and resistance zones.
Extend : Sets how far the support and resistance zones should be extended into the future.
Top and Bottom Colors : Allows customization of the colors for the support and resistance zones.
⯁ CONCLUSION
The Support and Resistance Power Channel indicator provides a powerful and visually intuitive way to track key market levels, buy and sell pressure, and potential reversals. With its real-time zone plotting and the calculation of power within each zone, it offers traders essential insights for making more informed trading decisions.
Anti-Fade GuardThis indicator helps you avoid the costly mistake of fading strong trends by identifying when the market is in a high-conviction directional move — and when it’s not.
Inspired by real trading behaviors and momentum confirmation principles, Anti-Fade Guard provides a clear, visual decision tool for intraday and scalping traders.
✅ How It Works
It uses a multi-factor scoring model that analyzes:
• 📈 EMA Trend Bias — Direction of price vs EMA and EMA slope
• 🔁 2-Bar Trend Structure — Detects consistent higher highs/lows
• 🚨 Breakout Confirmation — Confirms clean moves through previous bar extremes
• 🔊 Volume Strength — Detects conviction based on volume above 20-bar average
• 📏 Body-to-Range Strength — Filters out candles with indecision (e.g. dojis)
Each signal contributes to a bullish or bearish score, and a trend is only considered valid when 2 or more signals agree.
🟩🟥 Visual Output
A real-time summary box in the bottom-right corner shows:
• Trend Status: 📈 Bullish / 📉 Bearish / 🟩 Neutral
• Signal Breakdown: EMA, Price Structure, Breakout, Volume, Candle Strength
• A Heatmap-style Trend Score: color-coded for conviction
This makes it easy to filter setups, stay on the right side of the market, and avoid fighting the trend.
Smart Money Signal Engine (Smart Liquidity Zone - Anchored)🧭 Smart Liquidity Zone Indicator – Simple Guide
✅ What This Does
This tool helps you spot:
1. Smart Money Buy Zones (green box)
2. Fake Breakouts (trap alerts)
3. Real Breakouts (momentum alerts)
⸻
1. 🟩 Liquidity Zone (Green Box)
What it means:
Where big players (smart money) are likely interested in buying.
What you do:
• If price enters the box and holds → consider buying
• If price drops through fast → wait or look for short setups
⸻
2. 🔴 Trap Alert (Smart Money Trap)
What it means:
Price goes up fast with volume…
But no real buying power underneath = likely fakeout
On chart:
You’ll see a red label that says “Trap”
What you do:
• ❌ Don’t chase the pump
• ✅ Wait for reversal or short entry
⸻
3. 🟢 Breakout Alert
What it means:
Price breaks above a key level with strong volume
Smart money is likely behind the move
On chart:
You’ll see a green label that says “Breakout”
What you do:
• ✅ You can enter a momentum trade
• ✅ Place stop below previous structure
⸻
🔔 How to Turn on Alerts
Go to:
• TradingView > Alerts > Condition
• Choose:
• Smart Money Trap Alert
• Breakout Confirmed Alert
This way, TradingView notifies you instantly when:
• A fakeout is happening
• A real breakout begins
(OFPI) Order Flow Polarity Index - Momentum Gauge (DAFE) (OFPI) Order Flow Polarity Index - Momentum Gauge: Decode Market Aggression
The (OFPI) Gauge Bar is your front-row seat to the battle between buyers and sellers. This isn’t just another indicator—it’s a momentum tracker that reveals market aggression through a sleek, centered gauge bar and a smart dashboard. Built for traders who want clarity without clutter, it’s your edge for spotting who’s driving price, bar by bar.
What Makes It Unique?
Order Flow Pressure Index (OFPI): Splits volume into buy vs. sell pressure based on candle body position. It’s not just volume—it’s intent, showing who’s got the upper hand.
T3 Smoothing Magic: Uses a Tilson T3 moving average to keep signals smooth yet responsive. No laggy SMA nonsense here.
Centered Gauge Bar: A 20-segment bar splits bullish (lime) and bearish (red) momentum around a neutral center. Empty segments scream indecision—it’s like a visual heartbeat of the market.
Momentum Shift Alerts: Catches reversals with “Momentum Shift” flags when the OFPI crests, so you’re not caught off guard.
Clean Dashboard: A compact, bottom-left table shows momentum status, the gauge bar, and the OFPI value. Color-coded, transparent, and no chart clutter.
Inputs & Customization
Lookback Length (default 10): Set the window for pressure calculations. Short for scalps, long for trends.
T3 Smoothing Length (default 5): Tune the smoothness. Tight for fast markets, relaxed for chill ones.
T3 Volume Factor (default 0.7): Crank it up for snappy signals or down for silky trends.
Toggle the dashboard for minimalist setups or mobile trading.
How to Use It
Bullish Momentum (Lime, Right-Filled): Buyers are flexing. Look for breakouts or trend continuations. Pair with support levels.
Bearish Momentum (Red, Left-Filled): Sellers are in charge. Scout for breakdowns or shorts. Check resistance zones.
Neutral (Orange, Near Center): Market’s chilling. Avoid big bets—wait for a breakout or play the range.
Momentum Shift: A reversal might be brewing. Confirm with price action before jumping in.
Not a Solo Act: Combine with your strategy—trendlines, RSI, whatever. It’s a momentum lens, not a buy/sell bot.
Why Use the OFPI Gauge?
See the Fight: Most tools just count volume. OFPI shows who’s winning with a visual that slaps.
Works Anywhere: Crypto, stocks, forex, any timeframe. Tune it to your style.
Clean & Pro: No chart spam, just a sharp gauge and a dashboard that delivers.
Unique Edge: No other indicator blends body-based pressure, T3 smoothing, and a centered gauge like this.
The OFPI Gauge catches the market’s pulse so you can trade with confidence. It’s not about predicting the future—it’s about knowing who’s in control right now.
For educational purposes only. Not financial advice. Always use proper risk management.
Use with discipline. Trade your edge.
— Dskyz , for DAFE Trading Systems
Minervini Trend Template (EMA)📄 Description:
This script is inspired by Mark Minervini’s SEPA (Specific Entry Point Analysis) strategy and adapts his famous Trend Template using Exponential Moving Averages (EMAs). It helps traders visually identify technically strong stocks that are in ideal buy conditions based on Minervini's rules.
📈 Strategy Logic:
This script scans for momentum breakouts by filtering stocks with the following characteristics:
✅ Buy Criteria (All Conditions Must Be Met):
Price above 50-day EMA
Price above 150-day EMA
Price above 200-day EMA
50-day EMA above 150-day EMA
150-day EMA above 200-day EMA
200-day EMA trending upward (greater than it was 20 days ago)
Price within 25% of its 52-week high
Price at least 30% above its 52-week low
If all 8 conditions are satisfied, the script triggers a SEPA Setup Signal. This is visually indicated by:
✅ A green background on the chart
✅ A label saying “SEPA Setup” under the bar
🛒 When to Buy:
Wait for the stock to break out above a recent base or consolidation pattern (like a cup-with-handle or flat base) on strong volume.
The ideal entry is within 5% of the breakout point.
Confirm that the SEPA conditions are met on the breakout day.
📉 When to Sell:
Place a stop-loss 5–8% below your entry price.
Exit if the breakout fails and price falls back below the pivot or the 50-day EMA.
Take partial profits after a 20–25% gain, and move your stop-loss up to breakeven or trail it using moving averages like the 21 or 50 EMA.
Exit fully if price closes below the 50-day or 150-day EMA on volume.
🧠 Why EMAs?
EMAs react faster to recent price action than SMAs, helping you catch earlier signals in fast-moving markets. This makes it especially useful for growth and momentum traders following Minervini’s high-performance approach.
📊 How to Use:
Apply the script to any stock chart (daily timeframe recommended).
Look for a green background + SEPA Setup label.
Combine with price/volume analysis, base patterns, and market context to time your entries.
🚨 Optional Alerts:
You can set an alert on the condition minerviniPass == true to notify you when a SEPA-compliant setup appears.
📚 This tool is meant for educational and research purposes. Always validate with your own due diligence and consult your risk plan before making any trades.
Enhanced Volume Trend Indicator with BB SqueezeEnhanced Volume Trend Indicator with BB Squeeze: Comprehensive Explanation
The visualization system allows traders to quickly scan multiple securities to identify high-probability setups without detailed analysis of each chart. The progression from squeeze to breakout, supported by volume trend confirmation, offers a systematic approach to identifying trading opportunities.
The script combines multiple technical analysis approaches into a comprehensive dashboard that helps traders make informed decisions by identifying high-probability setups while filtering out noise through its sophisticated confirmation requirements. It combines multiple technical analysis approaches into an integrated visual system that helps traders identify potential trading opportunities while filtering out false signals.
Core Features
1. Volume Analysis Dashboard
The indicator displays various volume-related metrics in customizable tables:
AVOL (After Hours + Pre-Market Volume): Shows extended hours volume as a percentage of the 21-day average volume with color coding for buying/selling pressure. Green indicates buying pressure and red indicates selling pressure.
Volume Metrics: Includes regular volume (VOL), dollar volume ($VOL), relative volume compared to 21-day average (RVOL), and relative volume compared to 90-day average (RVOL90D).
Pre-Market Data: Optional display of pre-market volume (PVOL), pre-market dollar volume (P$VOL), pre-market relative volume (PRVOL), and pre-market price change percentage (PCHG%).
2. Enhanced Volume Trend (VTR) Analysis
The Volume Trend indicator uses adaptive analysis to evaluate buying and selling pressure, combining multiple factors:
MACD (Moving Average Convergence Divergence) components
Volume-to-SMA (Simple Moving Average) ratio
Price direction and market conditions
Volume change rates and momentum
EMA (Exponential Moving Average) alignment and crossovers
Volatility filtering
VTR Visual Indicators
The VTR score ranges from 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions. This is visually represented by colored circles:
"●" (Filled Circle):
Green: Strong bullish trend (VTR ≥ 80)
Red: Strong bearish trend (VTR ≤ 20)
"◯" (Hollow Circle):
Green: Moderate bullish trend (VTR 65-79)
Red: Moderate bearish trend (VTR 21-35)
"·" (Small Dot):
Green: Weak bullish trend (VTR 55-64)
Red: Weak bearish trend (VTR 36-45)
"○" (Medium Hollow Circle): Neutral conditions (VTR 46-54), shown in gray
In "Both" display mode, the VTR shows both the numerical score (0-100) alongside the appropriate circle symbol.
Enhanced VTR Settings
The Enhanced Volume Trend component offers several advanced customization options:
Adaptive Volume Analysis (volTrendAdaptive):
When enabled, dynamically adjusts volume thresholds based on recent market volatility
Higher volatility periods require proportionally higher volume to generate significant signals
Helps prevent false signals during highly volatile markets
Keep enabled for most trading conditions, especially in volatile markets
Speed of Change Weight (volTrendSpeedWeight, range 0-1):
Controls emphasis on volume acceleration/deceleration rather than absolute levels
Higher values (0.7-1.0): More responsive to new volume trends, better for momentum trading
Lower values (0.2-0.5): Less responsive, better for trend following
Helps identify early volume trends before they fully develop
Momentum Period (volTrendMomentumPeriod, range 2-10):
Defines lookback period for volume change rate calculations
Lower values (2-3): More responsive to recent changes, better for short timeframes
Higher values (7-10): Smoother, better for daily/weekly charts
Directly affects how quickly the indicator responds to new volume patterns
Volatility Filter (volTrendVolatilityFilter):
Adjusts significance of volume by factoring in current price volatility
High volume during high volatility receives less weight
High volume during low volatility receives more weight
Helps distinguish between genuine volume-driven moves and volatility-driven moves
EMA Alignment Weight (volTrendEmaWeight, range 0-1):
Controls importance of EMA alignments in final VTR calculation
Analyzes multiple EMA relationships (5, 10, 21 period)
Higher values (0.7-1.0): Greater emphasis on trend structure
Lower values (0.2-0.5): More focus on pure volume patterns
Display Mode (volTrendDisplayMode):
"Value": Shows only numerical score (0-100)
"Strength": Shows only symbolic representation
"Both": Shows numerical score and symbol together
3. Bollinger Band Squeeze Detection (SQZ)
The BB Squeeze indicator identifies periods of low volatility when Bollinger Bands contract inside Keltner Channels, often preceding significant price movements.
SQZ Visual Indicators
"●" (Filled Circle): Strong squeeze - high probability setup for an impending breakout
Green: Strong squeeze with bullish bias (likely upward breakout)
Red: Strong squeeze with bearish bias (likely downward breakout)
Orange: Strong squeeze with unclear direction
"◯" (Hollow Circle): Moderate squeeze - medium probability setup
Green: With bullish EMA alignment
Red: With bearish EMA alignment
Orange: Without clear directional bias
"-" (Dash): Gray dash indicates no squeeze condition (normal volatility)
The script identifies squeeze conditions through multiple methods:
Bollinger Bands contracting inside Keltner Channels
BB width falling to bottom 20% of recent range (BB width percentile)
Very narrow Keltner Channel (less than 5% of basis price)
Tracking squeeze duration in consecutive bars
Different squeeze strengths are detected:
Strong Squeeze: BB inside KC with tight BB width and narrow KC
Moderate Squeeze: BB inside KC with either tight BB width or narrow KC
No Squeeze: Normal market conditions
4. Breakout Detection System
The script includes two breakout indicators working in sequence:
4.1 Pre-Breakout (PBK) Indicator
Detects potential upcoming breakouts by analyzing multiple factors:
Squeeze conditions lasting 2-3 bars or more
Significant price ranges
Strong volume confirmation
EMA/MACD crossovers
Consistent price direction
PBK Visual Indicators
"●" (Filled Circle): Detected pre-breakout condition
Green: Likely upward breakout (bullish)
Red: Likely downward breakout (bearish)
Orange: Direction not yet clear, but breakout likely
"-" (Dash): Gray dash indicates no pre-breakout condition
The PBK uses sophisticated conditions to reduce false signals including minimum squeeze length, significant price movement, and technical confirmations.
4.2 Breakout (BK) Indicator
Confirms actual breakouts in progress by identifying:
End of squeeze or strong expansion of Bollinger Bands
Volume expansion
Price moving outside Bollinger Bands
EMA crossovers with volume confirmation
MACD crossovers with significant price range
BK Visual Indicators
"●" (Filled Circle): Confirmed breakout in progress
Green: Upward breakout (bullish)
Red: Downward breakout (bearish)
Orange: Unusual breakout pattern without clear direction
"◆" (Diamond): Special breakout conditions (meets some but not all criteria)
"-" (Dash): Gray dash indicates no breakout detected
The BK indicator uses advanced filters for confirmation:
Requires consecutive breakout signals to reduce false positives
Strong volume confirmation requirements (40% above average)
Significant price movement thresholds
Consistency checks between price action and indicators
5. Market Metrics and Analysis
Price Change Percentage (CHG%)
Displays the current percentage change relative to the previous day's close, color-coded green for positive changes and red for negative changes.
Average Daily Range (ADR%)
Calculates the average daily percentage range over a specified period (default 20 days), helping traders gauge volatility and set appropriate price targets.
Average True Range (ATR)
Shows the Average True Range value, a volatility indicator developed by J. Welles Wilder that measures market volatility by decomposing the entire range of an asset price for that period.
Relative Strength Index (RSI)
Displays the standard 14-period RSI, a momentum oscillator that measures the speed and change of price movements on a scale from 0 to 100.
6. External Market Indicators
QQQ Change
Shows the percentage change in the Invesco QQQ Trust (tracking the Nasdaq-100 Index), useful for understanding broader tech market trends.
UVIX Change
Displays the percentage change in UVIX, a volatility index, providing insight into market fear and potential hedging activity.
BTC-USD
Shows the current Bitcoin price from Coinbase, useful for traders monitoring crypto correlation with equities.
Market Breadth (BRD)
Calculates the percentage difference between ATHI.US and ATLO.US (high vs. low securities), indicating overall market direction and strength.
7. Session Analysis and Volume Direction
Session Detection
The script accurately identifies different market sessions:
Pre-market: 4:00 AM to 9:30 AM
Regular market: 9:30 AM to 4:00 PM
After-hours: 4:00 PM to 8:00 PM
Closed: Outside trading hours
This detection works on any timeframe through careful calculation of current time in seconds.
Buy/Sell Volume Direction
The script analyzes buying and selling pressure by:
Counting up volume when close > open
Counting down volume when close < open
Tracking accumulated volume within the day
Calculating intraday pressure (up volume minus down volume)
Enhanced AVOL Calculation
The improved AVOL calculation works in all timeframes by:
Estimating typical pre-market and after-hours volume percentages
Combining yesterday's after-hours with today's pre-market volume
Calculating this as a percentage of the 21-day average volume
Determining buying/selling pressure by analyzing after-hours and pre-market price changes
Color-coding results: green for buying pressure, red for selling pressure
This calculation is particularly valuable because it works consistently across any timeframe.
Customization Options
Display Settings
The dashboard has two customizable tables: Volume Table and Metrics Table, with positions selectable as bottom_left or bottom_right.
All metrics can be individually toggled on/off:
Pre-market data (PVOL, P$VOL, PRVOL, PCHG%)
Volume data (AVOL, RVOL Day, RVOL 90D, Volume, SEED_YASHALGO_NSE_BREADTH:VOLUME )
Price metrics (ADR%, ATR, RSI, Price Change%)
Market indicators (QQQ, UVIX, Breadth, BTC-USD)
Analysis indicators (Volume Trend, BB Squeeze, Pre-Breakout, Breakout)
These toggle options allow traders to customize the dashboard to show only the metrics they find most valuable for their trading style.
Table and Text Customization
The dashboard's appearance can be customized:
Table background color via tableBgColor
Text color (White or Black) via textColorOption
The indicator uses smart formatting for volume and price values, automatically adding appropriate suffixes (K, M, B) for readability.
MACD Configuration for VTR
The Volume Trend calculation incorporates MACD with customizable parameters:
Fast Length: Controls the period for the fast EMA (default 3)
Slow Length: Controls the period for the slow EMA (default 9)
Signal Length: Controls the period for the signal line EMA (default 5)
MACD Weight: Controls how much influence MACD has on the volume trend score (default 0.3)
These settings allow traders to fine-tune how momentum is factored into the volume trend analysis.
Bollinger Bands and Keltner Channel Settings
The Bollinger Bands and Keltner Channels used for squeeze detection have preset (hidden) parameters:
BB Length: 20 periods
BB Multiplier: 2.0 standard deviations
Keltner Length: 20 periods
Keltner Multiplier: 1.5 ATR
These settings follow standard practice for squeeze detection while maintaining simplicity in the user interface.
Practical Trading Applications
Complete Trading Strategies
1. Squeeze Breakout Strategy
This strategy combines multiple components of the indicator:
Wait for a strong squeeze (SQZ showing ●)
Look for pre-breakout confirmation (PBK showing ● in green or red)
Enter when breakout is confirmed (BK showing ● in same direction)
Use VTR to confirm volume supports the move (VTR ≥ 65 for bullish or ≤ 35 for bearish)
Set profit targets based on ADR (Average Daily Range)
Exit when VTR begins to weaken or changes direction
2. Volume Divergence Strategy
This strategy focuses on the volume trend relative to price:
Identify when price makes a new high but VTR fails to confirm (divergence)
Look for VTR to show weakening trend (● changing to ◯ or ·)
Prepare for potential reversal when SQZ begins to form
Enter counter-trend position when PBK confirms reversal direction
Use external indicators (QQQ, BTC, Breadth) to confirm broader market support
3. Pre-Market Edge Strategy
This strategy leverages pre-market data:
Monitor AVOL for unusual pre-market activity (significantly above 100%)
Check pre-market price change direction (PCHG%)
Enter position at market open if VTR confirms direction
Use SQZ to determine if volatility is likely to expand
Exit based on RVOL declining or price reaching +/- ADR for the day
Market Context Integration
The indicator provides valuable context for trading decisions:
QQQ change shows tech market direction
BTC price shows crypto market correlation
UVIX change indicates volatility expectations
Breadth measurement shows market internals
This context helps traders avoid fighting the broader market and align trades with overall market direction.
Timeframe Optimization
The indicator is designed to work across different timeframes:
For day trading: Focus on AVOL, VTR, PBK/BK, and use shorter momentum periods
For swing trading: Focus on SQZ duration, VTR strength, and broader market indicators
For position trading: Focus on larger VTR trends and use EMA alignment weight
Advanced Analytical Components
Enhanced Volume Trend Score Calculation
The VTR score calculation is sophisticated, with the base score starting at 50 and adjusting for:
Price direction (up/down)
Volume relative to average (high/normal/low)
Volume acceleration/deceleration
Market conditions (bull/bear)
Additional factors are then applied, including:
MACD influence weighted by strength and direction
Volume change rate influence (speed)
Price/volume divergence effects
EMA alignment scores
Volatility adjustments
Breakout strength factors
Price action confirmations
The final score is clamped between 0-100, with values above 50 indicating bullish conditions and below 50 indicating bearish conditions.
Anti-False Signal Filters
The indicator employs multiple techniques to reduce false signals:
Requiring significant price range (minimum percentage movement)
Demanding strong volume confirmation (significantly above average)
Checking for consistent direction across multiple indicators
Requiring prior bar consistency (consecutive bars moving in same direction)
Counting consecutive signals to filter out noise
These filters help eliminate noise and focus on high-probability setups.
MACD Enhancement and Integration
The indicator enhances standard MACD analysis:
Calculating MACD relative strength compared to recent history
Normalizing MACD slope relative to volatility
Detecting MACD acceleration for stronger signals
Integrating MACD crossovers with other confirmation factors
EMA Analysis System
The indicator uses a comprehensive EMA analysis system:
Calculating multiple EMAs (5, 10, 21 periods)
Detecting golden cross (10 EMA crosses above 21 EMA)
Detecting death cross (10 EMA crosses below 21 EMA)
Assessing price position relative to EMAs
Measuring EMA separation percentage
Recent Enhancements and Evolution
Version 5.2 includes several improvements:
Enhanced AVOL to show buying/selling direction through color coding
Improved VTR with adaptive analysis based on market conditions
AVOL display now works in all timeframes through sophisticated estimation
Removed animal symbols and streamlined code with bright colors for better visibility
Improved anti-false signal filters throughout the system
Optimizing Indicator Settings
For Different Market Types
Range-Bound Markets:
Lower EMA Alignment Weight (0.2-0.4)
Higher Speed of Change Weight (0.8-1.0)
Focus on SQZ and PBK signals for breakout potential
Trending Markets:
Higher EMA Alignment Weight (0.7-1.0)
Moderate Speed of Change Weight (0.4-0.6)
Focus on VTR strength and BK confirmations
Volatile Markets:
Enable Volatility Filter
Enable Adaptive Volume Analysis
Lower Momentum Period (2-3)
Focus on strong volume confirmation (VTR ≥ 80 or ≤ 20)
For Different Asset Classes
Equities:
Standard settings work well
Pay attention to AVOL for gap potential
Monitor QQQ correlation
Futures:
Consider higher Volume/RVOL weight
Reduce MACD weight slightly
Pay close attention to SQZ duration
Crypto:
Higher volatility thresholds may be needed
Monitor BTC price for correlation
Focus on stronger confirmation signals
Integrated Visual System for Trading Decisions
The colored circle indicators create an intuitive visual system for quick market assessment:
Progression Sequence: SQZ (Squeeze) → PBK (Pre-Breakout) → BK (Breakout)
This sequence often occurs in order, with the squeeze leading to pre-breakout conditions, followed by an actual breakout.
VTR (Volume Trend): Provides context about the volume supporting these movements.
Color Coding: Green for bullish conditions, red for bearish conditions, and orange/gray for neutral or undefined conditions.
Order Block Matrix [Alpha Extract]The Order Block Matrix indicator identifies and visualizes key supply and demand zones on your chart, helping traders recognize potential reversal points and high-probability trading setups.
This tool helps traders:
Visualize key order blocks with volume profile histograms showing liquidity distribution.
Identify high-volume price levels where institutional activity occurs.
rank historical order blocks and analyze their strength based on volume.
Receive alerts for potential trading opportunities based on price-block interactions.
🔶 CALCULATION
The indicator processes chart data to identify and analyze order blocks:
Order Block Detection
Inputs:
Price action patterns (consolidation areas followed by breakouts).
Volume data from current and lower timeframes.
User-defined lookback periods and thresholds.
Detection Logic:
Identifies consolidation areas using a dynamic range comparison.
Confirms breakout patterns with percentage threshold validation.
Maps volume distribution across price levels within each order block.
🔶Volume Analysis
Volume Profiling:
Divides each order block into configurable grid segments.
Maps volume distribution across price segments within blocks.
Highlights zones with highest volume concentration.
Strength Assessment:
Calculates total block volume and relative strength metrics.
Compares block volume to historical averages.
Determines probability of reversal based on volume patterns.
isConsolidation(len) =>
high_range = ta.highest(high, len) - ta.lowest(high, len)
low_range = ta.highest(low, len) - ta.lowest(low, len)
avg_range = (high_range + low_range) / 2
current_range = high - low
current_range <= avg_range * (1 + obThreshold)
🔶 DETAILS
Visual Features
Volume Profile Histograms:
Color-coded bars showing volume concentration within order blocks.
Gradient coloring based on relative volume (high volume = brighter colors).
Bull blocks (green/teal) and bear blocks (red) with varying opacity.
Block Visualization:
Dynamic box sizing based on volume concentration.
Optional block borders and background fills.
Volume labels showing total block volume.
Screener Table:
Real-time analysis of order block metrics.
Shows block direction, proximity, retest count, and volume metrics.
Color-coded for quick reference.
Interpretation
High Volume Areas: Zones with institutional interest and potential reversal points.
Block Direction: Bullish blocks typically support price, bearish blocks typically resist price.
Retests: Multiple tests of an order block may strengthen or weaken its influence.
Block Age: Newer blocks often have stronger influence than older ones.
Volume Concentration: Brightest segments within blocks represent the highest volume areas.
🔶 EXAMPLES
The indicator helps identify key trading opportunities:
Bullish Order Blocks
Support Zones: Identify strong support levels where price is likely to bounce.
Breakout Confirmation: Validate breakouts with volume analysis to avoid false moves.
Retest Strategies: Enter trades when price retests a bullish order block with high volume.
Bearish Order Blocks
Resistance Zones: Identify strong resistance levels where price is likely to reverse.
Distribution Areas: Detect zones where smart money is distributing to retail.
Short Opportunities: Find optimal short entry points at high-volume bearish blocks.
Combined Strategies
Order Block Stacking: Multiple aligned blocks create stronger support/resistance zones.
Block Mitigation: When price breaks through a block, it often indicates a strong trend continuation.
Volume Profile Applications: Higher volume segments provide more precise entry and exit points.
🔶 SETTINGS
Customization Options
Order Block Detection:
Consolidation Lookback: Adjust the period for consolidation detection.
Breakout Threshold: Set minimum percentage for breakout confirmation.
Historical Lookback Limit: Control how far back to scan for historical order blocks.
Maximum Order Blocks: Limit the number of visible blocks on the chart.
Visual Style:
Grid Segments: Adjust the number of volume profile segments.
Extend Blocks to Right: Enable/disable extending blocks to current price.
Show Block Borders: Toggle border visibility.
Border Width: Adjust thickness of block borders.
Show Volume Text: Enable/disable volume labels.
Volume Text Position: Control placement of volume labels.
Color Settings:
Bullish High/Low Volume Colors: Customize appearance of bullish blocks.
Bearish High/Low Volume Colors: Customize appearance of bearish blocks.
Border Color: Set color for block outlines.
Background Fill: Adjust color and transparency of block backgrounds.
Volume Text Color: Customize label appearance.
Screener Table:
Show Screener Table: Toggle table visibility.
Table Position: Select positioning on the chart.
Table Size: Adjust display size.
The Order Block Matrix indicator provides traders with powerful insights into market structure, helping to identify key levels where smart money is active and where high-probability trading opportunities may exist.
Bollinger Volatility AnalyzerThe Bollinger Volatility Analyzer (BVA) is a powerful enhancement of the traditional Bollinger Bands indicator, tailored to help traders identify volatility cycles and catch potential breakouts with better precision and timing. It builds upon the foundational concept of Bollinger Bands—using a moving average and standard deviation bands—but adds crucial insights into market contraction and expansion, which can be instrumental in timing entries and exits.
Here's how it works and why it's useful
At its core, the indicator calculates a moving average (called the "basis") and plots two bands—one above and one below—based on a multiple of standard deviation. These bands expand during volatile periods and contract during quiet ones. The width between these bands, normalized as a percentage of the basis, gives us a sense of how compressed or expanded the market currently is. When the band width drops below a user-defined threshold (like 2%), the script highlights this with an orange triangle below the bar. This is the "squeeze" condition, signaling a potential buildup of market energy—a kind of calm before the storm.
What makes this version of Bollinger Bands particularly powerful is that it not only detects squeezes, but also tells you when price breaks out of that squeeze range. If price closes above the upper band after a squeeze, a green "Breakout ↑" label is shown; if it closes below the lower band, a red "Breakout ↓" appears. These breakout labels act as entry signals, suggesting that volatility is returning and a directional move has begun.
This indicator is especially useful in markets that tend to alternate between consolidation and breakout phases, such as forex, crypto, and even individual stocks. Traders who look for early signs of momentum—whether for swing trading, scalping, or position building—can benefit from this tool. During a quiet market phase, the indicator warns you that a move might be coming; when the move starts, it tells you the direction.
In fast-moving markets, BVA helps filter out noise by focusing only on high-probability conditions: quiet consolidation followed by a strong breakout. It’s not a complete system by itself—it works best when paired with volume confirmation or oscillators like RSI—but as a volatility trigger and directional guide, it’s a reliable component of a trading workflow.
