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Volume
Enhanced MFI Divergence with Pivot SignalsEnhanced MFI Divergence with Pivot Signals
This custom Pine Script indicator identifies bullish and bearish divergences between price action and the Money Flow Index (MFI), enhancing the trader's ability to spot potential reversal zones with visual clarity and optional confirmation filters.
📊 Key Features:
🔹 MFI Divergence Detection
The script detects:
Bullish divergence when price forms a lower low but MFI forms a higher low.
Bearish divergence when price forms a higher high but MFI forms a lower high.
🔹 Pivot-Based Logic
To ensure high-confidence signals, the script uses pivot point logic to mark local highs and lows on both price and MFI. This avoids noise and focuses only on meaningful swing points.
🔹 Optional Confirmation Filter
You can enable a filter that checks if MFI is above 50 during bullish divergence (implying buying pressure) and below 50 for bearish divergence (implying selling pressure), adding an extra layer of confirmation.
🔹 Signal Markers
Signals are visually displayed on the chart using colored triangles:
Green triangle up for bullish divergence
Red triangle down for bearish divergence
🔹 Background Color Shading
The background is optionally shaded green or red based on MFI’s relationship to its smoothed WMA, helping you visually interpret trend bias.
🔹 Pivot Point Debugging Tools
Circles and crosses mark pivot points on price and MFI for debugging and visual clarity.
🔹 Alerts Ready
Real-time alerts notify you instantly when a bullish or bearish MFI divergence occurs, allowing for quick decision-making.
⚙️ How It Helps
This indicator is designed to help traders:
Anticipate price reversals by identifying hidden strength or weakness in momentum,
Avoid false breakouts,
Confirm entries or exits based on volume-weighted momentum divergence.
It works especially well when used alongside trend-following tools like moving averages, support/resistance zones, or additional volume indicators.
GER40 BIAS Forecast [ML-Based]🎯 Purpose:
This indicator provides a daily directional bias (LONG / SHORT / FLAT) for the German DAX40 index (GER40) using a statistically optimized scoring model, developed with 6 years of historical data and verified through machine learning analysis.
🧠 How the Score Works (ML-derived):
Each trading day receives a bias score (0–3) for both long and short setups, based on these 3 factors from the daily candle:
Condition Long Score Logic Short Score Logic
1. Candle Direction Close > Open → +1 Close < Open → +1
2. VWAP Slope VWAP > VWAP → +1 VWAP < VWAP → +1
3. Volatility Strength Range > SMA(20) → +1 Close < Yesterday's Low → +1 (Rejection)
➡️ A score of 2 or more triggers a Long or Short Bias for the day.
These scoring rules are derived from a machine learning model trained on 6 years of DAX data, identifying the most predictive features for directional follow-through.
📘 Bias Interpretation:
Score Result Daily Bias Background Color
Long Score ≥ 2 LONG Green
Short Score ≥ 2 SHORT Red
Both < 2 FLAT Gray
📍 Indicator Features:
🎨 Background coloring to visualize daily bias directly on intraday charts
🔢 Optional score labels (e.g. “Long: 2 | Short: 1”) per calendar day
📈 VWAP line plotted for additional intraday context
❌ Entry signals removed – this version focuses solely on forecasting directional bias
💡 Use Case:
Morning planning aid
Filtering for high-probability intraday setups
Combining with session-based entry systems
MACD Crossover with Supertrend FilterThis script is a custom trading indicator that generates **buy and sell signals** based on the combination of:
### 🔹 MACD Crossover:
* **Long (Buy)** signal: when the MACD line crosses above the signal line **below the 0 line**.
* **Short (Sell)** signal: when the MACD line crosses below the signal line **above the 0 line**.
### 🔹 Supertrend Filter:
* **Only buy** when the Supertrend is **bullish (green)**.
* **Only sell** when the Supertrend is **bearish (red)**.
### 🔹 Additional Features:
* Plots green or red arrows on the chart for entries.
* Supertrend line is color-coded.
* Alerts can be enabled for both long and short signals.
✅ This combination filters MACD signals using trend direction for more reliable entries.
Momentum Candle SEKOLAH TRADINGMomentum Candle - Sekolah Trading
This indicator is intended for scalpers because it has a high probability of winning on the 15-minute and 5-minute timeframes.
How to Use:
1. When a large candle with a short wick appears, a signal arrow will be displayed.
2. If the arrow remains visible until the candle closes, you may enter a trade on the next candle.
3. If the signal appears below a bullish candle, you can enter a buy trade following the momentum. If the signal appears above a bearish candle, you can enter a sell trade accordingly.
This indicator was developed by the Research and Development team at Sekolah Trading.
Volume Momentum [BackQuant]Volume Momentum
The Volume Momentum indicator is designed to help traders identify shifts in market momentum based on volume data. By analyzing the relative volume momentum, this indicator provides insights into whether the market is gaining strength (uptrend) or losing momentum (downtrend). The strategy uses a combination of percentile-based volume normalization, weighted moving averages (WMA), and exponential moving averages (EMA) to assess volume trends.
The system focuses on the relationship between price and volume, utilizing normalized volume data to highlight key market changes. This approach allows traders to focus on volume-driven price movements, helping them to capture momentum shifts early.
Key Features
1. Volume Normalization and Percentile Calculation:
The signed volume (positive when the close is higher than the open, negative when the close is lower) is normalized against the rolling average volume. This normalized volume is then subjected to a percentile interpolation, allowing for a robust statistical measure of how the current volume compares to historical data. The percentile level is customizable, with 50 representing the median.
2. Weighted and Smoothed Moving Averages for Trend Detection:
The normalized volume is smoothed using weighted moving averages (WMA) and exponential moving averages (EMA). These smoothing techniques help eliminate noise, providing a clearer view of the underlying momentum. The WMA filters out short-term fluctuations, while the EMA ensures that the most recent data points have a higher weight, making the system more responsive to current market conditions.
3. Trend Reversal Detection:
The indicator detects momentum shifts by evaluating whether the volume momentum crosses above or below zero. A positive volume momentum indicates a potential uptrend, while a negative momentum suggests a possible downtrend. These trend reversals are identified through crossover and crossunder conditions, triggering alerts when significant changes occur.
4. Dynamic Trend Background and Bar Coloring:
The script offers customizable background coloring based on the trend direction. When volume momentum is positive, the background is colored green, indicating a bullish trend. When volume momentum is negative, the background is colored red, signaling a bearish trend. Additionally, the bars themselves can be colored based on the trend, further helping traders quickly visualize market momentum.
5. Alerts for Momentum Shifts:
The system provides real-time alerts for traders to monitor when volume momentum crosses a critical threshold (zero), signaling a trend reversal. The alerts notify traders when the market momentum turns bullish or bearish, assisting them in making timely decisions.
6. Customizable Parameters for Flexible Usage:
Users can fine-tune the behavior of the indicator by adjusting various parameters:
Volume Rolling Mean: The period used to calculate the average volume for normalization.
Percentile Interpolation Length: Defines the range over which the percentile is calculated.
Percentile Level: Determines the percentile threshold (e.g., 50 for the median).
WMA and Smoothing Periods: Control the smoothing and response time of the indicator.
7. Trend Background Visualization and Trend-Based Bar Coloring:
The background fill is shaded according to whether the volume momentum is positive or negative, providing a visual cue to indicate market strength. Additionally, bars can be color-coded to highlight the trend, making it easier to see the trend’s direction without needing to analyze numerical data manually.
8. Note on Mean-Reversion Strategy:
If you take the inverse of the signals, this indicator can be adapted for a mean-reversion strategy. Instead of following the trend, the strategy would involve buying assets that are underperforming and selling assets that are overperforming, based on volume momentum. However, it’s important to note that this approach may not work effectively on highly correlated assets, as their price movements may be too similar, reducing the effectiveness of the mean-reversion strategy.
Final Thoughts
The Volume Momentum indicator offers a comprehensive approach to analyzing volume-based momentum shifts in the market. By using volume normalization, percentile interpolation, and smoothed moving averages, this system helps identify the strength and direction of market trends. Whether used for trend-following or adapted for mean-reversion, this tool provides traders with actionable insights into the market’s volume-driven movements, improving decision-making and portfolio management.
Volume Point of Control with Fib Based Profile🍀Description:
This indicator is a comprehensive volume profile analysis tool designed to identify key price levels based on trading activity within user-defined timeframes. It plots the Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL), along with dynamically calculated Fibonacci levels derived from the developing period's range. It offers extensive customization for both historical and developing levels.
🍀Core Features:
Volume Profiling (POC, VAH, VAL):
Calculates and plots the POC (price level with the highest volume), VAH, and VAL for a selected timeframe (e.g., Daily, Weekly).
The Value Area percentage is configurable. 70% is common on normal volume profiles, but this script allows you to configure multiple % levels via the fib levels. I recommend using 2 versions of this indicator on a chart, one has Value Area at 1 (100% - high and low of lookback) and the second is a specified VA area (i.e. 70%) like in the chart snapshot above. See examples at the bottom.
Historical Levels:
Plots POC, VAH, and VAL from previous completed periods.
Optionally displays only "Unbroken" levels – historical levels that price has not yet revisited, which can act as stronger magnets or resistance/support.
The user can manage the number of historical lines displayed to prevent chart clutter.
Developing Levels:
Shows the POC, VAH, and VAL as they form in real-time during the current, incomplete period. This provides insight into intraday/intra-period value migration.
Dynamic Fibonacci Levels:
Calculates and plots Fibonacci retracement/extension levels based dynamically on the range between the developing POC and the developing VAH/VAL.
Offers 8 configurable % levels above and below POC that can be toggled on/off.
Visual Customization:
Extensive options for colors, line styles, and widths for all plotted levels.
Optional gradient fill for the Value Area that visualizes current price distance from POC - option to invert the colors as well.
Labels for developing levels and Fibonacci levels for easy identification.
🍀Characteristics:
Volume-Driven: Levels are derived from actual trading volume, reflecting areas of high participation and price agreement/disagreement.
Timeframe Specific: The results are entirely dependent on the chosen profile timeframe.
Dynamic & Static Elements: Developing levels and Fibs update live, while historical levels remain fixed once their period closes.
Lagging (Historical) & Potentially Leading: Historical levels are based on the past, but are often respected by future price action. Developing levels show current dynamics.
🍀How to Use It:
Identifying Support & Resistance: Historical and developing POCs, VAHs, and VALs are often key areas where price may react. Unbroken levels are particularly noteworthy.
Market Context & Sentiment: Trading above the POC suggests bullish strength/acceptance of higher prices, while trading below suggests bearishness/acceptance of lower prices.
Entry/Exit Zones: Interactions with these levels (rejections, breakouts, tests) can provide potential entry or exit signals, especially when confirming with other analysis methods.
Dynamic Targets: The Fibonacci levels calculated from the developing POC-VA range offer potential intraday/intra-period price targets or areas of interest.
Understanding Value Migration: Observing the movement of the developing POC/VAH/VAL throughout the period reveals where value is currently being established.
🍀Potential Drawbacks:
Input Sensitivity: The choice of timeframe, Value Area percentage, and volume resolution heavily influences the generated levels. Experimentation is needed for optimal settings per instrument/market. (I've found that Range Charts can provide very accurate volume levels on TV since the time element is removed. This helps to refine the accuracy of price levels with high volume.)
Volume Data Dependency: Requires accurate volume data. May be less reliable on instruments with sparse or questionable volume reporting.
Chart Clutter: Enabling all features simultaneously can make the chart busy. Utilize the line management inputs and toggle features as needed.
Not a Standalone Strategy: This indicator provides context and key levels. It should be used alongside other technical analysis tools and price action reading for robust decision-making.
Developing Level Fluctuation: Developing POC/VA/Fib levels can shift considerably, especially early in a new period, before settling down as more volume accumulates and time passes.
🍀Recommendations/Examples:
I recommend have this indicator on your chart twice, one has the VA set at 1 (100%) and has the fib levels plotted. The second has the VA set to 0.7 (70%) to highlight the defined VA.
Here is an example with 3 on a chart. VA of 100%, VA of 80%, and VA of 20%
Dynamic Volume Levels & BreakoutsUpdated and improved v.1.3
Description
This mathematical indicator exposes the different volume-weighted multi-temporal key price levels and their breakouts.
Background
The volume factor allows us to align our analysis to institutional activity, this gives us a guarantee of “true” movement behind the price action. In addition, the 200-session factor naturally acts as a “magnet” where the price tends to interact statistically. Finally, in conjunction with these two variables, multi-temporality is integrated, which gives us a full spectrum of levels of interest.
By default, it is designed to work in 1D temporality, the indicator shows breaks and is strategically distributed (most traded time frames).
The indicator is fully customizable according to each strategy, although its essence is mostly remarkable in high temporalities.
Suggestions for use
Institutional levels
Dynamic support and resistance
Death and Golden Cross
Trend confirmation and strength
Volume with High/Low ColoringThe "Volume with High/Low Coloring" indicator is designed to help traders visually differentiate between high, low, and normal volume bars relative to recent historical averages. By applying dynamic color coding and customizable thresholds, this indicator enhances volume analysis and improves your ability to spot key moments of accumulation, distribution, or market inactivity.
High Volume: A bar is marked as high volume when it exceeds the average by a customizable multiplier (default is 1.5×) .
Low Volume: A bar is considered low volume when it falls below the average by another multiplier (default is 0.5×) .
Normal Volume: All bars that fall between the high and low thresholds.
Each category is displayed in a different user-selectable color, providing instant visual feedback for volume dynamics.
Customizable Colors:
High Volume: Light Green (default: semi-transparent green)
Low Volume: Light Blue (default: semi-transparent blue)
Normal Volume: Yellow (default: semi-transparent yellow)
Average Volume Line: Gray (optional reference line)
Dynamic Volume Levels & BreakoutsDescription
This mathematical indicator exposes the different volume-weighted multi-temporal key price levels and their breakouts.
Background
The volume factor allows us to align our analysis to institutional activity, this gives us a guarantee of “true” movement behind the price action. In addition, the 200-session factor naturally acts as a “magnet” where the price tends to interact statistically. Finally, in conjunction with these two variables, multi-temporality is integrated, which gives us a full spectrum of levels of interest.
By default, the indicator shows breakouts and is strategically distributed (most traded timeframes).
The indicator is fully customizable according to each strategy.
Suggestions for use
Institutional levels
Dynamic support and resistance
Death and Golden Cross
Trend confirmation and strength
GEEKSDOBYTE IFVG w/ Buy/Sell Signals1. Inputs & Configuration
Swing Lookback (swingLen)
Controls how many bars on each side are checked to mark a swing high or swing low (default = 5).
Booleans to Toggle Plotting
showSwings – Show small triangle markers at swing highs/lows
showFVG – Show Fair Value Gap zones
showSignals – Show “BUY”/“SELL” labels when price inverts an FVG
showDDLine – Show a yellow “DD” line at the close of the inversion bar
showCE – Show an orange dashed “CE” line at the midpoint of the gap area
2. Swing High / Low Detection
isSwingHigh = ta.pivothigh(high, swingLen, swingLen)
Marks a bar as a swing high if its high is higher than the highs of the previous swingLen bars and the next swingLen bars.
isSwingLow = ta.pivotlow(low, swingLen, swingLen)
Marks a bar as a swing low if its low is lower than the lows of the previous and next swingLen bars.
Plotting
If showSwings is true, small red downward triangles appear above swing highs, and green upward triangles below swing lows.
3. Fair Value Gap (3‐Bar) Identification
A Fair Value Gap (FVG) is defined here using a simple three‐bar logic (sometimes called an “inefficiency” in price):
Bullish FVG (bullFVG)
Checks if, two bars ago, the low of that bar (low ) is strictly greater than the current bar’s high (high).
In other words:
bullFVG = low > high
Bearish FVG (bearFVG)
Checks if, two bars ago, the high of that bar (high ) is strictly less than the current bar’s low (low).
In other words:
bearFVG = high < low
When either condition is true, it identifies a three‐bar “gap” or unfilled imbalance in the market.
4. Drawing FVG Zones
If showFVG is enabled, each time a bullish or bearish FVG is detected:
Bullish FVG Zone
Draws a semi‐transparent green box from the bar two bars ago (where the gap began) at low up to the current bar’s high.
Bearish FVG Zone
Draws a semi‐transparent red box from the bar two bars ago at high down to the current bar’s low.
These colored boxes visually highlight the “fair value imbalance” area on the chart.
5. Inversion (Fill) Detection & Entry Signals
An inversion is defined as the price “closing through” that previously drawn FVG:
Bullish Inversion (bullInversion)
Occurs when a bullish FVG was identified on bar-2 (bullFVG), and on the current bar the close is greater than that old bar-2 low:
bullInversion = bullFVG and close > low
Bearish Inversion (bearInversion)
Occurs when a bearish FVG was identified on bar-2 (bearFVG), and on the current bar the close is lower than that old bar-2 high:
bearInversion = bearFVG and close < high
When an inversion is true, the indicator optionally draws two lines and a label (depending on input toggles):
Draw “DD” Line (yellow, solid)
Plots a horizontal yellow line from the current bar’s close price extending five bars forward (bar_index + 5). This is often referred to as a “Demand/Daily Demand” line, marking where price inverted the gap.
Draw “CE” Line (orange, dashed)
Calculates the midpoint (ce) of the original FVG zone.
For a bullish inversion:
ce = (low + high) / 2
For a bearish inversion:
ce = (high + low) / 2
Plots a horizontal dashed orange line at that midpoint for five bars forward.
Plot Label (“BUY” / “SELL”)
If showSignals is true, a green “BUY” label is placed at the low of the current bar when a bullish inversion occurs.
Likewise, a red “SELL” label at the high of the current bar when a bearish inversion happens.
6. Putting It All Together
Swing Markers (Optional):
Visually confirm recent swing highs and swing lows with small triangles.
FVG Zones (Optional):
Highlight areas where price left a 3-bar gap (bullish in green, bearish in red).
Inversion Confirmation:
Wait for price to close beyond the old FVG boundary.
Once that happens, draw the yellow “DD” line at the close, the orange dashed “CE” line at the zone’s midpoint, and place a “BUY” or “SELL” label exactly on that bar.
User Controls:
All of the above elements can be individually toggled on/off (showSwings, showFVG, showSignals, showDDLine, showCE).
In Practice
A bullish FVG forms whenever a strong drop leaves a gap in liquidity (three bars ago low > current high).
When price later “fills” that gap by closing above the old low, the script signals a potential long entry (BUY), draws a demand line at the closing price, and marks the midpoint of that gap.
Conversely, a bearish FVG marks a potential short zone (three bars ago high < current low). When price closes below that gap’s high, it signals a SELL, with similar lines drawn.
By combining these elements, the indicator helps users visually identify inefficiencies (FVGs), confirm when price inverts/fills them, and place straightforward buy/sell labels alongside reference lines for trade management.
High Volume Color ChangeHigh Volume Color Change Strategy
This indicator combines volume analysis with MACD to identify potential trading opportunities. It tracks trading performance and provides real-time P&L calculations.
Key Features:
1. Volume Analysis:
- Detects high volume candles (1.5x above average volume)
- Uses a 10-bar lookback period for volume comparison
- Marks high volume candles on the chart (optional)
2. Trading Signals:
- Generates buy signals when price changes direction after a high volume candle
- Generates sell signals when price changes direction after a high volume candle
- Uses MACD convergence as an additional filter
- Shows signal markers on the chart
3. Performance Tracking:
- Tracks total trades and profitable trades
- Calculates cumulative P&L
- Shows current position and unrealized P&L
- Displays win rate percentage
4. Money Management:
- Uses initial balance to determine position size
- Compounds profits/losses for subsequent trades
- Calculates P&L based on percentage changes
- Tracks current balance and total P&L
5. Customization:
- Adjustable volume threshold
- Configurable lookback period
- Optional display of volume and signal labels
- Date range selection for analysis
6. Alerts:
- Separate alerts for buy and sell signals
- Clear messages indicating signal type
The strategy is designed for traders who want to:
- Identify high-volume price reversals
- Track their trading performance
- Manage position sizing based on account balance
- Compound their profits/losses
- Get clear buy/sell signals with alerts
Quantum Edge Pro - Adaptive AICategorical 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)
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
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.
Categories
Primary: Trend Analysis
Secondary: Mathematical Indicators
Tertiary: Educational Tools
"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.
Dollar VolumeThe Dollar Volume indicator enhances traditional volume analysis by showing not only the number of shares traded, but also the actual capital exchanged per bar. Using the formula
(High+Low)/2×Volume , it calculates dollar volume to give a clearer picture of real market participation. This approach helps traders identify where significant money is flowing—an important distinction when evaluating the strength of price moves or spotting potential institutional activity.
Volume bars are color-coded based on price direction, and a 50-period Volume Moving Average (VMA)—set to 50 by default—is plotted as a baseline to define “normal” volume levels. When a bar's volume exceeds this average by a user-defined multiple (default is 2×), it is highlighted: blue by default when volume is bullish and elevated, and maroon when bearish and elevated. This makes it easy to spot unusual or high-impact volume spikes at a glance, especially during potential breakout or reversal setups.
In the top-right corner of the chart, a compact display—highlighted in purple by default—shows the current dollar volume, with the option to toggle and view the average dollar volume instead. Meanwhile, the Y-axis continues to show raw share volume, giving you access to both perspectives side by side. With its combination of real capital flow, visual volume signals, and customizable thresholds, the Dollar Volume indicator is a practical and powerful tool for confirming price action, identifying accumulation, and monitoring momentum shifts.
TA Pressure GaugeThe Pressure Gauge indicator is composed of two main plotted elements in Oscillator Mode: the Up/Down Volume Ratio (UDVR) as a histogram, and the Relative Strength (RS) Score as a continuous line. These two metrics work together to provide real-time insights into both volume momentum and relative performance.
The UDVR histogram measures the ratio of buying volume to selling volume. Specifically, if the current close is greater than the previous close, the volume for that bar is classified as up volume. If the current close is lower than the previous close, it’s classified as down volume. Over a 50-bar rolling window (or fewer if limited history exists), the sum of up volume is divided by the sum of down volume to calculate the UDVR. The result is normalized and plotted as vertical bars centered around a baseline value of 50. A UDVR value greater than 1 indicates bullish dominance—more buying than selling—while a value less than 1 indicates bearish pressure. The histogram bars are dynamically color-coded:
Lime or Green when the UDVR is rising and remains above 1, signaling increasing buying strength.
Red or Maroon when the UDVR is falling and below 1, indicating growing selling pressure.
The second component is the Relative Strength Score (RS Score), plotted as a line graph overlaid on the oscillator. This is calculated by dividing the current closing price of the selected asset by the closing price of a benchmark index (e.g., SPX). The result is normalized over a selectable lookback period—63 bars (3 months), 126 bars (6 months), or 251 bars (12 months)—and then converted into a value between 1 and 99. This RS line reflects how well the asset is performing compared to the broader market. When the RS Score is above 70, it indicates strong outperformance and leadership; below 30 suggests underperformance.
The true value of Oscillator Mode is in its ability to combine these two readings visually. When both the UDVR histogram is green and elevated, and the RS line is rising and above 70, it often indicates strong institutional accumulation and momentum—key ingredients for high-probability breakout or trend-following trades. This dual-layered confirmation system enables traders to cut through noise and focus on setups that align both in volume strength and market relative performance. The oscillator can be fully customized within the script to change colors, sizing, and input periods, making it flexible for various trading styles and timeframes.
Look at this textbook flag forming on ticker symbol WGS. The setup was clean, and the Pressure Gauge was already showing bullish signals.
Following the breakout, you can see how the move confirmed what the Pressure Gauge was indicating early on—strong buying pressure and clear relative strength.
High Volume + High Price Change Candles (Relative to Volume SMA)The indicator marks days on which high volume was accompanied by high price change. Important to see where there was aggressive buying or selling. The High and Low of these candles may act as crucial support/resistance price points for a better interpretation of the price action.
VWAP&5EMA📘 VWAP + 5 EMA Combo
This indicator provides a clean and modular framework for tracking key moving averages and VWAP levels. Ideal for intraday and swing traders, it allows full control over which components to display.
✅ Features:
Rolling VWAP – volume-weighted moving average over a custom period
Session VWAP – standard intraday VWAP
Daily EMA (D1) – from higher timeframe
Intraday EMA – based on current chart
5 Custom EMAs – fully adjustable and individually toggleable (default: 9, 21, 50, 100, 200)
🎯 Use Case:
Quickly assess dynamic support/resistance, confluence zones, and trend alignment across timeframes – without clutter. All lines are optional and independently configurable.
Candle Traded Value (₹ Cr)This indicator visualizes the traded value (Volume × Close Price) of each candle in ₹ Crores. It helps identify high-activity candles based on total money flow rather than just volume.
🔹 Histogram Bar Color Logic:
🟧 Orange: > ₹50 Cr
🔴 Red: > ₹10 Cr
⚫ Black: > ₹4 Cr
🔵 Blue (default): ≤ ₹4 Cr
🔹 Features:
20-candle average line (blue) for trend comparison
Labels on candles with traded value > ₹4 Cr (rounded to whole numbers)
Use this to quickly spot big-money activity and volume spikes in rupee terms.
Grid Long & Short Strategy [ trader_N08 ]Core Logic & Methodology
1. Trend & Momentum Filters:
The strategy uses two Exponential Moving Averages (EMAs): a slow EMA (default 200) for trend direction, and a fast EMA (default 50) for additional confirmation.
For long trades: the price must be above both EMAs and the RSI (Relative Strength Index, period 14) must be above a user-defined threshold (default 40).
For short trades: the price must be below both EMAs and the RSI must be below a user-defined threshold (default 60).
2. Volume Confirmation:
Trades are only considered when the current volume exceeds a multiple (default 1.2x) of the 20-period average volume, aiming to avoid low-liquidity signals.
3. Grid Entry System:
Upon a valid signal, the strategy opens an initial position and sets a “base price.”
Additional entries (“grid levels”) are added if the price moves against the initial position by a multiple of the Average True Range (ATR), with each subsequent grid level spaced further apart using an expansion factor.
The number of grid levels is capped (default: 1, user-adjustable) to control risk and position sizing.
4. Risk Management:
Each position uses both a fixed stop loss and take profit, defined as a percentage of the base entry price (defaults: 0.3% stop, 4% take profit).
A trailing stop is also applied, based on a user-defined multiple of ATR.
Only one grid is active per direction at a time; grids reset when all positions are closed.
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Default Properties & Backtest Settings
Account Size: 10000$
Commission: 0.01 %
Slippage: 5 ticks
Risk Per Trade: The default settings are designed to risk a small percentage of equity per grid level, but users should verify that their position sizing does not exceed sustainable risk (generally not more than 5–10% per trade).
Sample Size: The strategy is intended to generate a sufficient number of trades when applied to liquid markets and appropriate timeframes (e.g., 15m–4h charts on major FX, crypto, or indices).
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Underlying Concepts
Grid Trading: A method of adding positions at predefined intervals as price moves, aiming to capture mean reversion or trend continuation.
Trend & Momentum Confirmation: Reduces false entries by requiring alignment of price, moving averages, and RSI.
ATR-Based Spacing: Uses market volatility to dynamically set grid distances and trailing stops.
Volume Filter: Seeks to avoid signals during low-activity periods.
Footprint Stacked Imbalance + Absorption Detectorthis indicator looks for stacked imbalance on footprint charts or candle stick when price returns it a good chance for a balance from the level and i also added an absorpsion indicator this will look for agressive buyer or sellers buy passive limit orders , so if buyer agressive buys are not moving the price up they are getting absorped and soon will die out and fade the other direction.
Clean Shelf & BreakoutTradingView Pine Script (v5) that marks a stock as having a “clean shelf” if it has spent the last 15 candles with each candle’s intraday range < 15% (i.e., (high - low) / low < 0.15). It adds a label when a breakout happens after this shelf:
Market Maker Zones [VWAP + Liquidity + Stop Hunts]This is a Pine Script indicator for TradingView that identifies market maker zones through VWAP, liquidity zones, and stop hunt levels. Here's what each component does:
VWAP Component:
Calculates Volume Weighted Average Price from a specified anchor time
Uses cumulative volume and price-volume to track institutional interest
Plotted as an orange line that market makers often use as a reference
Liquidity Zones:
Identifies bars with volume exceeding 1.5x the average (configurable)
Highlights these high-volume areas with blue background
These represent zones where large orders were executed
Stop Hunt Zones:
Tracks recent highs and lows over a 20-bar window
Plots horizontal lines at these levels with labels
These are areas where stop losses typically cluster
Key Market Maker Concepts:
The indicator assumes market makers hunt stops at obvious levels (recent highs/lows), accumulate positions in high-volume zones, and use VWAP as a fair value reference. When price approaches these zones, it often indicates potential reversal or continuation points.
Usage Tips:
Watch for price reactions near VWAP line
High-volume zones often act as support/resistance
Stop hunt levels frequently get tested before significant moves
Combine all three elements to identify high-probability trade setups
The script is well-structured with clear input parameters and visual elements that make it easy to spot these institutional footprints on your charts.
ScalpMaster Pro AIScalpMaster Pro AI is a precision-built AI-powered trading indicator designed for scalpers and intraday traders. It combines multiple high-probability strategies like: