Indicator Library

26,000+ engineered features from 60+ proprietary indicators across 13 categories. Every indicator is purpose-built for walk-forward validated crypto trading — no off-the-shelf defaults, no curve-fitting.

Momentum

10 indicators — Directional conviction, trend pressure, and institutional flow detection

Momentum

FB Oscillator

Forward-backward momentum oscillator measuring trend conviction through bidirectional price analysis. Captures momentum asymmetry invisible to traditional single-direction oscillators.

Momentum

Chaos RSI

Chaos theory-enhanced RSI that captures non-linear momentum dynamics and regime transitions. Detects hidden divergences and phase shifts that standard RSI misses entirely.

Momentum

Trend Pressure Index

Volume-weighted momentum gauge combining price velocity with participation metrics. Filters out low-volume moves to isolate genuine institutional-grade trend pressure.

Momentum

Market Structure Oscillator

Identifies structural market shifts through swing high/low analysis and internal structure breaks. Signals trend reversals before traditional indicators by detecting structural change.

Momentum

Isotonic Oscillator

Non-parametric momentum indicator using isotonic regression for noise-resistant trend signals. Preserves monotonic relationships in price data while eliminating false oscillations.

Momentum

Institutional Order Flow Strength

Detects institutional participation through volume-price divergence patterns. Identifies smart money accumulation and distribution phases before price confirms the move.

Momentum

IFS Stochastic

Institutional flow stochastic combining smart money flow analysis with traditional stochastic oscillators. Separates retail noise from institutional conviction in overbought/oversold zones.

Momentum

Volume-Weighted Momentum

Momentum signals weighted by volume participation to filter low-conviction moves. Only flags directional shifts backed by genuine market participation and liquidity.

Momentum

Heikin-Ashi Momentum

Smoothed momentum derived from Heikin-Ashi candle transformations for enhanced trend clarity. Eliminates intra-bar noise while preserving directional momentum information.

Momentum

Elder Ray

Bull/bear power analysis measuring buying and selling pressure relative to moving averages. Quantifies the balance of power between bulls and bears at each price level.

Volatility

5 indicators — Regime detection, compression signals, and adaptive channel positioning

Volatility

Squeeze Index

Detects Bollinger Band / Keltner Channel compression preceding explosive moves. Identifies periods of coiled volatility that historically precede major breakouts.

Volatility

True Volatility Analysis

Volume-adjusted volatility regime classification separating noise from signal. Distinguishes between genuine volatility expansion and random price fluctuations driven by low liquidity.

Volatility

Vol Waterfall

Cascading volatility analysis across multiple timeframes for regime change detection. Tracks how volatility propagates from short to long timeframes to anticipate structural shifts.

Volatility

Williams VIX Fix

Synthetic VIX approximation for crypto markets using Williams’ percentage range method. Provides fear-gauge readings for assets that lack traditional options-derived volatility indices.

Volatility

Keltner Channel Position

Price position within adaptive Keltner channels for volatility-adjusted mean reversion signals. Normalizes price extension relative to ATR-based bands for regime-aware entry timing.

Trend

9 indicators — Directional analysis, trend strength, breakout detection, and exhaustion signals

Trend

Monotonicity Score

Measures trend consistency through directional persistence analysis. Quantifies how “clean” a trend is by scoring the ratio of consecutive same-direction bars over a rolling window.

Trend

Directional Matrix

Multi-factor directional analysis combining momentum, market structure, and volume alignment. Produces a composite directional score that requires agreement across multiple dimensions.

Trend

Geometric Bias

Geometric mean-based trend bias detection for asymmetric price movement analysis. Captures skewed return distributions that arithmetic-based indicators systematically miss.

Trend

Supertrend Polyfactor

Multi-factor supertrend combining ATR, volume, and momentum for adaptive trend following. Self-adjusts sensitivity based on current market regime to reduce whipsaws.

Trend

ADX Regime

ADX-based trend strength classification with DI+/DI- crossover analysis. Separates trending from ranging markets to activate the appropriate strategy parameters.

Trend

Donchian Position

Price position within Donchian channels for breakout and trend-following signals. Normalizes current price relative to the N-period high/low range for clean breakout detection.

Trend

Trend Exhaustion

Detects late-stage trend moves through momentum divergence and extension analysis. Identifies when a trend is running out of fuel before the actual reversal occurs.

Trend

Micro Trend Detection

Short-term EMA/ADX classification into MICRO_UP, MICRO_DOWN, and MICRO_FLAT states. Creates feature variants per micro-regime for regime-conditional signal generation.

Trend

Walk-Forward Enhanced Trend

Trend indicators specifically optimized for walk-forward validation robustness. Designed to maintain predictive power across unseen data folds rather than maximizing in-sample fit.

Volume

8 indicators — Institutional activity detection, VWAP analysis, and money flow tracking

Volume

Volume Surprise

Statistical detection of abnormal volume spikes indicating institutional activity. Uses z-score based thresholds against rolling baselines to flag genuine participation anomalies.

Volume

Rolling VWAP

Multi-period volume-weighted average price for dynamic support/resistance levels. Provides institutional reference prices that act as magnets for price action across multiple timeframes.

Volume

VAPM

Volume-Adjusted Price Momentum normalizes momentum by participation levels. Filters out price moves driven by thin liquidity and highlights conviction-backed directional shifts.

Volume

Swing Anchored VWAP

VWAP anchored to significant swing points for institutional reference levels. Automatically identifies key pivots and calculates volume-weighted fair value from those anchors.

Volume

Anchored Volume Profile

Volume distribution analysis anchored to key price events and swing points. Maps where the most trading activity occurred to identify high-volume nodes and value areas.

Volume

Volume Delta Divergence

Divergence between price and cumulative volume delta indicating hidden accumulation or distribution. Reveals institutional intent when price action alone tells an incomplete story.

Volume

Enhanced Chaikin Money Flow

Advanced CMF with smoothing and divergence detection for money flow analysis. Tracks whether volume is flowing into or out of an asset with enhanced noise reduction.

Volume

A/D Oscillator

Accumulation/Distribution oscillator with multi-timeframe confirmation. Detects whether smart money is accumulating or distributing across synchronized timeframes.

Ichimoku

1 indicator — Complete Kinko Hyo system with cloud, cross, and distance features

Ichimoku

Ichimoku Cloud Analysis

Full Kinko Hyo implementation: Tenkan, Kijun, Senkou A/B, Chikou. Generates cloud thickness, TK cross signals, and price-cloud relationship features for comprehensive trend and support/resistance analysis.

Lorentzian

1 indicator — Machine learning distance classifier for market state identification

Lorentzian

Lorentzian Distance Classifier

Uses Lorentzian distance metric (more robust than Euclidean for financial data) for proximity-based market state classification. Handles outliers and fat tails inherent in crypto price distributions.

Candlestick

3 indicators — Pattern recognition, composite scoring, and ML-based candle classification

Candlestick

Candlestick Pattern Engine

Recognizes 30+ candlestick formations (engulfing, doji, hammer, etc.) with regime-weighted reliability scoring. Pattern confidence adjusts based on the current market regime context.

Candlestick

Candlestick Composites

Composite signals combining multiple candlestick patterns into actionable confluence scores. Aggregates individual pattern signals into a single conviction metric for cleaner entry triggers.

Candlestick

Candle Classifier

ML-based candle type classification beyond traditional patterns for structural analysis. Identifies candle archetypes using body/wick ratios and volume context that named patterns miss.

Harmonic

3 indicators — Fibonacci-based pattern recognition and cross-timeframe harmonic convergence

Harmonic

Harmonic Pattern Recognition

Detects Gartley, Butterfly, Bat, Crab, and Shark patterns using Fibonacci ratio validation. Automatically scores pattern completion quality and projects potential reversal zones.

Harmonic

Fibonacci Features

Multi-level Fibonacci retracement and extension zones with completion probability scoring. Generates proximity features for key Fibonacci levels that act as institutional reference points.

Harmonic

Harmonic Resonance

Cross-timeframe harmonic convergence detection for high-probability reversal zones. Identifies where multiple harmonic patterns across timeframes align to create confluence zones.

Fair Value Gaps

4 indicators — Institutional imbalance detection, mitigation tracking, and absorption analysis

Fair Value Gaps

FVG Detection

Identifies institutional order flow imbalances where price moved so quickly that gaps formed. Analyzes gap size, direction, and fill probability for each detected imbalance zone.

Fair Value Gaps

FVG Mitigation

Tracks gap fill progress and mitigation patterns for re-entry signal generation. Monitors partial and full fills to determine when institutional orders have been satisfied.

Fair Value Gaps

FVG Positioning

Price position relative to active FVGs for directional bias assessment. Measures whether price is trading above, within, or below key imbalance zones for context-aware signals.

Fair Value Gaps

FVG Absorption

Volume analysis within FVG zones to detect institutional absorption patterns. Identifies when large orders are being filled within imbalance zones, signaling potential continuation or reversal.

Pivot Levels

2 indicators — Multi-variant pivot point systems and untested level analysis

Pivot Levels

Multi-Pivot Points

Daily, weekly, and monthly pivots with Fibonacci, Camarilla, and Woodie calculation variants. Generates price-distance features for each level across multiple pivot methodologies.

Pivot Levels

Unreached Levels

Identifies significant price levels not yet tested for magnet/target analysis. Tracks untouched support and resistance zones that tend to attract price action over time.

Statistical

7 indicators — Regime detection, spectral analysis, and probabilistic models

Statistical

CUSUM Change Detection

Cumulative sum algorithm for detecting regime shifts in mean and variance. Provides statistically rigorous change-point detection that flags structural breaks in price behavior.

Statistical

HMM Regime Detection

Hidden Markov Model for probabilistic regime identification. Estimates the most likely hidden market state and transition probabilities between regimes using observable price features.

Statistical

Rolling SSA

Singular Spectrum Analysis for trend/cycle decomposition and noise filtering. Decomposes price series into trend, oscillatory, and noise components without assuming stationarity.

Statistical

Phase Regression

Hilbert transform-based phase analysis for cycle timing and turning points. Extracts instantaneous phase and frequency to identify where price sits within its dominant cycle.

Statistical

Dominant Cycle Analysis

Spectral analysis to identify the current dominant price cycle period. Dynamically adapts indicator lookback periods to match the prevailing market rhythm.

Statistical

Correlation Anomaly

Cross-asset correlation breakdown detection for regime change early warning. Flags when historical correlation structures break down, often preceding major market moves.

Statistical

Mean Reversion Zone Score

Statistical scoring of mean-reversion probability at extreme price levels. Combines z-score, percentile rank, and half-life estimation to assess reversion likelihood.

Smart Money Concepts

5 indicators — Order blocks, liquidity sweeps, and adaptive overbought/oversold analysis

Smart Money Concepts

Order Blocks

Identifies institutional order block zones where smart money accumulated or distributed. Tracks active, mitigated, and breached blocks with volume confirmation for entry zones.

Smart Money Concepts

Liquidity Sweep

Detects stop-hunt patterns and liquidity grabs at swing highs and lows. Identifies when price briefly pierces a key level to trigger stop losses before reversing direction.

Smart Money Concepts

Williams %R Multi

Multi-period Williams %R for overbought/oversold analysis with institutional context. Runs parallel lookback periods to identify when multiple timeframes agree on extreme positioning.

Smart Money Concepts

Williams %R Consensus

Cross-timeframe Williams %R agreement for high-conviction signals. Only triggers when short, medium, and long-term %R readings simultaneously confirm extreme conditions.

Smart Money Concepts

Williams %R Adaptive

Regime-adaptive Williams %R with dynamic thresholds. Automatically adjusts overbought/oversold boundaries based on the current volatility regime to reduce false signals.

Cross-Feature

2 indicators — Derivative features and multi-indicator composite signals

Cross-Feature

Delta Features

Rate-of-change and momentum derivatives across all base indicators. Captures the acceleration and deceleration of every indicator to detect inflection points before they materialize.

Cross-Feature

5D Features

Five-day composite features combining multiple indicator families for medium-term signals. Aggregates cross-category information over a 5-day horizon for swing-trade-grade feature extraction.

26,000+ Engineered Features

Each of the 60+ base indicators generates multiple feature variants. Every raw output is expanded through multi-period lookbacks, regime-conditional variants (Bull/Sideways/Bear/Bubble), micro-trend states (Up/Down/Flat + 6 transitions), delta derivatives, z-score normalizations, and cross-indicator interactions. The result: 26,000+ unique features per symbol, each walk-forward validated across 6 expanding-window folds to ensure out-of-sample robustness.

Ready to Trade with Institutional-Grade Signals?

Our ensemble classifier processes all 26,000+ features through walk-forward validated models to deliver actionable trading signals for BTC, ETH, SOL, XRP, ADA, and DOT.