⚛ Quantum Reservoir Computing
QRC • QLE treats markets as coupled oscillators. A quantum-style reservoir (Ψ) preserves temporal structure while MSMF kernels (Energy, Resonance, Topology) measure order and geometry. Signals appear when cross‑scale coherence and reservoir pulses align. Direction and Magnitude are separated so you see both the lean and the charge of the state.
Spectral‑Fractal Resonance Engine
SFRE is a decision‑grade overlay that fuses four orthogonal proxies of market structure into a single, portable score. It separates what you see (calibrated visuals) from what you act on (gate‑only gain for thresholds), keeping visuals honest while timing remains responsive.
Market Renormalization Flow
MERAflow redefines market analysis through a layered renormalization framework that distills volatility, consistency, and compression into a unified energy metric — the MERA score. Engineered for precision traders and systematic strategists, it renormalizes price action across micro to macro scales, quantifying the "flow state" of markets by normalizing local oscillations against broader entropy contexts.
Turning Point – Advanced
ATR‑driven SuperTrend with an adaptive RSI engine, divergence context, regime/volume filters, and anti‑whipsaw controls. Prints Buy/Sell balloons on price and is scanner‑ready (register_signal).
What it measures
- SuperTrend (on selectable price source)
- TR = max(H−L, |H−C[1]|, |L−C[1]|); ATR = EMA(TR, atrPeriod)
- Upper band = src − multiplier × ATR; Lower band = src + multiplier × ATR
- State flips only when close cleanly crosses the prior opposite band.
Reversal Point Dynamics – Pro
Reversal Point Dynamics Pro (RPD Pro) is a precision-engineered trading system built for traders who demand adaptability, speed, and accuracy across all market conditions.
Powered by the Wick Pressure Kernel (WPK) and Adaptive Entropy Engine, RPD Pro isolates true market exhaustion points, filters out false reversals, and identifies structural turning zones long before conventional indicators confirm them.
This system dynamically adjusts to volatility and liquidity conditions—scanning price action in real time to reveal key reversal opportunities in scalping, day trading, swing trading, and position-based setups. Whether the market is ranging, trending, or in high-velocity breakout phases, RPD Pro continuously recalibrates signal precision for the active environment.
ICT Theory – Advanced
The ICT Theory – Advanced (ICT-A) system transforms Inner Circle Trader methodology into a precision-engineered, real-time market-structure and liquidity mapping framework. Designed for traders who operate with institutional awareness, ICT-A automatically identifies and tracks Swing Highs/Lows (SH/SL), Breaks of Structure (BOS), Changes of Character (CHoCH), Order Blocks (OB), Fair Value Gaps (FVG), Liquidity Pools (BSL/SSL), and Kill Zones, with all elements persisting across timeframe changes for seamless multi-frame analysis.
Each module uses fixed, pre-allocated data series for structural memory and computational efficiency, ensuring that every critical level remains visible and relevant during live execution. ICT-A bridges ICT theory and algorithmic precision, providing traders with a clear liquidity-based roadmap rather than a lagging signal system.
Fractal Bayesian Confluence Model
The Fractal Bayesian Confluence Model (FBCM) represents a new dimension of probabilistic market intelligence — a convergence of fractal geometry, Bayesian inference, and volatility-adaptive learning. Designed for advanced traders and data-driven tacticians, FBCM decodes the probabilistic DNA of price structure by continuously re-estimating the likelihood of trend, mean reversion, and consolidation regimes across multiple temporal scales.
At its core, FBCM fuses three critical layers of market cognition:
- Fractal State Analysis – Multi-horizon lookbacks (short, mid, long) capture self-similar structures and recursive volatility cycles to detect regime shifts.
- Bayesian Belief Propagation – Continuously updates posterior probabilities of trend persistence versus exhaustion using adaptive priors for real-time learning.
- Dynamic Confluence Engine – Integrates weighted evidence from momentum, volatility, compression, and fractal symmetry to quantify conviction with statistical clarity.
Unlike conventional trend or oscillator systems, FBCM doesn’t “signal”—it infers. Each probability layer acts as a Bayesian negotiator, balancing entropy and order to reveal the most probable path forward. The model learns, forgets, and rebalances its confidence dynamically, creating a living feedback system that evolves with market behavior.
RSI of RSI Deviation
Momentum Acceleration With Statistical Confluence
RoRD measures acceleration of momentum by applying RSI to RSI (RSI²), smoothing with T3, and normalizing behavior with a dual Z‑score. Instead of only showing momentum, RoRD highlights how momentum itself is changing and how statistically unusual that change is right now. Built for scalpers through swing traders who want speed, confluence, and clarity.
Deviation over Deviation
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nulla euismod condimentum felis vitae efficitur. Sed vel dictum quam, at blandit leo.A volatility-of-volatility oscillator that quantifies how today’s deviation deviates from its own recent behavior. DoD flags statistically rare expansion/compression regimes, then confirms or filters them with higher‑timeframe context.
What it measures
- DoD Z-Score = z of (stdev(src, devLen)) over dodLen:
DoD Z = [stdev(src, devLen) − sma(stdev, dodLen)] / stdev(stdev, dodLen) - HTF DoD Z: same formula on a higher timeframe; the latest HTF Z is mapped to your current chart for confluence.