regime-detection

Systematic options trading intelligence for small accounts. Create desks in your portfolio, allocate capital and risk appetite at Desk Level. Every trade generated by system is specific for the desk keeping in mind capital allocation, risk limits, position sizing

HMM-based market microstructure regime detection for cryptocurrency order books — 30+ features, Gaussian HMM, C++/pybind11 LOB engine, interactive Plotly Dash dashboard

Financial market regime detection using Hidden Markov Models for adaptive trading strategies

Unsupervised regime detection for financial time series using embeddings and clustering.

High-performance, Polars-native technical analysis in Python and Rust with 221 Native Indicators · Full Ehlers DSP suite · Regime Detection · Backtest engine · Bit-identical streaming & batch · Options India suite

Experimental causal-inference research on financial regimes: PCMCI+, ICP and causal forests over market data (work in progress)

World Embedding: a daily 64-dim representation of the aggregate economic state (1985-2021). Drop-in state vector for asset pricing, macro forecasting, regime detection, and event studies.

Quantum Geometry and Topological Regime Detection in Financial Markets

Self-Discovering Regime Detection with Uncertainty Quantification

📈 Bitcoin trading system using Hidden Markov Models for market regime detection. Real-time signals, multi-timeframe analysis & interactive regime visualization.

Detecting market regimes using Hidden Markov Models on S&P 500 data

AlphaInfo Structural Intelligence API as a Claude Code skill — anomaly detection, regime change, multi-sensor fault isolation, with self-correcting cascade and plan-aware behavior

Market regime detection system using CWT wavelet analysis

Research-grade systematic equities trading and portfolio research platform focused on regime-aware adaptive multi-strategy allocation.

Macro regime research platform — 10-pillar scoring engine, live web dashboard, portfolio Greeks, Monte Carlo scenarios. CLI + Flask. Built for a PM morning risk meeting.

A fat-tail-native quantitative finance toolkit for Python.

A 30-second test of whether a pattern-finder can tell a real signal from random noise — most can't. An open finding from my ML research on financial markets.

Regime-aware cross-asset risk platform for European markets: 3-state Gaussian HMM, regime-conditional VaR/ES, walk-forward strategy backtests and a stress engine — with deliberate, honest reporting of a negative result.

Algorithmic trading engine for NSE. Regime-Adaptive Ensemble ML (XGBoost + LightGBM). Features automated bias auditing (CI/CD), Triple-Barrier Labeling, and dynamic risk management

RBI-grade market regime detection & liquidity stress modelling using volatility, yield curves, and ensemble HMMs.