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

Market regime detection system using CWT wavelet analysis

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

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

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

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

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

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

Coordinate Discovery branch of OMNIABASE: multibase structural analysis for hidden coordinates and latent signatures.

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

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

Institutional-grade 5-phase quantitative analysis pipeline — 20+ indicators, HMM regime detection, GARCH volatility, walk-forward backtesting, Claude-powered trade notes.

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.

Financial Data Analytics Dashboard

Uncertainty-aware financial forecasting for the Borsa Istanbul 100 Index. Transformer model with Monte Carlo Dropout for epistemic uncertainty, integrating Turkish equity, US equity, and FRED-MD macro data. Coursework for COM0415 Applied Deep Learning.

A structured project for time series analysis and forecasting using statistical methods

Unsupervised latent regime discovery for crypto markets. HMM, VAE, and temporal contrastive models identify hidden market states from multi-exchange data. FastAPI + React dashboard. Docker Compose.

LSTM-driven market regime detection with rule-based signal generation for systematic trading.

Quantitative trading system for XAU/USD — PELT+BOCPD regime detection, RS-GBM Monte Carlo (N=10,000), ICT strategies. P(ruin)=0% across all stress tests.

Market regime detector for NIFTY 50 using Stoic emotional taxonomy, Wundt's Valence-Arousal model, and Hidden Markov Models — built on 10 years of fundamental data.