Agentic coding skills for backtesting trading strategies using VectorBT. Supports Indian, US, and Crypto markets with realistic transaction cost modeling, TA-Lib indicators, QuantStats tearsheets, and 12 ready-made strategy templates.

An implementation of Giuseppe Paleologo's Rademacher Antiserum, designed to assess strategy performance consistency through Rademacher complexity and RAS-adjusted Sharpe Ratios. This code evaluates strategy robustness by applying Rademacher random vectors for anti-overfitting analysis.

Helix Treasury System

scikit-learn-compatible time-series cross-validation: purging, embargo, combinatorial purged CV, and deflated Sharpe ratios

Crypto-currencies (Bitcoin) trading & Transfer Learning applications

Systematic intraday opening-range breakout strategy on US equities — 10-year validated backtest with walk-forward optimization, statistical robustness suite, and live paper-trading on Alpaca.

面向 A 股因子的可复现研究框架：信号 → IC / 分层回测 / walk-forward → Tear Sheet 报告

一个面向 AI Agent / 量化实习的多智能体量化研究平台 / A resume-ready multi-agent quantitative research platform for AI Agent & Quant internships

Adversarial co-evolution orchestrator: an executor LLM improves an artifact, a deterministic scorer judges it (keep-if-better via git), a validator LLM advises — until quality peaks. Off-the-shelf agent CLIs, walk-forward scoring, live web dashboard. General-purpose, not just trading.

Portfolio backtest engine with montecarlo simulation, walk-forward, efficient frontier, FIRE, charts, performance optimization, max drowdown with Ai suggest!

Quantitative forex strategy research engine — 10 strategies, Optuna optimization, walk-forward + Monte-Carlo validation, honest overfit/ruin analysis. Pure Python.

Prove a trading edge survives real costs out-of-sample, or kill it. An honest edge-validation harness for CME micro futures & prop challenges.

Personal local quant trading + research platform — PIT factor composite (momentum / quality / value / PEAD) on the S&P 500, daily pipeline, paper execution, FastAPI + Next.js dashboard.

Utilized time series, statistic, ML and NLP models to practice. Topics include stock forecasting (algorithm trading), US 2024 presidential election and customer sentimental review.

A股量化Alpha研究: 多因子选股 + LightGBM非线性因子挖掘, Walk-forward验证, 自动交叉验证检查

Quant research: early-breakout momentum on SP500 — 9.4% CAGR vs SPY's 7.9% on 26-year survivorship-bias-free backtest (1,081 historical constituents). Automated Alpaca paper trading. 305 tests. Not financial advice.

SiraEdge Portfolio Optimization Module - Complete implementation with 7 optimization models, ML integration, and comprehensive documentation

End-to-end quantitative trading system for Taiwan stocks — DoubleEnsemble model, 300+ factors, Walk-Forward backtesting, React dashboard

Method to use rolling optimization with 3D LSTM arrays. Explores integrating multi-asset portfolio with embedding layer.

NFL forecasting engine — spread/ML/total/Wong-teasers with two-stage LightGBM + Monte Carlo, isotonic calibration, walk-forward backtest, and a native macOS desktop app.