walk-forward-optimization

Plataforma de trading gratis y de código abierto para Mac (con guía para portarla a Windows con Claude): footprint, DOM, backtesting anti-sobreoptimización y estrategias con IA. 100 % local.

Python backtesting engine built on NautilusTrader for end-to-end quant research: market data ingestion/validation, microstructure calibration, single-asset and stat-arb strategy creation, walk-forward optimization, analytics, portfolio-of-strategies backtesting, and portfolio weight optimization.

Kiploks Trading Robustness Engine is an open-source TypeScript engine for deterministic backtest and walk-forward analysis (WFA) of algorithmic trading strategies, published as @kiploks/engine-* packages under Apache 2.0.

Research framework for evaluating systematic trading strategies using walk-forward optimization, statistical validation, and robustness testing in Python.

Rust port of quant-research-framework: walk-forward backtester with robustness tests and realism controls. 1-to-1 output parity with the Python reference, ~24x faster.

Automatic crypto futures trading bot using Bollinger Band Squeeze strategy. Includes backtesting, optimization, and live trading modules.

End-to-end ML pipeline that predicts BTC/USDT price direction (4h horizon) using XGBoost + Optuna + SHAP. 9-phase architecture, Walk-Forward Validation across 15 folds, 37 technical indicators, 98 automated tests. ROC-AUC: 0.5431.

4-strategy crypto backtesting engine with walk-forward optimisation and Monte Carlo risk analysis. Achieved 52.3% CAGR, Sharpe 1.42 on 2024 out-of-sample data. Built with Python, asyncio, ccxt, TimescaleDB, Redis.

Intraday short-selling system for parabolic micro-cap reversals. Polars + Numba rules engine with SAC reinforcement learning position sizing.

Institutional-grade quantitative trading framework for Binance, OKX, and BitMEX. Features a low-latency execution engine (CCXT-free), multi-strategy concurrency (Trend/Scalp/HV), and a rigorous Walk-Forward Optimization (WFO) pipeline.

Quant research: volatility-scaled trend-following on futures — parameter robustness, multi-timeframe decay, EWMAC/MACD/Bollinger comparison, purged walk-forward optimization, and a multi-asset (NQ/JY/BTC) portfolio

Swing-trading bot for US momentum stocks. Walk-forward optimised, Monte Carlo validated, paper-traded. Personal learning project.

Long-only ETF portfolio optimization (PyPortfolioOpt) with walk-forward backtesting, monthly rebalancing, transaction costs and a min-volatility fallback — benchmarked vs SPY

GPU-accelerated walk-forward optimization for evaluating systematic trading strategies (C++20, OpenCL)

systematic trading strategies developed and validated using walk-forward analysis. The code is modular and structured for production backtesting.

This is my local algorithmic trading system

Institutional-grade market regime detection, systemic risk telemetry, and walk-forward backtesting engine in Python.

Can 2x Claude 4.6 Opus generate infinite money?

Streamlit backtesting engine with a pluggable strategy interface, walk-forward analysis, transaction costs, and regime attribution.