vectorbt

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.

Autonomous quantitative trading research platform that transforms stock lists into fully backtested strategies using AI agents, real market data, and mathematical formulations, all without requiring any coding.

A strategy tester for MetaTrader5 in Python language

Web app for pandas-ta indicators

End-to-end algorithmic trading terminal featuring PyTorch LSTM forecasting, NLP market sentiment analysis, Lasso ML feature selection, and vectorbt backtesting. Built for multi-asset quantitative research.

A backtesting web app for walk-forward optimization with common indicator strategies.

Nine-agent AI framework automating quant research from hypothesis generation through leakage-aware backtesting

A comprehensive framework for developing and backtesting quantitative trading strategies.

A-share AI quant research with PIT data, walk-forward validation, DeepSeek agents & continuous paper trading｜中国 A 股 AI 量化研究与持续模拟盘

Nous Ergon — signal quality analysis, portfolio simulation, and autonomous parameter optimization via sweep + VectorBT

Local AI Investing Platform — v3.1 Master Spec. Hybrid AI-assisted quant. LangGraph + Temporal, DeepSeek R1 + Qwen 2.5, VectorBT + Nautilus, Next.js 16 PWA.

VelaQuant: event-driven US equities research, backtesting, and paper-trading infrastructure

量化回测系统 - 支持布林带/配对交易/网格交易Quantitative backtesting system - Supports Bollinger bands/paired trading/grid trading

Criação de mini mesa quant

ETH futures 15m swing bot. Built around safely swapping strategies: shadow-run candidates, hot-swap with importlib, human approval over Telegram. Never went live.

Cost-aware momentum backtester + live paper-trading bot. Python/VectorBT. Fees & slippage modelled in every run; in-sample vs out-of-sample always split.

A staged research pipeline for systematic trading strategies (S1 screen, S2 optimize, S3 validate, S4 significance, S5 portfolio) with vectorbt backtests and keyless yfinance data.

Genetic algorithm that evolves combinations of 24 technical indicators to discover robust trading strategies. Streamlit dashboard with vectorbt backtesting.

Paper-only trading research lab: 3 quantitative strategies, walk-forward optimization, Claude-powered analysis, IBKR paper execution, Telegram control. Production patterns for financial automation.

Institutional-grade hybrid pipeline algorithmic trading system using VectorBT, CCXT, and NautilusTrader