Trading Evolved book code
-
Updated
Jun 14, 2020 - Jupyter Notebook
Trading Evolved book code
面向 A 股本地数据的 AI 因子研究工作台:因子生成、存储、注册、评估与报告。
IB FlexStatement to PyFolio bridge
Python Quant Stack
Trading Strategy Development
Quantitative performance & risk analytics: 150+ financial metrics, portfolio optimization, Monte Carlo simulation, and attribution — the actively maintained successor to empyrical, pyfolio, and alphalens.
A trading algorithm that identifies stocks with the largest potential for growth while heavily considering its volatility using quantopian
Backtesting workflow for a moving average crossover strategy using Apple stock data, Backtrader, and PyFolio-style performance analysis.
Forecasting AUD/USD and EUR/USD with ARMA/ARIMA/SARIMA models on 5-minute OHLCV data -- does a 1-step-ahead price prediction actually translate into a tradeable edge?
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
Analyzes historical performance of stocks and portfolios using yfinance for data and pyfolio for comprehensive tear sheets.
🔮 AI-Powered Algorithmic Trading Platform — QuantInsti Library Integration | LangGraph + LiteLLM + GARCH + pyfolio
To associate your repository with the pyfolio topic, visit your repo's landing page and select "manage topics."