FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading
tushare行情数据本地化存储、行情数据分析、形态选股
Stock-Robo-Advisor project including backtesting, simulating and practicality for future.
This is a project of portfolio optimization using Quantum-inspired Tabu Search and Trend Ratio
A stock investment assistant tool which utilized supervised machine learning models such as Logistic Regression, Random Forest, and Support Vector Machine to predict the stock’s 60 days’ return rate. If a specific stock outperformed the average return rate, the model would recommend to hold.
一个面向 A 股研究流程的 Qlib 工作台，支持收盘后数据校验、滚动训练、推荐日报、复盘回测和 ClawTeam 任务编排。
Uses SQL DB and API (live prices) to display info, prices and logo. Built using Flask
RL stock selection for China A-share — bundled polars-native factor library (105 Alpha101 + 191 GTJA Alpha191 = 296 factors), board-aware price limits, GPU train + ONNX CPU infer, MIT-licensed.
An AI-driven quantitative stock analysis system for A-Shares. Integrates multi-factor models, fundamental scoring, and enhanced technical analysis (MACD/RSI) to generate interactive HTML investment reports with price predictions.
Quantitative A-share stock selection strategies using AkShare
Deep learning quant trading strategy for China A-share. It demonstrates execution-aware signal modeling, as-of-date data hygiene, multi-path encoders, and offline-online consistency. Core alpha assets are intentionally omitted.
Using PCA(Principle Component Analysis) and DEA(Data Envelope Analysis) techniques to identify relative efficient firms (stocks).
A Julia package for selecting assets based on volume, volatility, and market cap. Supports multiple selection methods for financial analysis.
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