{"skill":{"slug":"jiadong-quant-tools","displayName":"Quant Tools 1.0.0","summary":"学术导向量化研究工具集。包含7大核心库（因子分析、组合优化、AI增强、因果验证、衍生品定价、回测引擎、情感分析）和5大投研工具（VeighNa交易框架、Qlib AI投研、WTP高性能框架、AkShare数据接口、JupyterHub研究环境）。适用于策略研发、因子挖掘、论文复现、资产配置、API服务化等投研任务...","tags":{"analysis":"1.0.0","data":"1.0.0","finance":"1.0.0","latest":"1.0.0","quant":"1.0.0","research":"1.0.0"},"stats":{"comments":0,"downloads":147,"installsAllTime":0,"installsCurrent":0,"stars":0,"versions":1},"createdAt":1775744838974,"updatedAt":1775745411375},"latestVersion":{"version":"1.0.0","createdAt":1775744838974,"changelog":"Initial release of quant-tools: a comprehensive academic-oriented quantitative research toolkit.\n\n- Includes 7 core research libraries (factor analysis, portfolio optimization, AI enhancement, causal inference, derivatives pricing, backtesting engine, sentiment analysis).\n- Bundles 5 major investment research tools: VeighNa trading framework, Qlib AI research, WTP high-performance engine, AkShare data interface, JupyterHub research environment.\n- Supports strategy development, factor mining, academic replication, asset allocation, and API service tasks.\n- Ideal for quant research teams seeking an integrated toolchain for both algorithmic innovation and investment research.\n- Trigger words: 量化、quant、因子、组合优化、因子分析、回测、交易框架、数据接口、学术研究.","license":"MIT-0"},"metadata":null,"owner":{"handle":"jiadong0723","userId":"s171evqrw320fst1p7x7dqf9hs84gww5","displayName":"jiadong0723","image":"https://avatars.githubusercontent.com/u/267246555?v=4"},"moderation":null}