Systematic signal refinement framework using point-in-time data, triple-barrier labeling, calibrated ML models, and probability-aware portfolio construction.

中证500多因子指数增强策略研究框架：Spec 驱动的不可变实验管理、严格 PIT 数据、训练/验证/测试集三段隔离，验证期 IR 2.150（仅供学习研究，非投资建议）

Point-in-time Python equity research pipeline for replicating and extending Kim et al. (2021) Arbitrage Portfolios, with a runnable synthetic-data demo.

Real-time vintages of daily, end-of-month, and monthly average effective exchange rates (EERs). Accompanies RBA RDP 2025-09.

Schema-controlled Python research system for equity factor research, synthetic validation, portfolio accounting, backtesting, and empirical-data readiness.

Synthetic research-bias validation toolkit for systematic trading research.