面向 A 股日K、分钟K与ETF分钟数据的本地量化引擎，集成增量同步、本地缓存、复权、批量查询、回测与指标计算。
EvoQuant is a self-evolving AI research agent specialized in quantitative investment research. It runs the full research loop autonomously
证券、期货市场量化交易相关业务和技术知识笔记
Systematic Volatility Research and Backtesting for equity options
Curated roadmap for quant finance interviews (Quant Trader, Quant Researcher, Quant Analyst): probability, mental math, brainteasers, coding & high-signal resources.
Python package that enables access to the entire Darwinex Data Offering (DARWIN, FX, Stock, Commodity, Index and Cryptocurrency assets) from one Wrapper Library.
Read-only trading journal and review harness: Jev typed judgments, agent integration, and a reproducible finance benchmark. No orders, no advice.
Quantitative research platform for crypto: 120 pre-registered hypotheses, deflated-Sharpe validation, and a permanent ledger of everything that failed. Currently paper trading.
Trading Evolved book code
Structured collection of quantitative finance projects organized by core methodological domains, covering stochastic modeling, valuation, portfolio construction, risk management, trading simulations, and predictive modeling.
Evidence-traceable, point-in-time multi-agent research for China A shares
LLM-powered Quantitative research assistant which combines financial data, quantitative models, and natural laungage generation to produce insightful market research reports. AI/ML + FinTech Engineering
C++/Python microstructure research engine for event-driven limit order book prediction and reproducible quantitative experiments.
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
Szigor Research reference for systematic signals, execution constraints, ledger replay, portfolio state, and backtesting.
Nautilus_Trader_Jerry_fall_2023 is a customized verision of Nautilus trader by Zhuoran "Jerry" Li on Fall 2023
Cross-sectional Transformer and FFN for stock return prediction and alpha generation. Implements GKX (2020) NN5 replication and MSRR loss (Kelly et al. 2025) for direct portfolio Sharpe optimization. Avg SDF Sharpe 2.05, significant alpha (t=5.34) unexplained by FF5+Momentum.
Generates returns of Mutual Funds and comparison them
Explore how Bitcoin market sentiment influences trader behavior and performance using real trading data and emotional indicators like the Fear & Greed Index. This project applies data science, clustering, and visualization techniques to uncover actionable insights for crypto trading strategies.
面向中国 A 股研究的 Agent Skill：公告、财报、研报解析与因子候选生成
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