I build research-to-production style quant systems across data engineering, signal research, machine-learning research, research-bias validation, portfolio construction, risk governance, execution lifecycle, auditability, market-structure research, and reproducible reporting.

This public GitHub profile is a sanitized showcase. It uses synthetic data, mock execution, simplified examples, and public documentation. Proprietary production signals, live platform configuration, private parameters, real trading logs, paid vendor data, and platform-identifier information are intentionally excluded.

VNQ data lake manual
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research / synthetic data layer
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        +--> Ares public architecture demo
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        |   Chronos master portfolio governor
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        |   Execution and audit toolkit
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        +--> Equity alpha research lab
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        |   XGBoost sweep / OOS prediction / feature importance
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        +--> Quant research validation toolkit
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        |   look-ahead / leakage / survivorship / purge / embargo audits
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        +--> vHedge defensive allocation demo
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        +--> QingLong A-share research lab

• Separate data, signal, ML research, validation, portfolio, risk, execution, and reporting layers.
• Use synthetic data and dry-run examples for public demonstration.
• Prefer reproducible runs with config snapshots, deterministic seeds, leaderboards, audit reports, and manifests.
• Evaluate return, drawdown, turnover, costs, liquidity, tradability, leakage risk, and implementation risk together.
• Treat validation as a system requirement: look-ahead checks, label leakage guards, OOS testing, purge/embargo windows, point-in-time universe membership, cost assumptions, universe stability, and market-structure constraints.
• Keep live execution details, platform-specific configuration, and private strategy parameters outside public repositories.

This profile is designed for research and professional review by:

• Quant researchers
• Quant developers
• Portfolio and risk professionals
• Academic supervisors
• Research collaborators

Nothing in these repositories is investment advice or a trading recommendation. Public examples are intentionally simplified and synthetic.