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Jing-Lavinia/README.md

Jing Li

Quantitative Researcher

Systematic Alpha · Relative Value · Research Engineering

I turn market questions into evidence-first research with explicit information clocks, realistic frictions, portfolio constraints, and honest evaluation.

LinkedIn · Email

Open to quantitative research opportunities.


Selected case studies

Systematic Equity Alpha

Cross-sectional financial ML with a neutral alpha sleeve, separately governed beta exposure, next-open execution, and frozen evaluation.

Evidence: 23.49% development CAGR and 1.24 Sharpe at 5 bps; the short holdout gained 7.71% but was driven by the overlay rather than standalone alpha.

View case study →

Crypto Relative Value

Point-in-time perpetual-futures research with causal pair discovery, funding, contract lifecycle controls, and exact P&L attribution.

Evidence: 1.62 development Sharpe at 7 bps plus funding; the locked terminal window gained 4.12% and exposed material regime dependence.

View case study →

IMC Prosperity 4

Solo multi-round trading research covering fast valuation, options path risk, decision attribution, and a failed strategy that motivated a release gate.

Evidence: #1,036 of 18,803 teams globally, #17 in China.

View case study →

Research principles

  • Respect the clock: distinguish observation, decision, execution, and P&L.
  • Model the portfolio: make exposure, concentration, turnover, and costs explicit.
  • Keep adverse evidence: weak sleeves, failed releases, and limitations stay visible.

Publications and earlier research

  • Carbon Risk and Return Prediction — corresponding author; graph-structured information and Multi-CNN return prediction. DOI
  • Gaussian Control with Hierarchical Semantic Graphs in 3D Human Recovery (HUGS) — coauthor; no module-level or quantitative personal-contribution claim is made here. arXiv
  • Financial prediction, structured representations, sequence models, and biomedical generation are summarized with explicit provenance and contribution boundaries. Research foundations →

Public disclosure

These repositories are technical case studies, not source releases. Implementation remains proprietary; research design, failure analysis, and trade-offs can be discussed in interviews.

All trading results are simulated research evidence, not live performance, investment advice, or a guarantee of future returns.

Popular repositories Loading

  1. Jing-Lavinia Jing-Lavinia Public

    Quantitative researcher | Systematic alpha, relative value, and research engineering.

  2. systematic-equity-alpha systematic-equity-alpha Public

    Case study: causal, cost-aware U.S. large-cap alpha research with explicit attribution.

  3. crypto-relative-value-research crypto-relative-value-research Public

    Case study: causal crypto perpetual relative value with funding, lifecycle risk, and exact accounting.

  4. imc-prosperity-4-research imc-prosperity-4-research Public

    Case study: solo IMC Prosperity 4 trading decisions, path risk, and failure analysis.

  5. research-foundations research-foundations Public

    Publications and research themes with explicit contribution and disclosure boundaries.