Charlie Yan

Quantitative research on options — volatility surface dynamics, execution cost, and the accounting that decides whether an edge survives contact with a spread.

Most of what I publish is the negative result and the machinery that produced it, because in this work a wrong number that reconciles is more expensive than one that crashes.

Day to day I trade a live index options book — variance and skew premium through defined-risk structures, with a real-time arbitrage-free surface calibration underneath it.

Currently in Los Angeles, looking for a quantitative research or trading seat. Email is the fastest way to reach me.

Each pairs with a public repo holding the code and a data-availability statement that says plainly whether you can run it.

  1. Quantitative Index Options Trader, Foghnan Trading Dec 2024 — Present

    • Systematic capture of SPY variance and skew premium through defined-risk put spreads, with a walk-forward execution framework and a transaction-cost model for non-linear slippage across calendar rollovers.
    • Real-time, arbitrage-free volatility surface calibration that separates left-tail crash risk from normal diffusive vol, driving regime-shifting parameters that protect short-volatility structures under stress.
    • Cross-venue execution pipeline for event-driven mispricings across index contracts: multi-leg orders behind strict risk gates, plus capacity and decay analysis rigorous enough to disprove an apparent alpha hypothesis on transaction-cost grounds.
    • Statistical risk audits and post-trade review on new signals. Rejected a false smile-residual signal, and showed that mark-to-market accounting structurally understated real drawdown risk.
    • Fail-closed, multi-provider data pipeline with concurrency budgets, feeding an options analytics layer that tracks implied vol term structure, skew proxies and dealer gamma exposure.
  2. Quantitative Research Intern, JFA Research Sep — Dec 2024

    • Prototyped a liquidity-aware volatility surface framework that preserves price-relevant structural kinks where order-book supply and demand justify them.
    • Validated across major index options and small-cap names, cutting pricing artifacts outside the NBBO on illiquid tickers while holding exact baseline fits. Shipped interactive diagnostics for out-of-sample decay analysis.

Python · C++ · SQL · volatility surface calibration · IV term structure & skew · dealer gamma · walk-forward design · capacity & decay analysis · FIX connectivity · low-latency execution · LangGraph · MCP / FastMCP

  • tickq 2026

    A small SQL tool for market and execution data on DuckDB — a partitioned Parquet lake, market-data macros with a stated NULL contract, and quality checks whose recall and precision are measured on seeded defects.

  • boostkit 2026

    Histogram gradient-boosted trees from scratch in numpy, leaf-wise with the LightGBM recipe, plus exact TreeSHAP — validated against LightGBM and brute-force Shapley.

  • edge-or-memory 2026 — in progress

    A sealed, point-in-time harness for the study "Do LLM research agents find edge or remember it?" — the apparatus, published before any result exists.

  • quotesim 2026

    An options quoting simulator with synthetic flow — Avellaneda-Stoikov and GLFT quoters in price and vol space, delta-band hedging, an exact P&L attribution, and comparisons paired by seed only.

  • volsurf 2026

    Implied-volatility surfaces from option chains — parity forwards, a vectorised Black inverter, raw-SVI fits per expiry, and static-arbitrage checks that are counted and located, never repaired.

  • pricers 2026

    Option pricing methods written out in numpy and validated against closed forms and QuantLib with explicit tolerances — Black-Scholes, trees, finite differences with PSOR and Brennan-Schwartz, Monte Carlo, Longstaff-Schwartz, Heston COS.

  • riskkit 2026

    Portfolio risk for a futures-and-options book — VaR and ES by four methods, backtests with computed size and power, stress and reverse stress, and explicit limit-down, empty-book and stale-quote semantics.

  • tcakit 2026

    Transaction cost analysis and market-impact calibration for equities and listed options — implementation shortfall, difficulty-adjusted scorecards, and impact fits that report held-out error.

  • deskboard 2026

    Real-time options risk and P&L dashboard with deterministic replay — per-leg Greeks, attribution with an exact identity, a limit engine that says why it fired, and a Telegram bot for the alerts.

  • quant-research-agent 2026

    A research agent that reviews quant backtests, and the evals that measure whether it catches known bugs and refuses to overstate results. The eval numbers are the deliverable.

  • options-surface-mcp 2026

    Arbitrage-free SVI volatility surfaces, Greeks and static no-arbitrage checks, exposed as MCP tools with a derived-golden eval harness.

  • chainmill PyPI 2026

    Parallel ingest of zipped option-chain archives into a queryable SQLite store, with resumable builds and per-archive failure isolation.

  • exitkit PyPI 2026

    Twenty-seven position-exit policies behind one interface, with a drop-in adapter for backtesting.py.

  • runseal PyPI 2026

    Content-addressed provenance for research runs — prove which data, code, config and environment produced a number, and that none of it changed since.

  • opentape 2026

    Twelve backtest bug classes, twelve runtime invariants, thirteen synthetic reproductions — the checks from "Dollar-Correct, Time-Wrong" as a library.

  • aesthetic-eval 2026

    A CLI that scores websites across 10 UI/UX dimensions against research-backed thresholds, with SARIF output and baseline diffing.