Project write ups

BTC/USD Cross-Venue Price Discovery

Coinbase vs Kraken Market Microstructure and Econometric Price Discovery

resultAcross 9 econometrically usable paired sessions, Coinbase showed stronger short-horizon price leadership over Kraken: BH-significant Granger evidence appeared in 6/9 sessions Coinbase → Kraken versus 1/9 in the reverse direction.

accepted sessions

10

econometrically usable

9

BH-significant Granger CB→KR

6/9

BH-significant Granger KR→CB

1/9

The hard part was preventing the result from collapsing into a single clean claim. Short-horizon leadership was clear; long-run leadership was not.

A confirmatory empirical study of BTC/USD price discovery across Coinbase and Kraken using synchronized market data, VAR/VECM models, Granger causality, predictive regressions, impulse responses, Gonzalo–Granger component shares, and Hasbrouck information-share bounds. The evidence favors stronger Coinbase short-horizon leadership, while long-run price discovery remains heterogeneous across sessions.

BayesAudit

Budget-Constrained Oversight for Hierarchical LLM Workflows

result144 confirmatory and held-out trajectories across 36 matched quartets, three constraint domains, and 1,945 passing tests.

trajectories

144

matched quartets

36

constraint domains

3

passing tests

1,945

The hard part was preserving a held-out nonreplication instead of tuning the benchmark until the original result returned.

BayesAudit is a reproducible Python research framework for studying budget-constrained oversight in hierarchical LLM workflows. It combines hierarchical workflow simulation, strategic attackers, rule-based and Bayesian monitoring, objective violation scoring, provider-cost controls, and matched experimental studies.

C++ Limit Order Book & Market-Making Simulator

Matching Engine, ITCH Replay, Market-Making Diagnostics, and Artifact Validation

result3.7M events/sec benchmark, 12,423 QQQ ITCH messages, 30-seed strategy statistics, 10-seed fill-rate diagnostics, and validator-backed artifacts.

A deterministic C++ market microstructure simulator with price-time priority matching, Nasdaq ITCH replay, naive vs Avellaneda-Stoikov market-making experiments, queue-position diagnostics, ten-seed fill-rate mechanism tests, and artifact validation.

A systems-focused market microstructure project implementing a deterministic C++ matching engine, benchmark harness, ITCH replay path, and market-making simulator for comparing naive symmetric quoting with Avellaneda-Stoikov-style inventory-aware quoting under controlled synthetic and ITCH-calibrated flow.

Vol Surface Research Lab

SABR/Heston Calibration, Robustness, and Failure Diagnostics

result121 tests, 206 row recommended universe, SABR median RMSE 0.0190 to 0.0077, Heston global RMSE 0.1174.

Built a reproducible Python options research engine for chain cleaning, forward extraction, OTM IV surface construction, static-arbitrage diagnostics, SABR robustness testing, Heston calibration, and same-universe model comparison. The main result was diagnostic: filtering reduced SABR median RMSE from 0.0190 to 0.0077, while global/per-expiry Heston underfit SABR despite passing synthetic recovery checks.

A reproducible Python research engine for option-chain cleaning, implied-volatility surfaces, SABR/Heston calibration, robustness testing, and model failure analysis.

Bayesian Sequential Decision Making Thesis

resultBayesian regime detection, HMM plus CUSUM, CPPI drawdown control, and S&P 500 crisis validation.

the hard part was accepting that a well trained Bayesian agent can still stay wrong too long.

A short Projects stub for my Barrett honors thesis. The full paper writeup lives in Writing.

IMC Prosperity 4

result#194 algo, top 1.4% of 18,800 teams.

the hard part was adapting strategy across rounds under sparse feedback.

A multi round algorithmic trading competition where simple models, inventory discipline, and careful iteration mattered more than fancy machinery.

Deep Hedging under Rough Volatility

resultResearch prototype with repo; no public performance number claimed.

the hard part was making path structure matter without overclaiming the metric.

A rough volatility hedging prototype comparing smooth GBM intuition with jagged volatility paths and learned path dependent hedges.

PRISM

result122 tests, 85% coverage, documented API limits.

the hard part was proving which historical data did not exist.

A prediction market signal framework for sports, built around validation, fees, and data limits rather than a clean story.

Bayesian Market Filters

resultOut of sample Sharpe near 0.7 after fees.

the hard part was reporting the modest number after fixing the inflated one.

Estimating hidden state in noisy market data, then testing whether that estimate survives fees and a clean split.

Hierarchical Bayesian Portfolio Optimization

resultBayesian covariance prototype with repo; no broad return claim.

the hard part was watching the optimizer exploit covariance noise.

A Bayesian covariance estimation project built after sample covariance made mean variance portfolios unstable.