quant research notebook

Ansh Dani

Incoming UChicago MSFM. CS and Math, ASU. I build market microstructure systems, Bayesian regime models, and volatility tools, with an emphasis on reproducible claims and honest failure analysis.

incomingUChicago MSFM
graduatedASU CS and Math, 4.0
focusC++ microstructure and Bayesian regimes

featured work

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2026C++, market microstructure, limit order book, ITCH replay, Avellaneda Stoikov, benchmarking, queue position

C++ Limit Order Book And Market Making Simulator

result3.7M events/sec benchmark, 12,423 QQQ ITCH messages, paired 30 seed statistics, and queue diagnostics.

selected inventory risk and risk adjusted improvement under hand chosen flow; broad PnL dominance did not survive statistical checks.

status: completebenchmark: 3.7M events/secreplay: 12,423 QQQ ITCH messagesconfidence: high
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2025Python, algorithmic trading

IMC Prosperity 4

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

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

status: completeartifact: public leaderboardrank: #194 algo
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2026honors thesis, Bayesian inference, regime detection, HMM, CUSUM, CPPI

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.

status: completeartifact: thesis PDFconfidence: high
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2025PyTorch, neural SDEs, rough volatility

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.

status: research prototypeartifact: GitHub repoconfidence: medium
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2026Python, Kalshi API, DuckDB, scikit learn, XGBoost

PRISM

result122 tests, 85% coverage, documented API limits.

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

status: framework completetests: 122 passingcoverage: 85%confidence: high on engineering, documented data limits
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2026Python, NumPy, SciPy

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.

status: completeresult: out of samplescope: single asset and one pairconfidence: medium
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Browser native analytical tools, preserved from the old site and led by the new Kalman filter demo.

experience

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Stochastic Time Series Modeling Intern

Endless Moments LLC

September 2025 to present

Built and evaluated stochastic time series models for prediction and diagnostics.

Pythontime seriesmodel diagnostics

CS and Math Tutor

Sun Devil Athletics

August 2025 to January 2026

Tutored undergraduates in calculus, algorithms, and proof oriented problem solving.

calculusalgorithmsteaching

Applied Statistics Research Intern

Morrison School of Agribusiness

June 2025 to September 2025

Worked on applied statistics for USDA grant data, including transformations and model checks for high variance economic series.

statistical inferencetime seriesR

AI Developer Intern

ONLC Training Centers

May 2025 to June 2025

Built AI assisted training and retrieval prototypes for course operations.

retrievalLangChainOpenAI APIs

contact

Get in touch

The fastest ways to reach me, no forms.

guest@notebook:~$ cat contact.json
{ "email": "anshdani04@gmail.com", "github": "github.com/AnshDani2004", "linkedin": "linkedin profile" }
guest@notebook:~$
Chicago based · quantitative research and trading.