Research
Research Interests
Application of modern machine learning techniques in quantitative and empirical finance
- Volatility modeling
- Empirical option pricing, return predictability, and microstructure
- Optimal portfolio and ETF construction
- Deep learning and deep reinforcement learning for systematic trading strategies
- Causal inference for transaction cost modeling
- Blockchain technology and De-Fi (automated market makers)
Working Papers and Work in Progress
"High-Frequency Multivariate Sequence Modeling for Intraday S&P 500 Volatility and 0DTE Options Mispricing," (2025)
with Christopher S. Jones
"Nonlinear Shrinkage Estimation for High Dimensional Hidden Markov Models," (2025)
with Gourab Mukherjee
"Alpha Term Structure in Corporate Bonds for Pricing and Hedging," (2025)
with Petter Kolm and Terry Benzschawel
Publications and Forthcoming Papers
"Modeling Wallet-Level Behavioral Shifts Post-FTX Collapse: An XAI-Driven GLM Study on Ethereum Transactions," (2025), Forthcoming, IEEE Artificial Intelligence for Business (AIxB)
with Benjamin Gillen, Rashmi Ranjan Bhuyan, and Gourab Mukherjee
"High-Frequency Kelly Criterion and Fat-Tails: Gambling with an Edge," (2022)
ProQuest Dissertations and Theses
"Kelly Criterion: From a Simple Random Walk to Lévy Processes," (2021)
SIAM Journal of Financial Mathematics, 12-1, 342-368
with Sergey Lototsky
"Transient Feedback and Robust Signaling Gradients. Appendix: Feedback on Receptor Synthesis Rate," (2016)
International Journal of Numerical Analysis and Modeling
with Frederic Y. Wan
Permanent Working Papers
"Predicting Realized Variance Out of Sample: Can Anything Beat The Benchmark?," (2022)
arXiv preprint
"Is the Kelly Criterion Just Another Utility Function?," (2022)
with Peter Carr
You can also find my articles on my Google Scholar profile.