I study the behavior of retail investors in options and cryptocurrency markets — and what modern AI means for finance research and teaching. My work appears in the Journal of Financial Markets, the Journal of Behavioral and Experimental Finance, and Finance Research Letters.
I'm an assistant professor of finance at Texas State University's McCoy College of Business. My research asks how real investors actually behave — why retail traders gamble on stock and Bitcoin options, how banking access shapes who participates in crypto, and how markets price political uncertainty in real time.
Alongside the empirical work, I think hard about what AI means for finance — as a research method, as a teaching challenge, and as a force reshaping the industry. I've spoken on treating AI as a teammate rather than a tool, and my current projects apply textual analysis and machine learning to retail investor behavior.
With Ivilina Popova and Y. Liu. Examines whether retail investors treat equity options as lottery-like gambles — and what that behavior means for options markets.
With Y. Liu. Extends the gambling-preferences lens from equities to the Bitcoin options market.
With I. Kumar. Uses India's crypto ban to study how access to traditional banking shapes who participates in cryptocurrency markets.
With A. Tarkom. Traces how markets priced political uncertainty in real time around the 2024 U.S. presidential election.
With Y. Wu. Revisits the role banks played as lenders of first resort during the COVID-19 liquidity crunch.
I teach across the undergraduate and graduate finance curriculum, and I care about preparing students to think well alongside AI — the subject of my workshop "AI as a Teammate, not a Tool" at Texas State's AI in Teaching and Learning Symposium.
Whether it's a research collaboration, a speaking invitation, or a conversation about AI in finance — I'd be glad to hear from you.