I work across finance, financial engineering, quantitative finance, and data science, with a focus on derivatives, risk management, and portfolio management. My research spans the pricing, hedging, and market design of derivatives and event-linked instruments; risk measurement, margining, and risk-premia dynamics across assets and regimes; the evolution of factor premia and market structure; and portfolio construction and dynamic allocation informed by modern data-science and machine-learning methods.
ORCID: 0009-0000-2439-0566
SSRN Working Paper · June 2026 · 20 pages
Prediction markets such as Kalshi and Polymarket aggregate dispersed beliefs into discoverable probabilities, yet lack the derivative architecture that has matured around equity, FX, and crypto assets. This paper constructs that architecture from first principles: the probability index is modelled as a bounded martingale, a closed-form funding-rate identity is derived for the event-linked perpetual future, and a full pricing, hedging, and portfolio-margin framework bridges prediction markets and classical derivatives theory.
SSRN Working Paper · July 2026 · 22 pages
Stambaugh's AFA Presidential Address argued that index funds primarily displace noise traders, shrinking the mispricings active managers exploit. This paper extends that mechanism to the cross-section of equity factors: premia identifiable from price-based characteristics (value) compress disproportionately as passive share grows, while others re-sort — reshaping which factor premia survive in an increasingly indexed market.
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