research

Working Papers

2026

1. 

   Market Efficiency in Prediction Markets: A Comparison with Derivatives

   SSRN

   with Michele Fabi, Roberto Marfè, and Lorenzo Schoenleber

   Abstract ▲

   We study pricing efficiency in decentralized prediction markets by comparing Polymarket prices with option-implied prices derived from derivatives. We analyze nearly 5,000 Polymarket contracts written on Bitcoin (BTC) and Ethereum (ETH), two assets for which prediction-market contracts and liquid derivatives markets coexist. We find that Polymarket prices closely track option-implied prices, but systematic deviations remain: they are concentrated in tail and barrier contracts, vary with sentiment, volatility, demand, and market frictions, and imply more probability mass on extreme price movements. To guide our empirical investigation, we introduce a parsimonious limits-to-arbitrage model that formalizes equilibrium behavior in decentralized prediction markets.

   Presentations: Decentralized Finance & Crypto Workshop at Scuola Normale Superiore (Pisa), 5th Workshop on Decentralized Finance (DeFi) in Association with Financial Cryptography 2026 (St. Kitts)^*, XXVII Workshop on Quantitative Finance (Bergamo), Tech 4 Finance #3: AI and Blockchain (Paris), Designing DeFi (D2 2026) (New York), Frontiers in DeFi 2026 (Berlin)^*, 3rd Structured Retail Products and Derivatives Conference (Hagen), Future Finance Fest (3f) (Amsterdam)^*, 8th Future of Financial Information Conference (Frankfurt), 14th International Moscow Finance Conference (Moscow)^*, 2025 Global AI Finance Research Conference (Hong Kong), DeFi Workshop 2025 (Grenoble)^*

2024

1. 

   Factor Dispersions

   SSRN

   with Daniil Gerchik, Lorenzo Schoenleber, and Grigory Vilkov

   Abstract ▲

   Dispersion strategies capture the difference in variance dynamics between a basket and its components. Even though smart-beta indices intend to load heavily on a particular factor, factor dispersions based on such baskets are exposed to risks of other factors and idiosyncratic variances. Analyzing factor dispersions through a linear factor model and equicorrelation representations, we recover driving forces behind dispersion dynamics and work out an attribution of a dispersion risk premium. As a balanced combination of systematic and idiosyncratic variance components, dispersion and its risk premium provide signals about future changes in systematic and alpha-based investment opportunities.

   CBOE Research Grant

   Presentations: Second Liverpool Workshop in Option Markets (Liverpool), Second Bonn-Frankfurt-Mannheim PhD Conference (Bonn), World Federation of Exchanges Research Webinar (online)^*, Cboe Risk Management Conference 2024 (Snowbird)^*, 2024 FMA Conference on Derivatives and Volatility (Chicago)