research

Working Papers

2026

  1. Market Efficiency in Prediction Markets: A Comparison with Derivatives
    Market Efficiency in Prediction Markets: A Comparison with Derivatives
    Abstract ▲
    We study pricing efficiency in decentralized prediction markets by comparing market-implied probabilities from Polymarket with benchmarks derived from option-implied risk-neutral distributions extracted from the derivatives market. From Bitcoin and Ethereum prediction-market contracts, we find that, although Polymarket prices broadly track option-implied benchmarks, they show systematic price differences driven by behavioral factors and market frictions. Price differences are most pronounced in tail events, during periods of high volatility, and in response to major macroeconomic shocks, and they reflect the influence of sentiment, attention, and blockchain-specific risks. These results reveal both efficiency and behavioral distortions in prediction markets.
    Presentations:
    • December 2025: 2025 Global AI Finance Research Conference, Hong Kong, China
    • January 2026: Decentralized Finance & Crypto Workshop, Scuola Normale Superiore, Pisa, Italy
    • April 2026: XXVII Workshop on Quantitative Finance, University di Bergamo, Bergamo, Italy
    • May 2026: 2026 conference Tech 4 Finance 3: AI and Blockchain, Paris, France
    • May 2026: Designing DeFi Conference, New York, USA (scheduled)
    • May 2026: 3rd Structured Retail Products and Derivatives Conference, Hagen, Germany (scheduled)
    • June 2026: 8th Future of Financial Information Conference, Frankfurt, Germany (scheduled)

2024

  1. Factor Dispersions
    Factor Dispersions
    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:
    • May 2024: Bonn-Frankfurt-Mannheim PhD Conference 2024, Bonn, Germany
    • November 2024: 2024 FMA Conference on Derivatives and Volatility, Chicago, USA
    • July 2025: Second Liverpool Workshop in Option Markets, Liverpool, UK

Work in Progress

2026

  1. Firm-level News Networks
    Firm-level News Networks