Research Interests

Financial econometrics with a focus on derivatives markets, option-implied risk measures, tail risk, volatility modelling, and empirical asset pricing.

Publications

  1. Weihan Li, Jin E. Zhang, Xinfeng Ruan, and Pakorn Aschakulporn (2026)

    The rare disaster concern index: RIX

    Global Finance Journal, 69, 101226.

  2. Weihan Li, Jin E. Zhang, Xinfeng Ruan, and Pakorn Aschakulporn (2024)

    An empirical study on the early exercise premium of American options: Evidence from OEX and XEO options

    Journal of Futures Markets, 44(7), 1117-1153.

  3. Haileslasie Tadele, Xinfeng Ruan, and Weihan Li (2022)

    Corporate governance and firm-level jump and volatility risks

    Applied Economics, 54(22), 2529-2553.

Working Papers

  1. Weihan Li, Jin E. Zhang, Xinfeng Ruan, and Pakorn Aschakulporn (2025)

    The rare disaster concern index (RIX) and cross-sectional equity returns: Evidence from the U.S. energy market

Conference Presentations

Research Methods

Option Pricing & Risk-Neutral Measures

Model-free extraction of option-implied risk measures via numerical integration (CBOE VIX methodology); RIX construction and term-structure estimation across 30-, 60-, and 90-day horizons, with analytical derivation under the Gram-Charlier density framework (Global Finance Journal, 2026).

Option Liquidity & Microstructure

Multiple liquidity proxies to explain the negative early exercise premium (NEEP) of American index options, with cross-sectional OLS robustness checks across moneyness-maturity subgroups (Journal of Futures Markets, 2024).

Cross-Sectional Asset Pricing & Event Studies

Fama-MacBeth regressions, quintile portfolio sorts, long-short strategy evaluation; CAR estimation around earnings announcements and political shocks using Fama-French three-, four-, and five-factor benchmarks.

Volatility Modelling & Systemic Risk

Mimicking-portfolio construction of firm-level jump and volatility risk measures (Applied Economics, 2022); GARCH-based volatility series as macroeconomic state variables; CoVaR and ΔCoVaR estimation via quantile regression; Forward-ΔCoVaR panel forecasting across one- to four-quarter horizons.

Panel Data & Causal Inference

GLS, fixed-effects, and System GMM estimation; endogeneity diagnostics (Hausman, Durbin-Wu-Hausman); panel unit root testing (Fisher-ADF); Newey-West standard errors; bootstrap Kolmogorov-Smirnov inference.