Forecasting market index volatility using Ross-recovered distributions

DOI10.1080/14697688.2021.1939407zbMath1484.91475OpenAlexW3184454133MaRDI QIDQ5068087

Marie-Hélène Gagnon, Dominique Toupin, Gabriel J. Power

Publication date: 5 April 2022

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2021.1939407

zbMATH Keywords

forecastoptionsvolatilityphysical distributioninternationalrisk-neutralRoss recovery

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Derivative securities (option pricing, hedging, etc.) (91G20)

Cites Work

• Nonparametric risk management and implied risk aversion
• Option market trading activity and the estimation of the pricing kernel: a Bayesian approach
• Positive Eigenfunctions of Markovian Pricing Operators: Hansen-Scheinkman Factorization, Ross Recovery, and Long-Term Pricing
• Volatility is rough
• Recovery with Unbounded Diffusion Processes*
• Ross recovery with recurrent and transient processes
• Forecasting S\&P 100 volatility: The incremental information content of implied volatilities and high-frequency index returns

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