High-Frequency Realized Stochastic Volatility Model

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The PRMIA Hong Kong Chapter

Seminar on Data Analytics and Risk Management - High-Frequency Realized Stochastic Volatility Model

The seminar is jointly organized by the <a href="https://prmia.org/Public/Network/Chapter_Websites/Hong%20Kong.aspx" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Hong Kong Chapter of The Professional Risk Managers' International Association (PRMIA)</a> and <a href="https://www.isi-web.org/isi-community/committees/outreach-to-east-asia" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">The International Statistical Institute (ISI) East Asian Outreach Committee</a>. Date: Jun 15, 2022 (Wed)Time: 17:00 - 18:00 (HKT) [Check the time at your place <a href="https://www.timeanddate.com/worldclock/converter.html?iso=20220615T090000&amp;p1=102" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">HERE</a>] <h2>High-Frequency Realized Stochastic Volatility Model</h2>By Professor Toshiaki WatanabeInstitute of Economic Research, Hitotsubashi UniversityA new high-frequency realized stochastic volatility model is proposed. Apart from the standard daily-frequency stochastic volatility model, the high-frequency stochastic volatility model is fit to intraday returns by extensively incorporating the intraday volatility periodicity and the reaction of intraday volatility to macroeconomic announcements. The daily realized volatility calculated using intraday returns is incorporated into the high-frequency stochastic volatility model by taking account of the bias in the daily realized volatility caused by microstructure noise. A Bayesian method via Markov chain Monte Carlo is developed for the analysis of the proposed model. The empirical analysis using the 5-minute returns of S&amp;P 500 E-mini futures provides evidence that our high-frequency realized stochastic volatility model improves in-sample model fit and volatility forecasting over the high-frequency stochastic model without the daily realized volatility.

Toshiaki Watanabe has been a Professor at the Institute of Economic Research, Hitotsubashi University since 2006, where he was the Director from 2019 through 2020. He has also been the Director at the Center for the Promotion of Social Data Science Education and the Assistant to the President for Research and Education on Social Data Science since 2020. He has also been working at the Institute for Monetary and Economic Studies, Bank of Japan as an individual commission since 2006, where he was formerly a Senior Fellow from 2005 through 2006. He taught at the Tokyo Metropolitan University’s economics department from 1993 through 2005. He is the Chair of the Economics, Finance and Business (EFaB) section of the International Society of Bayesian Analysis (ISBA) in 2022. He received his Ph.D. in Economics from Yale University in 1993 and B.A. in Economics from the University of Tokyo in 1986.

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High-Frequency Realized Stochastic Volatility Model

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