Dynamics of realized volatilities and correlations: An empirical study |
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| Institution: | 1. Department of Mathematics, University of Québec, P.O. Box 8888, Downtown Station, Montréal, QC, Canada H3C 3P8;2. Hydro-Québec, Finance Department, HEC-Montréal, 3000 Chemin de la Côte-Ste-Catherine, Montréal, QC, Canada H3T 2A7;1. Utrecht School of Economics, Utrecht University, Utrecht, The Netherlands;2. Supervisory Policy Division, De Nederlandsche Bank, Amsterdam, The Netherlands and Department of Economics, University of Groningen, Groningen, The Netherlands;1. Griffith Business School, Griffith University, 170 Kessels Road, Nathan, Queensland 4111, Australia;2. Department of Business Administration, European University Viadrina, Große Scharrnstraße 59, 15230 Frankfurt (Oder), Germany;1. Central University of Finance and Economics, School of Statistics and Mathematics, China;2. Beihang University, School of Economics and Management, China;3. Yanqi Lake Beijing Institute of Mathematical Sciences and Applications, China;1. School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China;2. School of Economics and Management, Southwest Jiaotong University, Chengdu, China;3. School of Finance, Yunnan University of Finance and Economics, Kunming, China |
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| Abstract: | This study examines two important issues underlying realized volatility and correlation estimators. First, an empirical inquiry is conducted to assess whether Bax and Eurodollar futures tick-by-tick data can be characterized as marked-point processes. Second, ARMA, neural network, GARCH-BEKK, and naive volatility and correlation forecasts are compared in an out-of-sample context when a trader prices an interest rate spread option based on those forecasts and simultaneously delta-hedges her position. Other loss functions are also considered. Competing volatility forecasts are also compared to implied volatilities. |
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