Characteristics of Implied and Realized Volatility: the Case of Deep OTM Put Options
The relation between implied and realized volatility constitutes the crucial issue in contemporary risk management and algorithmic investment systems giving us the rationale to adequately forecast future levels of implied volatility. Differently from the majority of papers we focus mainly on implied volatility for OTM and deep OTM options with maturity shorter than two weeks. Therefore, apart from realized volatility, we introduce additional variables explaining future levels of implied volatility i.e. volatility term structure and volatility slope calculated separately for various moneyness levels. The research is performed on 1 minute option data directly from CBOE covering the period from 2004 to 2019.
We confirm the results of Christensen and Prabhala (1998), Gwilym and Buckle (1999), Hansen (1999) and Sakowski and Ślepaczuk (2019) that implied volatility contains incremental information about future volatility, beyond that contained in the past realized volatility. Similarly to Fleming (1998) and Strun and Hansen (2002) we report that implied volatility forecasts are upwardly biased. Our findings show that including information from additional variables increases the explanatory power of our models. Moreover, our results differ from previous studies (Day and Lewis, 1992, Harvey and Whaley 1992) because we use longer time series, overlapping and non-overlapping data, moneyness ranging from ATM to deep OTM options and much shorter maturities.
Rafal Sieradzki is currently a visiting scholar at New York University Stern School of Business, an associate professor of finance at Cracow University of Economics, and a member of the Quantitative Finance Research Group at the University of Warsaw. Previously, he served as a lead economist at the National Bank of Poland, where he was responsible for analyzing financial markets, with a special focus on the equity and derivatives segments.
Rafal's work has primarily focused on financial economics, the application of game theory to IPO underpricing, quantitative finance, and the interactions between financial markets and macroeconomics. His research has been presented and discussed at various conferences and seminars in Europe, Asia, and America. Currently, at NYU Stern, he is conducting research on the integration of climate risk into bankruptcy prediction models, with support from a grant from the National Science Centre.
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Meeting ID: 923 1986 2000