Estimating Stochastic Volatility under the Assumption of Stochastic Volatility of Volatility

Moawia Alghalith, Christos Floros and Konstantinos Gkillas
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Moawia Alghalith: Department of Economics, University of West Indies, St. Augustine, Trinidad, Trinidad and Tobago
Konstantinos Gkillas: Department of Business Administration, University of Patras, Patras 26500, Greece

Risks, 2020, vol. 8, issue 2, 1-15

Abstract: We propose novel nonparametric estimators for stochastic volatility and the volatility of volatility. In doing so, we relax the assumption of a constant volatility of volatility and therefore, we allow the volatility of volatility to vary over time. Our methods are exceedingly simple and far simpler than the existing ones. Using intraday prices for the Standard & Poor’s 500 equity index, the estimates revealed strong evidence that both volatility and the volatility of volatility are stochastic. We also proceeded in a Monte Carlo simulation analysis and found that the estimates were reasonably accurate. Such evidence implies that the stochastic volatility models proposed in the literature with constant volatility of volatility may fail to approximate the discrete-time short rate dynamics.

Keywords: nonparametric estimators; stochastic volatility; stochastic volatility of volatility (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:8:y:2020:i:2:p:35-:d:344228

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