Volatility Proxies for Discrete Time Models

Robin G. de Vilder and Marcel Visser

MPRA Paper from University Library of Munich, Germany

Abstract: Discrete time volatility models typically employ a latent scale factor to represent volatility. High frequency data may be used to construct proxies for these scale factors. Examples are the intraday high-low range and the realized volatility. This paper develops a method for ranking and optimizing volatility proxies. It is possible to outperform the quadratic variation as a proxy for the discrete time scale factor. For the S&P 500 index data over the years 1988-2006 this is achieved by a proxy which puts, among other things, more weight on the highs than on the lows over intraday intervals.

Keywords: volatility proxy; realized volatility; quadratic variation; scale factor; arch/garch/stochastic volatility; intraday seasonality (search for similar items in EconPapers)
JEL-codes: C22 C52 C65 (search for similar items in EconPapers)
Date: 2007-09-14
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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https://mpra.ub.uni-muenchen.de/11001/1/MPRA_paper_11001.pdf revised version (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:4917

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