The Role of Dynamic Specification in Forecasting Volatility in the Presence of Jumps and Noisy High-Frequency Data

Rasmus Varneskov ()
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Rasmus Varneskov: School of Economics and Management, Aarhus University and CREATES, Postal: Bartholins Allé 10, Aarhus, Denmark

CREATES Research Papers from School of Economics and Management, University of Aarhus

Abstract: This paper considers the performance of di erent long-memory dynamic models when forecasting volatility in the stock market using implied volatility as an exogenous variable in the information set. Observed volatility is sep- arated into its continuous and jump components in a framework that allows for consistent estimation in the presence of market microstructure noise. A comparison between a class of HAR- and ARFIMA models is facilitated on the basis of out-of-sample forecasting performance. Implied volatility conveys incremental information about future volatility in both specifications, improv- ing performance both in- and out-of-sample for all models. Furthermore, the ARFIMA class of models dominates the HAR speci cations in terms of out-of- sample performance both with and without implied volatility in the information set. A vectorized ARFIMA (vecARFIMA) model is introduced to control for possible endogeneity issues. This model is compared to a vecHAR speci cation, re-enforcing the results from the single equation framework.

Keywords: ARFIMA; HAR; Implied Volatility; Jumps; Market Microstructure Noise; VecARFIMA; Volatility Forecasting (search for similar items in EconPapers)
JEL-codes: C14 C22 C32 C53 G10 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-mst
Date: 2010-08-19
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Persistent link: http://EconPapers.repec.org/RePEc:aah:create:2010-39

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