Functional data analysis for volatility

Hans-Georg Müller, Rituparna Sen and Ulrich Stadtmüller

Journal of Econometrics, 2011, vol. 165, issue 2, 233-245

Abstract: We introduce a functional volatility process for modeling volatility trajectories for high frequency observations in financial markets and describe functional representations and data-based recovery of the process from repeated observations. A study of its asymptotic properties, as the frequency of observed trades increases, is complemented by simulations and an application to the analysis of intra-day volatility patterns of the S&P 500 index. The proposed volatility model is found to be useful to identify recurring patterns of volatility and for successful prediction of future volatility, through the application of functional regression and prediction techniques.

Keywords: Diffusion model; Functional principal component; Functional regression; High frequency trading; Market returns; Prediction; Volatility process; Trajectories of volatility (search for similar items in EconPapers)
JEL-codes: C14 C51 C52 G12 G17 (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (26)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:165:y:2011:i:2:p:233-245

DOI: 10.1016/j.jeconom.2011.08.002

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