Estimating integrated volatility using absolute high-frequency returns

Carla Ysusi

International Journal of Monetary Economics and Finance, 2008, vol. 1, issue 2, 177-200

Abstract: When high-frequency data is available, in the context of a stochastic volatility model, realised absolute variation can estimate integrated spot volatility. A central limit theory enables us to do filtering and smoothing using model-based and model-free approaches in order to improve the precision of these estimators. Although the absolute values are empirically attractive as they are less sensitive to possible large movements in high-frequency data, realised absolute variation does not estimate integrated variance. Some problems arise when using a finite number of intra-day observations, as explained here.

Keywords: quadratic variation; absolute variation; stochastic volatility models; semimartingale; high-frequency data; state-space representation; Kalman filter; spot volatility; central limit theory. (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmefi:v:1:y:2008:i:2:p:177-200

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