Generalized Variance: A Robust Estimator of Stock Price Volatility

R Gerlach, Maxwell Sutton and Andrey Vasnev

No 2015-02, Working Papers from University of Sydney Business School, Discipline of Business Analytics

Abstract: This paper proposes an ex-post volatility estimator, called generalized variance, that uses high frequency data to provide measurements robust to the idiosyncratic noise of stock markets caused by market microstructures. The new volatility estimator is analyzed theoretically, examined in a simulation study and evaluated empirically against the two currently dominant measures of daily volatility: realized volatility and realized range. The main finding is that generalized variance is robust to the presence of microstructures while delivering accuracy superior to realized volatility and realized range in several circumstances. The empirical study features Australian stocks from the ASX 20.

Keywords: Robust estimator; Volatility (search for similar items in EconPapers)
Date: 2015-04-30
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:syb:wpbsba:2123/13263

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