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The economics of data: Using simple model-free volatility in a high-frequency world

John Garvey and Liam Gallagher ()

The North American Journal of Economics and Finance, 2013, vol. 26, issue C, 370-379

Abstract: This paper examines the practical implications of using high-frequency data in a fast and frugal manner. It recognises the continued widespread application of model free approaches within many trading and risk management functions. Our analysis of the relative characteristics of four model-free volatility estimates is framed around their relative long memory effects as measured by the feasible exact local Whittle estimator. For a cross-section of sixteen FTSE-100 stocks, for the period 1997–2007, we show that 5-min realized volatility exhibits a higher level of volatility persistence than approaches that use data in a sparse way (close-to-close volatility, high-low volatility and Yang & Zhang volatility). This observation is a useful decision-tool for a trading and risk management decisions that are undertaken in a time-constrained task environment. It recommends that the use of sparse data (open, high, low and closing price observations) requires trader intuition and judgement to build long-memory effects into their pricing.

Keywords: Economics of information; Model free volatility; High frequency data; Long memory effects (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1016/j.najef.2013.02.011

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