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Information in daily data volatility measurements

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  • Hiroyuki Kawakatsu

Abstract

This paper evaluates the information content in daily volatility measures that utilize OHLC (Open‐High‐Low‐Close) price data. An encompassing regression framework is used to evaluate the absolute and relative information contain in such measures. 2‐step GMM (generalized method of moments) estimates using two sets of instruments are used to address potential bias from measurement errors. The evidence using S&P 500 index data suggest that volatility measures that use OHLC data encompass those based only on close‐to‐close returns or high‐minus‐low ranges. However, the proposed instruments do not all pass statistical tests of instrument validity and the identification robust confidence set can be quite large.

Suggested Citation

  • Hiroyuki Kawakatsu, 2021. "Information in daily data volatility measurements," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1642-1656, April.
    • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:2:p:1642-1656
    DOI: 10.1002/ijfe.1868
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    References listed on IDEAS

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