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Estimating Daily Volatility From Intraday Data

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  • Bollen, Bernard
  • Kofman, Paul

Abstract

This study proposes a new approach to the estimation of daily volatility. This approach is efficient (in the sense of using all available intraday price data) and unbiased (in the sense of accounting for the high levels of autocorrelation found in intraday price data). Empirical analysis of this new estimator on All Ordinaries Index Futures shows that it is less biased and more efficient than traditional volatility estimators. Furthermore this new approach confirms the GARCH(1,1) specification of the time series behaviour of daily volatility; namely that daily volatility follows an ARMA(1,1) process through time.

Suggested Citation

  • Bollen, Bernard & Kofman, Paul, "undated". "Estimating Daily Volatility From Intraday Data," Department of Econometrics and Business Statistics Working Papers 267915, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:ags:monebs:267915
    DOI: 10.22004/ag.econ.267915
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