ON THE ROBUSTNESS OF RANGE-BASED VOLATILITY ESTIMATORS

<heading id="h1" level="1" implicit="yes" format="display">Abstract</heading>We empirically examine Parkinson's range-based volatility estimate in the federal funds market, which is unique because institutional regulations create a predictable pattern in interday volatility. We find that range-based volatility estimates and standard deviations produce the expected volatility pattern. We also find that at trading pressure points where microstructure noise should be greatest, range-based estimates are less than the standard deviations. Thus, we support the argument that range-based volatility estimates remove the upward bias created by microstructure noise. We find that the Parkinson method is the most efficient range-based volatility measure among a set of alternates in this market. Copyright (c) 2010 The Southern Finance Association and the Southwestern Finance Association.