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SUMMARY:A Hausman Test for the Presence of Market Microstructure Noise in 
 High Frequency Data - Yacine Ait-Sahalia\,  Otto A. Hack 1903 Professor of
  Finance and Economics 
DTSTART:20160512T120000Z
DTEND:20160512T130000Z
UID:TALK59231@talks.cam.ac.uk
CONTACT:Cerf Admin
DESCRIPTION:We develop tests that help assess whether a high frequency dat
 a sample can be treated as reasonably free of market microstructure noise 
 at a given sampling frequency for the purpose of implementing high frequen
 cy volatility and other estimators. The tests are based on the Hausman pri
 nciple of comparing two estimators\, one that is efficient but not robust 
 to the deviation being tested\, and one that is robust but not as efficien
 t. We investigate the asymptotic properties of the test statistic in a gen
 eral nonparametric setting\, and compare it with several alternatives that
  are also developed in the paper. Empirically\, we find that improvements 
 in stock market liquidity over the past decade have increased the frequenc
 y at which simple\, uncorrected\, volatility estimators can be safely empl
 oyed.
LOCATION:Room W4.03 Judge Business School
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