TY - JOUR
T1 - Disentangling Sources of High Frequency Market Microstructure Noise
AU - Clinet, Simon
AU - Potiron, Yoann
N1 - Publisher Copyright:
© 2019 American Statistical Association.
PY - 2021
Y1 - 2021
N2 - Employing tick-by-tick maximum likelihood estimation on several leading models from the financial economics literature, we find that the market microstructure noise is mostly explained by a linear model where the trade direction, that is, whether the trade is buyer or seller initiated, is multiplied by the dynamic quoted bid-ask spread. Although reasonably stable intraday, this model manifests variability across days and stocks. Among different observable high frequency financial characteristics of the underlying stocks, this variability is best explained by the tick-to-spread ratio, implying that discreteness is the first residual source of noise. We determine the bid-ask bounce effect as the next source of noise.
AB - Employing tick-by-tick maximum likelihood estimation on several leading models from the financial economics literature, we find that the market microstructure noise is mostly explained by a linear model where the trade direction, that is, whether the trade is buyer or seller initiated, is multiplied by the dynamic quoted bid-ask spread. Although reasonably stable intraday, this model manifests variability across days and stocks. Among different observable high frequency financial characteristics of the underlying stocks, this variability is best explained by the tick-to-spread ratio, implying that discreteness is the first residual source of noise. We determine the bid-ask bounce effect as the next source of noise.
KW - Efficient price
KW - High frequency data
KW - Market microstructure noise
KW - Mid price
KW - Trade direction
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U2 - 10.1080/07350015.2019.1617158
DO - 10.1080/07350015.2019.1617158
M3 - Article
AN - SCOPUS:85068141721
SN - 0735-0015
VL - 39
SP - 18
EP - 39
JO - Journal of Business and Economic Statistics
JF - Journal of Business and Economic Statistics
IS - 1
ER -