TY - JOUR

T1 - Recovering the moments of information flow and normality of asset returns

AU - Izzeldin, Marwan

AU - Murphy, Anthony

PY - 2010/5/21

Y1 - 2010/5/21

N2 - We investigate the univariate procedure used by Ane and Geman (AG, 2000) to recover the moments of the information flow from high-frequency data, in a mixture of distributions model which generalizes the subordinated process in Clark (1973). We explain why the third and higher moments of the latent information flow cannot be accurately recovered using this procedure. We illustrate this using Monte Carlo simulations. We also show that, contrary to the claims in AG, returns conditioned on the re-centred number of trades are not approximately Gaussian. Finally, we consider the bivariate approach of Richardson and Smith (1994), inter alia, to recover the moments of information flow.

AB - We investigate the univariate procedure used by Ane and Geman (AG, 2000) to recover the moments of the information flow from high-frequency data, in a mixture of distributions model which generalizes the subordinated process in Clark (1973). We explain why the third and higher moments of the latent information flow cannot be accurately recovered using this procedure. We illustrate this using Monte Carlo simulations. We also show that, contrary to the claims in AG, returns conditioned on the re-centred number of trades are not approximately Gaussian. Finally, we consider the bivariate approach of Richardson and Smith (1994), inter alia, to recover the moments of information flow.

U2 - 10.1080/09603101003636212

DO - 10.1080/09603101003636212

M3 - Journal article

VL - 20

SP - 761

EP - 769

JO - Applied Financial Economics

JF - Applied Financial Economics

SN - 0960-3107

IS - 10

ER -