On the gains of using high frequency data and higher moments in Portfolio Selection
In this paper we conduct an empirical analysis on the performance gains of using high frequency data in portfolio selection. Within a CRRA-utility maximization framework, we suggest the construction of two different portfolios: a low and a high frequency portfolios. For ten different risk aversion levels, we compare the performance of both portfolios in terms of several out-of-sample measures. Using data on fourteen stocks of the CAC 40 stock market index, from January 1999 to December 2003, we conclude that the “fight” is always “won” by the high frequency portfolio for all the considered performance evaluation measures.
portfolio selection, utility maximization criteria, higher moments, high frequency data, out-of-sample analysis