B0614
Title: Estimation of the number of relevant factors from high-frequency data
Authors: Yuta Koike - University of Tokyo (Japan) [presenting]
Abstract: Factor models play an important role in modelling financial asset prices, both theoretically and practically. Traditionally, only "strong" factors that are correlated with all the assets under analysis have been considered, but in recent years, "weak" factors that are correlated with only some assets have attracted attention. It is discussed how to estimate the number of factors that drive the model, including "some" weak factors, from high-frequency data. In particular, a general setting in which the log price process is modelled as a semimartingale possibly with jumps is considered. Theoretically, the growth rate of the largest eigenvalue of the realized covariance matrix is relevant, and a new result is given from this perspective.
