Event Time

Abstract

Investors take for granted that returns are recorded in units of time, such as days, months, or years. Yet some time periods include unusual events that reasonably cause asset prices to change, whereas other periods are relatively free of unusual events, in which case returns mostly reflect noise. Based on insights from information
theory, the authors rescale time into event units so that each return is related to a common degree of event intensity. Their analysis reveals that when returns are measured in event units, their distributions are more normal and their co-occurrences are more stable, which enables analysts to form more reliable inferences.

Keywords: Calendar time, Co-occurrence, Event intensity, Event time, Information theory, Informativeness, Kullback-Leibler divergence, Kurtosis, Mahalanobis distance, Normal divergence, Pearson correlation, Relative entropy, z-score

JEL Classification: C1, C13, C40, C46, C58, C60, C63, C80, G10, G11