Effects of intervaling on high-frequency realized higher-order moments

Abstract

In high-frequency finance, the statistical terms ‘realized skewness’ and ‘realized kurtosis’ refer to the realized third- and fourth-order moments of high-frequency returns data normalized (or divided) by ‘realized variance’. In particular, before any computations of these two normalized realized moments are carried out, one often predetermines the holding-interval and sampling-interval and thus implicitly influencing the actual magnitudes of the computed values of the normalized realized higher-order moments i.e. they have been found to be interval-variant. To-date, little theoretical or empirical studies have been undertaken in the high-frequency finance literature to properly investigate and understand the effects of these two types of intervalings on the behaviour of the ensuring measures of realized skewness and realized kurtosis. This paper fills this gap by theoretically and empirically analyzing as to why and how these two normalized realized higher-order moments of market returns are influenced by the selected holding-interval and sampling-interval. Using simulated and price index data from the G7 countries, we then proceed to illustrate via count-based signature plots, the theoretical and empirical relationships between the realized higher-order moments and the sampling-intervals and holding-intervals.