Volatility return intervals analysis of the Japanese market

TL;DR

This paper analyzes the scaling and memory effects in return intervals of price volatility in the Japanese stock market, revealing consistent statistical features across different periods and data frequencies.

Contribution

It demonstrates that return interval distributions follow a universal scaling function and exhibit memory effects, extending previous market studies to the Japanese market with pre- and post-crash comparisons.

Findings

Return intervals follow a scaling function based on the ratio to the mean

Memory effects show large (small) intervals tend to follow large (small) ones

Similar statistical features are observed before and after the 1989 crash

Abstract

We investigate scaling and memory effects in return intervals between price volatilities above a certain threshold $q$ for the Japanese stock market using daily and intraday data sets. We find that the distribution of return intervals can be approximated by a scaling function that depends only on the ratio between the return interval $\tau$ and its mean $<\tau>$. We also find memory effects such that a large (or small) return interval follows a large (or small) interval by investigating the conditional distribution and mean return interval. The results are similar to previous studies of other markets and indicate that similar statistical features appear in different financial markets. We also compare our results between the period before and after the big crash at the end of 1989. We find that scaling and memory effects of the return intervals show similar features although the statistical properties of the returns are different.