Market-wide price co-movement around crashes in the Tokyo Stock Exchange

TL;DR

This study analyzes high-frequency stock return data from the Tokyo Stock Exchange during 2007-2009 to understand market-wide co-movement patterns around crashes, revealing long-range correlations and herding behavior before declines.

Contribution

It introduces a detailed analysis of principal components and multi-fractal modeling to identify early signs of market-wide herding prior to crashes in the Tokyo Stock Exchange.

Findings

Long-range auto-correlation of the maximum eigenvalue up to a couple of months.

Strong correlation between eigenvalue and index returns.

Parameter growth in the multi-fractal model before large intraday declines.

Abstract

As described in this paper, we study market-wide price co-movements around crashes by analyzing a dataset of high-frequency stock returns of the constituent issues of Nikkei 225 Index listed on the Tokyo Stock Exchange for the three years during 2007--2009. Results of day-to-day principal component analysis of the time series sampled at the 1 min time interval during the continuous auction of the daytime reveal the long range up to a couple of months significant auto-correlation of the maximum eigenvalue of the correlation matrix, which express the intensity of market-wide co-movement of stock prices. It also strongly correlates with the open-to-close intraday return and daily return of Nikkei 225 Index. We also study the market mode, which is the first principal component corresponding to the maximum eigenvalue, in the framework of Multi-fractal random walk model. The parameter of the model estimated in a sliding time window, which describes the covariance of the logarithm of the stochastic volatility, grows before almost all large intraday price declines of less than -5%. This phenomenon signifies the upwelling of the market-wide collective behavior before the crash, which might reflect a herding of market participants.