Extremal dependence tests for contagion

Abstract

A new test for financial market contagion based on changes in extremal dependence defined as co-kurtosis and co-volatility is developed to identify the propagation mechanism of shocks across international financial markets. The proposed approach captures changes in various aspects of the asset return relationships such as crossmarket mean and skewness (co-kurtosis) as well as cross-market volatilities (covolatility). Monte Carlo experiments show that the tests perform well except for when crisis periods are short in duration. Small crisis sample critical values are calculated for use in this case. In an empirical application involving the global financial crisis of 2008-09, the results show that significant contagion effects are widespread from the US banking sector to global equity markets and banking sectors through either the cokurtosis or the co-volatility channels, reinforcing that higher order moments matter during crises.

Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

“…There are some tests for contagion, for example, the test developed by Fry et al (2010), and Fry-McKibbin and Hsiao (2015). The tests can be used for big data, and also for large data sets that might not be characterized as big data.…”

The Impact of Financial Crisis of 2007 to 14 on the Australian Financial Firms

“…The crisis source is assumed to be the US banking sector which is calculated as the US Bank sector index [7]. The Australian daily stock price index and the US banking sector index were collected during the period of January 1 st , 2005 to December 31 st , 2014 so as to measure the change of the relationship between two assets markets.…”

“…The joint test of contagion developed by [7] and [8] is based on identifying significant changes in correlation, coskewness, co-kurtosis and co-volatility together between a crisis period and a non-crisis period in the meantime. The noncrisis period is denoted as and during-crisis period as .…”

“…The definition of contagion phenomenon: a significant change in cross-market joint comoment after a financial shock [8] has been applied. The paper measures whether there was such a financial contagion from the US to Australian financial firms during the financial crisis during the period of 2007-2014 which consists of the US subprime mortgage crisis, global financial crisis (also called the Great Recession) and the European debt crisis by using the method of joint test, which consists of linear and higher order co-moments such as: cross-market correlation [3], cross-market skewness (or co-skewness: the relationship between the asset return in market i and the return volatility in market j) [5], cross-market kurtosis (or co-kurtosis: the relationship between the asset return in market i and return skewness in market j) and cross-market volatility (or co-volatility: the relationship between the return volatility of markets i and j) [7]. The higher order co-moments are derived by assuming the distribution of markets stock return as a bivariate normal distribution with the higher order moments and co-moments, and the normality is certified by calculating the Lagrange Multiplier statistic.…”

“…[2] Focused on the non-linear relationship. A class of new testing method was developed by [5], [6], [7] and [8] which used higher order comoments to test the properties of the distributions of assets return.…”