Testing Contagion in Multivariate Financial Time Series based on Residual and Recurrence Times

Financial contagion refers to the transmission of a financial shock in one entity to other interdependent entities. While the study of causes and prevention of contagion is very popular among economists, there are not many quantitative studies on how to detect (hypothesis testing) and measure (estimate) contagion. In this dissertation thesis, a new idea of Residual and Recurrence Times method of high or low values for multivariate time series is shown. With financial contagion, the distributions of residual and recurrence times are not the same, where the equality of two distributions is examined by permutation test. When compared to some methods in multivariate extreme value theory, this new method does not need the IID assumption and can handle the situation where the extremes for different components do not occur at the same time.