Effect of jumps on causation patterns: an international investigation. (2nd January 2014) - Javed, Farrukh
In this paper, we empirically investigate and discuss the effects of jumps in data on causation pattern both in mean and variance. Our data consist of daily stock returns of four countries: France, Sweden, the UK and Finland. A test proposed by Cheung and Ng (1996) and Hong (2001) is applied for testing volatility spillover. We find significant evidence of jump spillover. It is shown that the presence of jump affects the transmission of information between two sets of series. Moreover, it is found that the choice of an appropriate model is essential for understanding the real pattern of transmission.