Mardi | 2015-04-23
Sully 4, 16h-17h20

Jean-Yves GNABO – Lyudmyla HVOZDYKZ – J erôme LAHAYE

This paper studies bivariate tail comovements on fi nancial markets that are of crucial importance for the world economy: the S&P 500, US bonds, and currencies. We propose to study that form of dependence under the lens of cojump identi cation in a bivariate Brownian semimartingale with idiosyncratic jumps, as well as cojumps. Whereas univariate jump identi cation has been widely studied in the high-frequency data literature, the multivariate literature on cojump identi cation is more recent and scarcer. Cojump identi cation is of interest, as it may identify comovements which are not trivially visible in a univariate setting. That is, price changes can be small relative to local variation, but still abnormal relative to local covariation. This paper investigates how simple parametric bootstrapping of the product of assets’ intraday returns can help detect cojumps in a multivariate Brownian semi-martingale with both idiosyncratic jumps and cojumps. In particular, we investigate how to disentangle idiosyncratic jumps from common jumps at an intraday level for pairs of assets. The approach is flexible, trivial to implement, and yields good power properties. It allows to shed new light on extreme dependence at the world economy level.