Price Transmissions and Market Risk in Financial Markets

Abstract

Decomposing a time series into its high- and low-frequency components has been the object of study in various fields of knowledge since the 19th century. Such decomposition has gained ground in the finance field in recent years motivated by the existence of heterogeneous investment horizons. A mathematical tool developed in the early 1990’s, denominated as wavelets, has become increasingly popular to characterize the short- and long-term behavior of financial indices. In particular, in an article published in 2005, Connor and Rossiter provide an appealing interpretation of wavelet analysis by pointing out that long-term traders focus on price fundamentals which drive overall trends, while short-term traders react to incoming information within a short-term horizon. Such heterogeneity, in Connor and Rossiter’s view, can be modeled by means of wavelet analysis.

In this article, we illustrate the usefulness of wavelets to gauging asset return co-movement, structural variance shifts, and the overall risk of a portfolio as measured by its value at risk. Specifically, we concentrate on the nine SPDR sectors––i.e., Consumer Discretionary, Consumer Staples, Energy, Financial, Health Care, Industrial, Materials, Technology, and Utilities––along the period 1999-2007.