Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?

Abstract

This paper investigates the presence of time-varying causal linkages in mean and variance between oil price changes and stock returns for six major oil-importing countries (France, Germany, Italy, Spain, the UK and the US) in a multiscale framework that combines wavelet analysis and a modified version of the dynamic causality test of Lu et al. (2014). The results show significant bidirectional causal relations between oil and stock markets at the different time horizons for all countries. The causal links tend to be stronger at coarser scales and in periods of financial turmoil, mainly during the recent global financial and European sovereign debt crises. This evidence provides useful insights to participants in oil and stock markets and to policymakers.

Impact of international energy prices on China's industries

“…Since earlier works by Huang, Masulis, and Stoll () and Jones and Kaul (), considerable research using different methods and alternative data sources have generally agreed that higher international oil prices have a significant and negative impact on stock market returns (see e.g., in the US stock markets, Kang, Ratti, & Yoon, ; Kilian & Park, ; in the US and major European stock markets, Jammazi, Ferrer, Jareño, & Shahzad, ; in the US and major Asian stock markets, H. Ding, Kim, & Park, ; in Indian stock markets, Ghosh & Kanjilal, ; in China and Vietnam stock markets, Nguyen & Bhatti, ; and in emerging stock markets, Basher, Haug, & Sadorsky, ). These findings indicate that crude oil movements may have important implications for international stock markets in terms of portfolio risk management and asset allocations.…”

Reconstructing complex network for characterizing the time-varying causality evolution behavior of multivariate time series

“…The most existing works focus on the long-term causality between time series, ignoring the dynamic adjustment mechanism of short-term fluctuation toward to the long-term equilibrium 28 – 31 . Recently, some studies developed various time-varying causality methods to investigate the dynamical linkages between some economic variables, such as stock market and exchange rate, spot and futures crude oil prices, and crude oil and stock markets 32 – 36 . However, these researches still essentially analyzed the causalities between bivariate time series, lacking the systematic perspective to uncover the hidden dynamic interaction information between multivariate time series, and to understand the evolution mechanism of the complicated system.…”

A wavelet approach towards examining dynamic association, causality and spillovers

“…Overall findings reported that stock indices of Portugal, Italy and Spain had strong interaction during crisis. Jammazi et al (2017) investigated time varying nature of causal interaction of oil price change and stock returns of six oil importing countries through multiresolution analysis in wavelet decomposition framework and dynamic causality test. Significant causal links were discovered in short duration during the periods of financial crisis.…”

“…One set deals with exploring the interplay pattern in aggregate financial time series (Kaura et al, 2018;Singhal & Ghosh, 2016). The other segment furnishes a granular level inspection of interaction in short and long run through time series decomposition by various means (Jammazi et al, 2017;Liu et al, 2017), Sen and Datta Chaudhuri (2016)). The present study attempts to contribute to the second category of literature.…”