Abstract
In a global economy, shocks occurring in one market can spill over to other markets. This paper investigates the impact of oil shocks and stock market crashes on correlations between stock and oil markets. We test changes in correlations for different time scales with non-overlapping confidence intervals based on estimated wavelet correlations. Our results indicate that correlation between oil and stock markets tends to be stable in non-shock periods, around zero, but this changes during oil and financial shocks both at higher and lower frequencies. We find evidence of contagion, in particular during the 2008 and 2011 stock market falls. At low frequencies, the number of correlation breakdowns during oil shocks and stock market crashes is higher and they can be interpreted as shifts in market co-movements.
Highlights
The keystone of portfolio allocation as well as risk management decisions is the correlation structure of security returns
The wavelet methodology is appropriate because it allows decomposing a time series into different frequency components that extract the short-term behavior and the low-frequency components that capture the more long-term dynamics of a variable
Like Huang (2011) we find that different wavelet details can capture different information, but the four day frequency captures the majority of changes of correlation between oil and stock markets, while the one day frequency just points significant changes in correlations, for some stock markets, around the Kuwait war and the 2008 oil peak
Summary
The keystone of portfolio allocation as well as risk management decisions is the correlation structure of security returns. From works of Huang et al (1996); Chen et al (1986); Jones and Kaul (1996); Driesprong et al (2008); Ramos and Veiga (2012), the focus of our work is not on the direct impact of oil shocks in stocks market returns, but on the impact on the correlation structure between those markets. To analyze this issue, we follow the recent works that propose to use different frequency levels to distinguish between contagion and interdependence.
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