Oil shock transmission to stock market returns: Wavelet-multivariate markov switching GARCH approach

被引:0
|
作者
Jammazi, Rania [1 ]
机构
[1] Jammazi, Rania
来源
Jammazi, Rania (jamrania2@yahoo.fr) | 1600年 / Springer Verlag卷 / 54期
关键词
Crude oil market - Developed countries - Government agencies - International crisis - Market instability - Oil price shocks - Shock transmission - Spillover effects;
D O I
10.1007/978-3-642-55382-0_4
中图分类号
学科分类号
摘要
Our understanding of the nature of crude oil price shocks and their effects on the stock market returns has evolved noticeably in recent years. Evidence of spillover effects between several kinds of markets has been widely discussed around the globe, and yet the transmission of shocks between crude oil market and stock market returns has received little attention. Extending earlier work in the literature, we use data on monthly crude oil returns and stock market returns of five developed countries (USA, UK, Japan, Germany and Canada) to investigate two issues that have been at the centre of recent debates on the effect of crude oil shocks on the stock market returns. First, we analyse whether shocks and or volatility emanating from two major crude oil markets are transmitted to the equity markets. We do this by decomposing monthly real crude oil prices and analysing the effect of the smooth part on the degree of the stock market instability. The motivation behind the use of this method is that noises can affect the quality of the shock and thus increase erroneous results of the shock transmission to the stock market. Second, under the hypothesis of common increased volatility, we investigate whether these states happen around the identified international crises. In doing so, flexible model is implemented involving the dynamic properties of the Trivariate Markov switching GARCH model and the recent Harr A trous wavelet decomposition, in order to achieve a strong prediction of the abovementioned situations The proposed model is able to circumvent the path dependency problem that can affect the prediction's robustness and also provides useful information for investors and government agencies that have largely based their views on the notion that crude oil markets negatively affect stock market returns. Indeed, the results show that the A Haar Trous Wavelet decomposition method appears to be an important step toward improving accuracy of the smooth signal in detecting key real crude oil volatility features. Additionally, apart from UK and Japanese cases, the responses of the stock market to an oil shock depend on the geographic area for the main source of supply whether it is from the North Sea or from North America (as two oil benchmarks are used, WTI and Brent respectively). © Springer-Verlag Berlin Heidelberg 2014.
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页码:71 / 111
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