Abstract

The relationship between oil prices and stocks is an important issue for portfolio selection and risk management. This article proposes a mixed frequency data sampling copula model with explanatory variables that incorporates low-frequency explanatory variables into a high-frequency dynamic copula model. It enables us to investigate the impacts of economic factors on the relationship between oil and stocks. It is found that the dependence of oil and stock markets is influenced by aggregate demand and stock-specific negative news. The impact of aggregate demand lasts for two years, while the impact of stock-specific news lasts for one quarter.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://dbpia.nl.go.kr/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
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