What Affects the Relationship Between Oil Prices and the U.S. Stock Market? A Mixed-Data Sampling Copula Approach

Bu, Ruijun; Chen, Qiang; Gong, Yuting

doi:10.1093/jjfinec/nbz043

Cited by 9 publications

(6 citation statements)

References 37 publications

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“…In addition, findings of the unadjusted and adjusted SRs provide market participants with instructive insights into cross‐market investments. The adjusted annualized SRs of the cross‐sector FFA portfolios could reach around 1.9734 over the period January 4, 2016 to December 31, 2019, which are generally higher than those of international stock portfolios (around 0.7–1 in Jondeau & Rockinger, 2012 and Miralles‐Marcelo et al, 2015) and commodity portfolios (around 1–1.5 in Lombardi & Ravazzolo, 2016 and Y. Gong et al, 2022).…”

Section: Resultsmentioning

confidence: 93%

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Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula

Gong

Wang

Zhu

et al. 2022

Journal of Futures Markets

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We form portfolios consisting of diverse quarterly forward freight agreement (FFA) contracts to maximize the market participant's expected utility. The empirical findings indicate that individual FFA returns display clear autocorrelation, seasonality, fat tail, and heteroscedasticity. The multivariate positively skewed t copula is suggested for constructing maximum utility FFA portfolios, implying that the constituent FFA returns exhibit higher correlations when they rise together. The out-of-sample trading strategy performance metrics and various robustness checks further indicate that the aforementioned copula performs best and robustly for all portfolios. These findings provide profound methodological and managerial implications for market participants to improve risk management.

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Section: Resultsmentioning

confidence: 93%

“…X. Gong and Lu (2016) discuss the spillover effect by applying the volatility spillover multivariate stochastic volatility (VS-MSV) model and Sun et al (2019) do so by adopting the dynamic conditional correlation-multivariate GARCH (DCC-MGARCH) model.…”

Section: Research Gapsmentioning

confidence: 99%

Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula

Gong

Wang

Zhu

et al. 2022

Journal of Futures Markets

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“…Bahmani-Oskooee et al (2019) utilized an asymmetric Granger causality test and failed to find a significant long-run causal relationship between oil prices and stock returns of nine different sectors of the US economy. Alternatively, Bu et al (2020) employed the copula-MIDAS-X model to capture low-frequency to high-frequency data to examine the relationship between oil prices and the US stock market (S&P 500 index). Their results show that the relationship is asymmetric, and the dependence on oil and stock markets is influenced by aggregate demand and stock-specific negative news.…”

Section: Oil Price and Stock Market Nexusmentioning

confidence: 99%

A Markov Switching Approach in Assessing Oil Price and Stock Market Nexus in the Last Decade: The Impact of the COVID-19 Pandemic

2023

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We revisit the oil price and stock market nexus by considering the impact of major economic shocks in the post-global financial crisis (GFC) scenario. Our breakpoint unit root test and Markov switching regression (MRS) analyses using West Texas Intermediate (WTI) oil price and Standard & Poor’s 500 (S&P 500) market index show that among the major economic events, the recent coronavirus (COVID-19) pandemic is the most significant contributor to market volatilities. Furthermore, our MRS results show that the relationship between oil price and the stock market is regime-dependent; the stock market experiences substantial and positive shocks in a volatile oil price regime. Our results provide valuable insights to investors and policymakers regarding risk management and financial market stability during economic crisis periods, specifically during the COVID-19 pandemic.

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“…Recently, several scholars incorporated low-frequency macrovariables into the Copula framework to explore if macrofactors have an impact on the dependence structure between financial markets. In particular, Gong et al [23,24] developed a Copula-mixed-data sampling (Copula-MIDAS) model to investigate the impact of macrofundamentals, market uncertainty, and liquidity on the interdependence of Chinese stock and bond markets. Jiang et al [25] constructed a TVM-Copula-MIDAS model to explore the interdependence between Chinese stock, bond, and fund markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Economic Policy Uncertainty and Conditional Dependence between China and U.S. Stock Markets

Zhang

et al. 2022

Complexity

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In this paper, we investigate the impact of economic policy uncertainty (EPU) on the conditional dependence between China and U.S. stock markets by employing the Copula-mixed-data sampling (Copula-MIDAS) framework. In the case of EPU, we consider the global EPU (GEPU), the American EPU (AEPU), and the China EPU (CEPU). The empirical analysis based on the Shanghai Stock Exchange Composite (SSEC) index in China and the S&P 500 index in the U.S. shows that the tail dependence between China and U.S. stock markets is symmetrical, and the t Copula outperforms alternative Copulas in terms of in-sample goodness of fit. In particular, we find that the t Copula-MIDAS model with EPU dominates the traditional time-varying t Copula in terms of in-sample fitting. Moreover, we observe that both the GEPU and AEPU have a significantly positive impact on the conditional dependence between China and U.S. stock markets, whereas CEPU has no significant impact. The tail dependence between China and U.S. stock markets exhibits an increasing trend, particularly in the recent years.

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What Affects the Relationship Between Oil Prices and the U.S. Stock Market? A Mixed-Data Sampling Copula Approach

Cited by 9 publications

References 37 publications

Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula

Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula

A Markov Switching Approach in Assessing Oil Price and Stock Market Nexus in the Last Decade: The Impact of the COVID-19 Pandemic

Economic Policy Uncertainty and Conditional Dependence between China and U.S. Stock Markets

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