The dependence and risk spillover between crude oil market and China stock market: New evidence from a variational mode decomposition-based copula method

Li, Xiafei; Wei, Yu

doi:10.1016/j.eneco.2018.07.011

Cited by 107 publications

(45 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The result suggests that the Chinese A-share and B-share markets are both led by oil, corn and the Bitcoin markets in the long run process of adjusting to innovations in the fundamental values, during a relative tranquil period ahead of the COVID-19 outbreak. This result might be attributed to the important roles for crude oil and corn in the economic growth in China such that they are deemed to be key inputs for industrial products (see for example, Li & Wei, 2018 ; Luo & Ji, 2018 ).…”

Section: Resultsmentioning

confidence: 99%

The influence of the COVID-19 pandemic on asset-price discovery: Testing the case of Chinese informational asymmetry

Corbet

Hou

et al. 2020

International Review of Financial Analysis

View full text Add to dashboard Cite

The circumstances surrounding the outbreak of the COVID-19 pandemic have generated substantial international political strain as governments attempt to mitigate the widespread associated social and economic repercussions. One theory has focused on the potential for Chinese informational asymmetry. Using Chinese financial market data, we attempt to establish the scale and direction of information flows during multiple distinct phases of the development of the pandemic. Two specific results are identified. Firstly, the majority of domestically-traded Chinese stocks present evidence of significant information flows at a far earlier stage than internationally-traded comparatives, suggesting that domestic investors recognised the dangers associated with COVID-19 far in advance of the rest of the world. One potential explanation surrounds the view that the severity of domestically-reported Chinese news was not appropriately recognised by international investors. Secondly, while evidence of safe-haven and flight-to-safety behaviour is evident throughout traditional energy and precious metal markets, cryptocurrencies became informationally-synchronised with Chinese equity markets, indicating their use as an investor safe-haven. This is a particularly concerning outcome for international policy-maker and regulatory authorities due to the fragility of these developing markets.

show abstract

Section: Resultsmentioning

confidence: 99%

The influence of the COVID-19 pandemic on asset-price discovery: Testing the case of Chinese informational asymmetry

Corbet

Hou

et al. 2020

International Review of Financial Analysis

View full text Add to dashboard Cite

show abstract

“…Mensi et al (2017a), Miyazaki and Hamori (2013), Chkili (2016), Dar and Maitra (2017) ), between oil and stock markets (i.e. Awartani (2013), Ji (2018), Li and Wei (2018), Peng et al (2018), Shahzad (2018), Wang and Wu (2018), Abdullah et al (2016) etc. ), between oil and gold (Le and Chang (2012), Tiwari and Sahadudheen (2015), Shahbaz et al (2017) and Kumar (2017) ), and among oil, gold and stock markets (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…Since the financial globalization of commodity markets leads to a rise in integration across the energy, metal and other commodity markets, the investigation of the relationship between these markets by utilizing various kinds of econometrics methods attracts portfolio investors, consumers and producers, policy makers and speculative traders. Numerous investigations have been conducted into the relationship between gold and stock markets (i.e., Chkili, 2016; Dar & Maitra, 2017; Mensi, Al‐Yahyaee, & Kang, 2017a; Miyazaki & Hamori, 2013), between oil and stock markets (i.e., Abdullah, Saiti, & Masih, 2016; Awartani & Maghyereh, 2013; Balcilar & Ozdemir, 2013a; Ji, Liu, Zhao, & Fan, 2018; Li & Wei, 2018; Peng, Zhu, Guo, & Chen, 2018; Shahzad, Mensi, Hammoudeh, Rehman, & Al‐Yahyaee, 2018; Wang & Wu, 2018), between oil and gold (Balcilar, Ozdemir, & Shahbaz, 2018a; Balcilar, Ozdemir, Shahbaz, & Gunes, 2018b; Kumar, 2017; Le & Chang, 2012; Shahbaz, Balcilar, & Ozdemir, 2017; Tiwari & Sahadudheen, 2015), and among oil, gold and stock markets (i.e., Bouri, Jain, Biswal, & Roubaud, 2017; Lau, Vigne, Wang, & Yarovaya, 2017; Mensi, Hammoudeh, Al‐Jarrah, Sensoy, & Kang, 2017b; Raza, Shahzad, Tiwari, & Shahbaz, 2016; Tursoy & Faisal, 2018) using various kinds of econometric methods.…”

Section: Introductionmentioning

confidence: 99%

Dynamic return and volatility spillovers among S&P 500, crude oil, and gold

Balcılar

Özdemir

2019

Int. J Fin Econ

View full text Add to dashboard Cite

This paper examines the return and volatility spillover effects among S&P 500, crude oil and gold by employing the spillover index of Diebold and Yilmaz (2012). Monthly realized volatility and return series covering the period from January 1986 to August 2018 are used to examine the return and volatility spillovers. Our findings indicate a bi-directional return and volatility spillover among these assets. The full sample empirical evidence is consistent with the structure in which oil plays a central role in the information transmission mechanism. The role of oil and gold as a safe haven has changed over time in financial and non-financial economic turbulence time-span. Commodity market financialization has decreased the effectiveness of adding commodities to portfolios after 2002.

show abstract

“…This study found that the volatility transmission effect from S&P 500 to USO and BGF was significant both before and during the U.S.-China trade war, which is consistent with previous academic studies that show a strong correlation between oil prices and the equity markets during a long period. S&P 500 includes 26 stocks of energy companies, which comprise more than 4% of the index by market capitalization [76]. Therefore, when S&P 500 increases, the prices of the component stocks are likely to increase.…”

Section: Discussionmentioning

confidence: 99%

Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model

Lin

Chang

2020

Mathematics

View full text Add to dashboard Cite

Oil continues to be a major source of world energy, but oil prices and funds have experienced high volatility over the last decade. This study applies the generalized autoregressive conditional heteroskedasticity-mixed-data sampling (GARCH-MIDAS) model on data spanning 1 July 2014 to 30 April 2020 to examine volatility transmission from the equity, bulk shipping, commodity, currency, and crude oil markets to the United States Oil Fund (USO) and BlackRock World Energy Fund A2 (BGF). By dividing the sample into two subsamples, we find a significant volatility transmission from the equity market to the oil ETF and energy fund both before and after the 2018 U.S.–China trade war. The volatility transmission from the bulk shipping, commodity, and crude oil markets turns significant for the oil ETF and energy fund after the 2018 U.S.–China trade war, extending into the COVID-19 pandemic in early 2020. The results suggest that investors can use the equity market to predict the movement of oil and energy funds during both tranquil and turmoil periods. Moreover, investors can use bulk shipping, commodity, and crude oil markets in addition to the equity market to forecast oil and energy funds’ volatility during the turmoil periods. This paper benefits investors against the high volatility of the energy funds.

show abstract

The dependence and risk spillover between crude oil market and China stock market: New evidence from a variational mode decomposition-based copula method

Cited by 107 publications

References 54 publications

The influence of the COVID-19 pandemic on asset-price discovery: Testing the case of Chinese informational asymmetry

The influence of the COVID-19 pandemic on asset-price discovery: Testing the case of Chinese informational asymmetry

Dynamic return and volatility spillovers among S&P 500, crude oil, and gold

Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model

Contact Info

Product

Resources

About