Quantile spillovers and connectedness analysis between oil and African stock markets

Mensi, Walid; Vo, Xuan Vinh; Kang, Sang Hoon

doi:10.1016/j.eap.2023.02.002

Cited by 19 publications

(2 citation statements)

References 75 publications

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“…The risk analysis shows that co-movements are persistent, and there is a dependence on portfolio risk in the BRICS economies and across markets during turmoil periods. Mensi et al (2023b) investigated how African stock markets and oil are linked in three different market conditions: bearish, normal, and bullish. Using the quantile connectedness approach, the findings reveal that during bearish market conditions, spillovers are more significant than in calm and bullish market conditions, and oil plays a vital role in transmitting these spillovers to African markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Dependence Structure and Time–Frequency Impact of Exchange Rates on Crude Oil and Stock Markets of BRICS Countries: Markov-Switching-Based Wavelet Analysis

Mudiangombe

Mwamba

2023

JRFM

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This paper used the Markov-switching (MS)-based wavelet analysis technique to study the dependence structure and the time–frequency impact of exchange rates on crude oil prices (West Texas Intermediate (WTI)) and stock returns. Daily data from 1 January 2005 to 1 March 2020 were collected for exchange rates, crude oil prices, and the BRICS stock market returns. The findings indicate that crude oil prices display higher volatility compared to stock returns and exchange rates. Furthermore, the wavelet analysis reveals consistent changes in the co-movement patterns of both volatility regimes, albeit with some variations in the time periods and frequency domains. The time–frequency dependence between Brazilian, Indian, and Chinese stock markets and crude oil is significantly influenced by exchange rates, which play a pivotal role in their co-movement in the medium term. The findings reveal that these three countries share economic interests, have strong economic ties and interdependencies, and may be motivated to cooperate during crisis periods. However, when it comes to Russia and South Africa (SA), exchange rates do not exhibit a long-term impact on the co-movement in time–frequency. Therefore, we recommend investors to look for investment opportunities that are less correlated with the co-moving markets.

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Section: Literature Reviewmentioning

confidence: 99%

Dependence Structure and Time–Frequency Impact of Exchange Rates on Crude Oil and Stock Markets of BRICS Countries: Markov-Switching-Based Wavelet Analysis

Mudiangombe

Mwamba

2023

JRFM

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“…The findings indicate that the return spillover between the markets under investigation is more prominent under bearish market conditions than during bullish conditions. Moreover, Mensi et al (2023) investigate the spillovers and connectedness of oil and African stock markets during bearish, normal, and bullish market conditions. By employing the quantile connectedness method, they reach evidence to support higher spillovers exist under bearish market conditions than in both tranquil and bullish market conditions.…”

Section: Introductionmentioning

confidence: 99%

Volatility Spillover in the Turkish Financial Market: A QVAR Analysis

Özdemir

2024

isarder

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Purpose –The volatility spillover is crucial matter for policy makers and portfolio managers to understand risk transmission between financial markets to understand where potential loss and risk comes from. In this research, it is aimed to investigate the tail risk spilloveramong the BIST-100 stock index, TR 10-year bonds, USD-TL exchange rate, gold futures, and Brent petroleum in Türkiye.Design/Methodology/Approach –The quantile vector autoregressive(QVAR) model, recommended by Ando et al., (2022),is used in this study. The QVAR model is proposed method in the literature to capture the tail risk spillovers from very low to very high volatility in financial markets. The data is weekly frequency and spans from January 28, 2010, to December 8, 2023. The weekly volatility data is obtained from a formula that utilize daily maximum and minimum prices as described in Diebold and Yilmaz (2012). Findings –The output of this study indicates that the volatility spilloversbetween related markets differs across different quantiles. Other results reveal that stock, bond, and currency markets are net risk spillovers during extremely low and moderately volatile periods, but gold and oil are net risk receivers. However, USD/TL is the only risk-transmitter in times of excessive volatility. Moreover, the time-varying spillover analysis shows that the total spillover index hit records during the COVID-19 outbreaks.Discussion –The output of this study confirms the findings of previous studies that find the spillover index does not remain constant over different quantiles. The output of this study provides crucial insights to finance authorities and investors on the nature of market risk and strategies for its management.

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The dependence and risk spillover between economic uncertainties and the crude oil market: new evidence from a Copula-CoVaR approach incorporating the decomposition technique

Zhang,

Tang

2023

Environ Sci Pollut Res

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Quantile spillovers and connectedness analysis between oil and African stock markets

Cited by 19 publications

References 75 publications

Dependence Structure and Time–Frequency Impact of Exchange Rates on Crude Oil and Stock Markets of BRICS Countries: Markov-Switching-Based Wavelet Analysis

Dependence Structure and Time–Frequency Impact of Exchange Rates on Crude Oil and Stock Markets of BRICS Countries: Markov-Switching-Based Wavelet Analysis

Volatility Spillover in the Turkish Financial Market: A QVAR Analysis

The dependence and risk spillover between economic uncertainties and the crude oil market: new evidence from a Copula-CoVaR approach incorporating the decomposition technique

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