Quantile and asymmetric return connectedness among BRICS stock markets

Nyakurukwa, Kingstone; Seetharam, Yudhvir

doi:10.1016/j.jeca.2023.e00303

Cited by 19 publications

(3 citation statements)

References 43 publications

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“…Yet another group of empirical papers on stock market connectedness considered the religious dimension, that is, Islamic stocks with conventional (Bossman, Junior, & Tiwari, 2022;Hassan, et al 2022;Haddad et al 2020). Other studies have examined the dynamic connectedness of South African stocks with other countries' stocks (Nyakurukwa & Seetharam, 2023;Khalfaoui et al, 2023;Chang et al, 2023). The papers have reported different results regarding the net receivers and transmitters of stock returns.…”

Section: Literature Reviewmentioning

confidence: 99%

African stock markets’ connectedness: Quantile VAR approach

Yaya,

Adenikinju,

Olayinka

2024

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The present paper investigates African stock markets’ linkages by considering stocks in the continent’s largest economies, specifically Egypt, Kenya, Morocco, Nigeria, South Africa, and Tunisia. Using a dataset that spanned November 25, 2008, to September 18, 2023, the quantile connectedness approach of Chatziantoniou et al. (2021) is employed, and the results unfold these interesting dynamics of African market connectivity: (i) In the bearish market phase, South African stock dominated the entire network, transmitting shocks to the remaining stocks, while Moroccan and Kenyan stocks played similar role mildly. (ii) In the bullish market phase, Nigerian stock dominated the market as a major net transmitter of shock supported by South African and Kenyan stock markets. (iii), The Egyptian and Tunis stock markets are net shock receivers in both the bear and bull market phases. (iv), At the median quantile value, stocks become less riskier and the Kenyan stock market becomes the most vulnerable while Nigerian, Egyptian, and South African stock markets are influenced by other stock markets when markets are calm. (v), Though, African stocks are underperforming, interested portfolio managers will learn from the trading strategies to be adopted to maximize their returns. These findings will benefit portfolio managers, international stakeholders, and regulators.

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Section: Literature Reviewmentioning

confidence: 99%

African stock markets’ connectedness: Quantile VAR approach

Yaya,

Adenikinju,

Olayinka

2024

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“…With the deepening of economic globalization and the integration of financial markets, the connectedness across stock markets of various countries has significantly increased, which also exacerbates the transmission of risks across diverse economies (Nyakurukwa and Seetharam 2023;Balcilar et al 2023). The sharp fluctuations in one stock market can spread and amplify across markets, thereby engendering substantial volatility in the global stock market and potentially precipitating systemic financial crises on a global scale.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Spillover Effects in the Global Stock Market under Normal and Extreme Market Conditions

Liu,

Xu,

Xie

2024

IJFS

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Using the volatility spillover index method based on the quantile vector autoregression (QVAR) model, this paper systematically examines structural changes and corresponding spillover effects within 20 major stock markets under both extreme and normal market conditions, using data spanning from January 2005 to January 2023. The results show that, compared to the traditional volatility spillover index method, which focuses mainly on average spillover effects, the QVAR model-based spillover index better captures spillover effects under extreme and various market conditions among global stock markets. The connections between stock markets are closer in extreme market conditions. The total spillover index of major global stock markets significantly increases in extreme conditions compared to normal conditions. In extreme market conditions, inflow indices show varying degrees of increase, with emerging economy stock markets displaying more significant increases. The outflow indices exhibit heterogeneity; emerging economies show consistent increases, while developed economies show mixed changes.

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“…To address this limitation, Ando et al (2022) proposed the quantile vector autoregression (QVAR) model that allows the intensity and the pattern of spillovers to vary with small, large negative and large positive shocks. The quantile-based connectedness analysis has been recently used, among others, by Chatziantoniou et al (2021) on interest rate swaps; Naeem et al (2021) on Sukuk bonds; Liu et al ( 2021) on crude oil and stock markets, Ando et al (2022) on credit risk; Chen et al (2022a, 2022b) on energy, metals and carbon markets; Tiwari et al (2022) on energy and agricultural markets; Jena et al (2022) on world petroleum markets; Chang et al (2023) on crude oil and stock returns in BRICS countries; and Nyakurukwa and Seetharam (2023) on BRICS stock markets.…”

Section: Introductionmentioning

confidence: 99%

How does fear spread across asset classes? Evidence from quantile connectedness

Fousekis

2023

SEF

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Purpose This study aims to investigate the connectivity among four principal implied volatility (“fear”) markets in the USA. Design/methodology/approach The empirical analysis relies on daily data (“fear gauge indices”) for the period 2017–2023 and the quantile vector autoregressive (QVAR) approach that allows connectivity (that is, the network topology of interrelated markets) to be quantile-dependent and time-varying. Findings Extreme increases in fear are transmitted with higher intensity relative to extreme decreases in it. The implied volatility markets for gold and for stocks are the main risk connectors in the network and also net transmitters of shocks to the implied volatility markets for crude oil and for the euro-dollar exchange rate. Major events such as the COVID-19 pandemic and the war in Ukraine increase connectivity; this increase, however, is likely to be more pronounced at the median than the extremes of the joint distribution of the four fear indices. Originality/value This is the first work that uses the QVAR approach to implied volatility markets. The empirical results provide useful insights into how fear spreads across stock and commodities markets, something that is important for risk management, option pricing and forecasting.

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Quantile and asymmetric return connectedness among BRICS stock markets

Cited by 19 publications

References 43 publications

African stock markets’ connectedness: Quantile VAR approach

African stock markets’ connectedness: Quantile VAR approach

Comparative Analysis of Spillover Effects in the Global Stock Market under Normal and Extreme Market Conditions

How does fear spread across asset classes? Evidence from quantile connectedness

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