2018
DOI: 10.1016/j.bir.2018.07.001
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Causality and contagion in emerging stock markets

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Cited by 13 publications
(8 citation statements)
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“…Analysis of causality holds great importance in studying financial market behaviour, and linear Granger causality is most commonly used to understand causal behaviour. However, attempts to understand behaviour and directional causality have motivated researchers to search for more efficient and global approaches (see, for example, Abdennadher and Hellara, 2018 , Agbloyor et al, 2013 , Comincioli, 1996 , Stavroglou et al, 2019 ). However, the credit for testing causality goes to Granger (1969) ; the Granger causality test (GC) is one of the most popularly used in the financial literature to evaluate the bidirectional relationship between variables.…”
Section: Methodsmentioning
confidence: 99%
“…Analysis of causality holds great importance in studying financial market behaviour, and linear Granger causality is most commonly used to understand causal behaviour. However, attempts to understand behaviour and directional causality have motivated researchers to search for more efficient and global approaches (see, for example, Abdennadher and Hellara, 2018 , Agbloyor et al, 2013 , Comincioli, 1996 , Stavroglou et al, 2019 ). However, the credit for testing causality goes to Granger (1969) ; the Granger causality test (GC) is one of the most popularly used in the financial literature to evaluate the bidirectional relationship between variables.…”
Section: Methodsmentioning
confidence: 99%
“…A later study by Abdennadher and Hellara (2018) found that the global financial crisis reinforced interdependencies between financial markets. They concluded that additional linkages during crisis periods in excess of those that arise during noncrisis periods contributes significantly in amplifying the international transmission of volatility and the risk of contagion.…”
Section: Literature Reviewmentioning
confidence: 97%
“…Numerous studies have been conducted to establish the nature of interdependence among international stock markets. This growing literature is partly attributed to financial market turbulence, which transmits shocks and volatility across regional and global markets, and partly to identify veritable sources for hedging risk and portfolio diversification (see, e.g., Abdennadher & Hellara, 2018; Amira et al, 2011; Hung, 2019; Solnik et al, 1996; Yépez, 2020). Although the majority of these studies focused on developed and emerging markets, there are also studies conducted to measure interdependence and linkages among Africa markets as well as between Africa and developed markets (see Agyei‐Ampomah, 2011; Collins & Biekpe, 2003; Panda et al, 2019).…”
Section: Introductionmentioning
confidence: 99%
“…For example, Arestis, Demetriades, and Luintel (2001) and Kumari and Mahakud (2015) link volatility to uncertainty in macroeconomic conditions whereas Kumari and Mahakud (2016) and Rehman (2013), Orlitzky (2013) remark that it is driven by investors' psychology and sentiments. Other studies (e.g., Abdennadher & Hellara, 2018;Asaturov, Teplova, & Hartwell, 2015;Natarajan, Singh, & Priya, 2014) attribute volatility to contagion or spillover effects.…”
Section: Introductionmentioning
confidence: 99%
“…Sosa and Ortiz (2017) study of stock exchanges in Canada, the U.S., and Mexico find that the Canadian stock market exhibited a high level of volatility, however, the inference in Mallikarjuna and Rao (2019) shows that the US has a higher level of volatility than Canada. It is conspicuous that several studies (e.g., Mallikarjuna & Rao, 2019;Abdennadher & Hellara, 2018;Kumari & Mahakud, 2016;Engle, Ghysels, & Sohn, 2013;Mala & Reddy, 2007) rely on AutoRegressive Conditional Heteroskedasticity (ARCH) and Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models or a variation of it, some (e.g., Alqahtani, Wither, Dong, & Goodwin, 2020;Khalid & Khan, 2017) favour other models, which may have contributed to the observation of conflicting outcomes. In addition, differences in approach adopted, data type, and study period may have elicited inconsistencies in findings.…”
Section: Introductionmentioning
confidence: 99%