Asymmetric Volatility Spillover between Stock Market and Foreign Exchange Market: Instances from Indian Market from Pre-, during and Post- Subprime Crisis Periods
Abstract:Modern businesses are so inter-twined that a cause in one market affects other markets throughout the Globe. The 2008 subprime crisis is one of such evidences of inter-linkage of global markets. Such type of event motivates many studies to analyse the transmission of volatility from one market to another market. The study aims to analyse the volatility spillover effect between CNX Nifty and exchange rates covering for three different currencies, that is, USD, GBP and yen. GARCH (1,1) and EGARCH (1,1) have been… Show more
“…In contrast to Dahir et al (2018), they find unidirectional spillover effects from the exchange rates to stock returns in the short-run for all BRICS and shocks to the US S&P 500 influence all BRICS stock markets except India. The results are similar to those of Bal, Manglani and Deo (2018), who used the GARCH and EGARCH and found a unidirectional effect from the exchange rate market to the stock market for India. Using Markov-switching (MS) VAR models, Chkili and Nguyen (2014)…”
Orientation: This study investigated the relationship between the equity markets and foreign exchange markets in Brazil, Russia, India, China and South Africa (BRICS).Research purpose: This study examined the financial connectedness through volatility spillovers and co-movements among equity and foreign exchange markets in the BRICS countries to better understand market interdependencies.Motivation for the study: The literature mainly focused on volatility transmission from developed countries.Research approach: This research, used the Diebold and Yilmaz spillover index approach (DY index). The DY index is based on variance decompositions (VD) and impulse response functions that use a vector autoregressive (VAR) modelling framework. The study period was from 02 January 1997 to 31 December 2018.Main findings: Shocks from the equity markets dominate the foreign exchange markets, while foreign exchange markets dominate their equity markets at an individual level. There are interdependencies between BRICS equity markets and foreign exchange markets, except for China, whose markets are relatively isolated from other BRICS markets. Brazil is the largest contributor of volatility spillovers to other BRICS markets. The South African rand is the most integrated within BRICS.Practical implications: Foreign exchange markets provided better diversification opportunities. Significant increases in volatility spillovers associated with turmoil periods in domestic and global markets provide evidence for contagion effects in BRICS markets.Contribution: The current account (flow-oriented model) is crucial in exchange rate determination at the individual country level. In contrast, the capital account (stock-oriented model) is a significant factor in exchange rate determinations at an aggregate level.
“…In contrast to Dahir et al (2018), they find unidirectional spillover effects from the exchange rates to stock returns in the short-run for all BRICS and shocks to the US S&P 500 influence all BRICS stock markets except India. The results are similar to those of Bal, Manglani and Deo (2018), who used the GARCH and EGARCH and found a unidirectional effect from the exchange rate market to the stock market for India. Using Markov-switching (MS) VAR models, Chkili and Nguyen (2014)…”
Orientation: This study investigated the relationship between the equity markets and foreign exchange markets in Brazil, Russia, India, China and South Africa (BRICS).Research purpose: This study examined the financial connectedness through volatility spillovers and co-movements among equity and foreign exchange markets in the BRICS countries to better understand market interdependencies.Motivation for the study: The literature mainly focused on volatility transmission from developed countries.Research approach: This research, used the Diebold and Yilmaz spillover index approach (DY index). The DY index is based on variance decompositions (VD) and impulse response functions that use a vector autoregressive (VAR) modelling framework. The study period was from 02 January 1997 to 31 December 2018.Main findings: Shocks from the equity markets dominate the foreign exchange markets, while foreign exchange markets dominate their equity markets at an individual level. There are interdependencies between BRICS equity markets and foreign exchange markets, except for China, whose markets are relatively isolated from other BRICS markets. Brazil is the largest contributor of volatility spillovers to other BRICS markets. The South African rand is the most integrated within BRICS.Practical implications: Foreign exchange markets provided better diversification opportunities. Significant increases in volatility spillovers associated with turmoil periods in domestic and global markets provide evidence for contagion effects in BRICS markets.Contribution: The current account (flow-oriented model) is crucial in exchange rate determination at the individual country level. In contrast, the capital account (stock-oriented model) is a significant factor in exchange rate determinations at an aggregate level.
“…Furthermore, this study also found significant return and volatility spillover indices in Australia, Singapore, the United States and the United Kingdom during both Asian crisis and global financial crisis. Apart from this, many studies (e.g., Bae & Zhang, 2015; Bal, Manglani, & Deo, 2018; Kang & Yoon, 2011; Karunanayake, Valadkhani, & O’Brien, 2010; Li & Giles, 2015) found significant integration among different financial markets in the post global financial crisis period.…”
Section: Literature Review and Theoretical Frameworkmentioning
This study investigates the dynamics of volatility spillover among Asian emerging stock markets over the period from 1 January 2002 to 29 December 2017. This study applies extended EGARCH model to estimate the asymmetric volatility spillovers. The findings of this study are interesting. This study finds statistically significant own past volatility spillovers in all selected stock markets. We find bidirectional significant spillovers of volatility in most of the selected markets. Moreover, we find significant asymmetric volatility spillover in all case of stock markets. Furthermore, the findings reveal statistically insignificant volatility spillover from China to India, China to Indonesia, China to Pakistan, Pakistan to China, Pakistan to Indonesia, Pakistan to Korea and Pakistan to Taiwan in this study period. The knowledge of return linkages and volatility spillover amongst Asian emerging financial markets has great implications for global investors, portfolio managers and policymakers.
“…Hung (2018) and Zabiulla (2015) used this model to examine the volatility spillover in foreign exchange markets. Habiba, Peilong, Hamid, and Shahzad (2019), Bal, Manglani, and Deo (2018) and Majumder and Nag (2018) used EGARCH model in their studies to capture the asymmetric volatility spillover between stock markets.…”
Financial markets are highly sensitive to the flow of information. The nature and arrival of information impact the price of gold. Gold, an international commodity, is traded across the world. Hence, the size and sign of information in any one country may be expected to affect the international gold price fixation. The objective of the study is to analyse the information spillover and the leverage effect transmitted from major gold consuming countries to the fixation of London Bullion Market Association (LBMA) AM fix and PM fix prices and how significantly the information of Indian market contributes to the price fixation. The multivariate exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model proposed by Koutmos and Booth ( 1995 , Journal of International Money and Finance, 14(6), 747–762) is used to analyse the daily spot gold price data of major gold consuming countries like India, the USA, Europe and Japan. The results concluded that price and volatility of major gold consuming countries spill over to the LBMA AM fix and PM fix prices. LBMA AM fix and PM fix prices are sensitive to the new information and their price movements are significantly influenced by the information from India and the USA. The leverage effect shows that positive information causes more volatility in the LBMA fix prices than negative information. The study suggests that the investors, bankers, wholesalers and retail customers who depend on LBMA fix prices as a benchmark price can predict them by utilizing the information received from the Indian and US markets. They can specifically look for positive news than the negative news, as they have more impact on the spillover effect.
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