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We investigate whether or not the effects of the subprime financial crisis on 12 Asian economies are similar to those of the Asian financial crisis by examining volatility spillovers and time-varying correlation between the US and Asian stock markets. After pretesting volatility causality and constancy of correlation, we estimate an appropriate smooth-transition correlation VAR-GARCH model for each Asian stock market. First, the empirical evidence indicates stark differences in stock market linkages between the two crises. The volatility causality comes from the crises-originating country. Volatility in Asian stock markets Granger-caused volatility in the US market during the Asian crisis, whereas volatility in the US stock market Granger-caused volatility in Asian stock markets during the subprime crisis. Second, decreased correlations during the period of financial turmoil were observed, especially during the Asian financial crisis. Third, the estimated points of transition in the correlation are indicative of market participants’ awareness of the ensuing stock market crashes in July 1997 and in September 2008.

This paper aims to study the daily returns and volatility spillover effects in common stock prices between China and four countries in Southeast Asia (Vietnam, Thailand, Singapore and Malaysia).

The analysis uses a vector autoregression with a bivariate GARCH-BEKK model to capture return linkage and volatility transmission spanning the period including the pre- and post-2008 Global Financial Crisis.

The main empirical result is that the volatility of the Chinese market has had a significant impact on the other markets in the data sample. For the stock return, linkage between China and other markets seems to be remarkable during and after the Global Financial Crisis. Notably, the findings also indicate that the stock markets are more substantially integrated into the crisis.

The results have considerable implications for portfolio managers and institutional investors in the evaluation of investment and asset allocation decisions. The market participants should pay more attention to assess the worth of across linkages among the markets and their volatility transmissions. Additionally, international portfolio managers and hedgers may be better able to understand how the volatility linkage between stock markets interrelated overtime; this situation might provide them benefit in forecasting the behavior of this market by capturing the other market information.

This paper would complement the emerging body of existing literature by examining how China stock market impacts on their neighboring countries including Vietnam, Thailand, Singapore and Malaysia. Furthermore, this is the first investigation capturing return linkage and volatility spill over between China market and the four Southeast Asian markets by using bivariate VAR-GARCH-BEKK model. The authors believe that the results of this research’s empirical analysis would amplify the systematic understanding of spillover activities between China stock market and other stock markets.

The paper evaluates the cross-transmission of returns and volatility shocks between Nigeria and South Africa stock markets to infer the extent of interdependence between the two markets. The paper also makes inference to optimal portfolio weights of holding assets in the two markets.

The paper uses an asymmetric vector autoregressive-exogenous generalised autoregressive conditional heteroscedasticity (VAR-X GARCH) model to assess the extent of returns and volatility spillovers between Nigeria and South Africa.

The results of the empirical analysis show evidence of shock spillovers from the South African stock market to the Nigerian stock market. Moreover, based on the dynamic Sharpe ratio and portfolio weight optimisation, the results indicate the possibility of portfolio diversification when holding simultaneous positions in the two stock markets.

The results imply the possibility of economic profit for investors who take positions in the two stock markets. The lack of synchronisation of stock markets in the two largest economies in Africa is in contrast with the situations in other regions where stock markets returns of large economies often co-move.

The paper is the first to use the asymmetric VAR-X GARCH model to assess the cross-transmission of shocks between stock markets.

The purpose of this paper is to investigate whether the crude oil volatility index (OVX) plays any key role in explaining the trend in emerging market stock returns from a global standpoint.

At the empirical stage, different forms of the GARCH-jump model have been estimated.

The findings confirm the effects of OVX on equity returns. In addition, the results document that there exist time-varying jumps in the stock market returns. Besides, the impacts of OVX shocks appear to be symmetric. The analysis further shows that the magnitude of OVX impact is marginally bigger than that of the conventional oil price shocks.

Since various financial assets are traded on the basis of oil and equity markets, investors, for instance, could use the findings of this study for taking proper investment decisions and gaining better portfolio diversification benefits. Additionally, policymakers could utilize the results to develop effective measures and strategies in order to minimize the oil price risk.

This paper aims to investigate the return links and volatility transmission between five major equity markets of the Latin American region and the USA over the period 1993-2012.

The authors employ a multivariate vector autoregressive moving average – generalized autoregressive conditional heteroskedasticity (VAR-GARCH) methodology which allows for cross-market transmissions in both return and volatility. Moreover, we show how the obtained results can be used to design internationally diversified portfolios involving the Latin American assets and to analyze the effectiveness of hedging strategies.

The results point to the existence of substantial cross-market return and volatility spillovers and are thus crucial for international portfolio management in the Latin American region. However, the intensity of shock and volatility cross effects varies across the studied markets.

The optimal weights and hedging ratios that we compute from the observed return and volatility spillovers, suggest that adding the Latin American assets helps improve the risk-adjusted return of the internationally diversified portfolios as well as reduce their risk exposure. For policymakers and market authorities, an increase in the level of shock interactions and volatility transmission between the US and Latin American equity markets as well as among these Latin American markets implies that the stability of the financial system in one country can be deeply affected by the disturbances in another country.

The authors extend the previous works on Latin American emerging markets by examining the extent of shock and volatility transmission as well as portfolio design and management from the point of view of both the US (global) and Latin American investors.

The purpose of this paper is to investigate the dynamic relationship between Nigeria-US exchange rate (XR) and crude oil price (OILP) using daily data from 1 January 2001 to 31 December 2015.

The study uses alternative methods, including vector autoregressive-generalised autoregressive conditional heteroskedasticity (VAR-GARCH) within the framework of Baba-Engle-Kraft-Kroner model, constant conditional correlation (CCC)-GARCH and dynamic conditional correlation (DCC)-GARCH models.

The results from the VAR-GARCH model indicate unidirectional cross-market mean spillovers from oil market (OILM) to foreign exchange market (FXM). In addition, the results show a positive effect of OILP on XR, suggesting that an increase in OILP appreciates Nigerian currency relative to US dollar and a fall in OILP depreciates it. The authors find that the effects of cross-volatility spillovers between the OILM and FXM are bidirectional. The CCC results indicate positive correlations of returns of 16 per cent between the FXM and OILM. Finally, the DCCs results indicate positive correlations between the two markets since the fourth quarter of 2008 (the world financial crisis period) until the recent period of world oil glut and slow demand for crude oil.

Following the depreciation of the Nigerian currency vis-á-vis US dollar since the onset of the recent world oil glut and lower oil prices, Nigerian authorities should embark on subsidy reform, such as reduction in fuel subsidies. This may enable the release of fiscal resources that may be used to either rebuild fiscal space lost or finance investment in non-oil sectors in order to reduce overdependence on oil income. Lower fiscal revenues, coupled with the risk that crude oil maintains its low price for some time, imply that government should reduce its expenditure, and continue to draw on available accumulated funds from the excess crude account for some time until the real depreciation required for adjustment is achieved.

Studies on volatility spillovers between OILM and FXM are limited in the literature, particularly in Nigerian case. Moreover, the study employs different approaches for broader analysis. These alternative methods, a clear departure from the previous studies, provide comprehensive dynamic nature of the relationship between the FXM and OILM.

This study aims to examine the volatility spillover effects between oil and stock returns in the emerging seven economies.

In this study, the Granger causality test and vector autoregression-generalized autoregressive conditional heteroskedasticity approach to analyze the volatility spillover from 1995 to 2019 were used. The findings provide evidence of significant volatility spillover between oil and Brazil, China, India, Indonesia, Mexico, Russia and Turkey (E7) stock markets.

All emerging seven stock markets exhibit positive and low constant conditional correlations with oil assets. The magnitude of the correlation changes in respond to the country’s net position in the crude oil market. While a relatively high level of correlation exists between oil and the stock markets of net oil-exporting countries, a relatively low level of correlation exists between oil and the stock markets of net oil-importing countries.

The findings suggest that oil asset improves the risk-adjusted performance of a well-diversified portfolio of stocks. However, investors should invest a larger portion of their portfolios in E7 stock markets than in oil.

The purpose of this paper is to investigate the volatility linkage between global oil market and major South Asian equity markets.

In order to serve the purpose, the authors employ a recently developed vector autoregressive-generalized autoregressive conditional heteroskedastic model to examine whether shocks and volatility spill over from the oil market to various equity markets under consideration.

The findings of the empirical analysis suggest that all the markets studied do receive volatility from the oil market. Not surprisingly, the authors do not find any significant evidence of volatility transmission from the equity markets to the global oil market. Additionally, while computing the optimal portfolio weights and hedge ratios, the authors document that inclusion of oil in the portfolio of stocks tends to reduce the risk of the resultant portfolio.

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With a substantial return and volatility characteristic of Bitcoin, which may be seen as a new category of investment assets, better understanding of the nature of return and volatility spillover can help investors and regulators in achieving the potential goal from portfolio diversification. The paper aims to discuss these issues.

This paper explores the return and volatility transmission between the Bitcoin, as the largest cryptocurrency, and other traditional asset classes, namely stock, bond and currencies from the standpoint of Turkey over the period July, 2010–June, 2018 using the newly developed multivariate econometric technique, VAR–GARCH, in mean framework with the BEKK representation.

The empirical results reveal the existence of the positive unilateral return spillovers from the bond market to Bitcoin market. Regarding the results of shock and volatility spillovers, there exists strong evidence of bidirectional cross-market shock and volatility spillover effects between Bitcoin and all other financial asset classes, except US Dollar exchange rate.

The important extention is the adoption of a newly developed multivariate econometric technique, VAR–GARCH, in mean framework with the BEKK representation, proposed by Engle and Kroner (1995), which is employed for the first time specifically to examine the extent of integration in terms of volatility and return between Bitcoin and key asset classes. Second, Bitcoin has experienced a rapid growth since around a decade and a number of investors are showing interest in its potential as an integrative part of portfolio diversification. The information provided by empirical results gives empirical bases from which to address topics concerning hedging purposes and optimal portfolio allocation. It is also increasingly important to analyze the current behavior of Bitcoin in relation to other assets to provide policy makers and regulatory bodies with guidance on the role of the Bitcoin as an investment asset in Turkey. Thus, this is the first serious attempt at exploring the potential for Bitcoin to offer diversification opportunities in the context of Turkey.

The purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.

The authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.

The findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.

To the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.