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The study uses the multivariate GARCH-BEKK model (which was first proposed by Baba et al. (1990) and then further developed by Engle and Kroner (1995)) to examine the return and volatility spillover between India and four leading Asian (namely, China, Japan, Singapore and Hong Kong) and two global (namely, the United Kingdom and the United States) equity markets.

The study employs a multivariate GARCH-BEKK model to quantify return correlation and volatility transmission across the pre- and post-2008 global financial crisis periods (apart from other conventional time series modelling like cointegration, Granger causality using vector error correction model (VECM)).

The results show a tendency of the Indian stock market index to move along with the US and Hong Kong market indices. The decrease in the value of the co-integration coefficient during the recession was explained by reduced investor confidence in developing countries. The result further shows a clear distinction in terms of volatility spillover between the Asian market vis-a-vis US and UK markets. Volatility transmission from India to Asian markets was found to be significantly higher as compared to the US and UK. So also, the study’s results show a puzzling result giving us comparable co-integration ranks for phase 2 (expansion) and phase 3 (slow-down) of the business cycle in most cases.

In Granger causality testing, the results were unable to ascertain the difference between phase 2 (expansion) and phase 3 (slowdown). However, the multivariate GARCH (MGARCH)-BEKK model showed a clear reduction in volatility transmission to NIFTY50 (is the flagship index on the National Stock Exchange of India Ltd. (NSE)) as India entered slow-down. This shows that the Indian economy does go through different business cycles, and the changes in parameters hence prove hypothesis 3 to be true with respect to volatility transmission to India from International markets.

The results show that for all countries, the volatility transmitted to India increases significantly going from phase 1 (recession) to phase 2 (expansion) and reduces again once the countries enter slow-down in phase 3 (slowdown). This shows that during expansion shocks and impulses in international markets affect the Indian markets significantly, supporting the increase in co-integration in phase 2 (expansion). During expansion, developing markets like India become profitable for investors, due to the high growth rate when compared to developed countries. This implies that a significant amount of capital enters Indian markets, which is susceptible to the volatility of international markets. The volatility transmission from India to the US and UK was insignificant in phase 1 (recession and recovery) and phase 3 (slow-down) showing a weak linkage between the markets during volatile time periods.

This study aims to examine the performance and volatility of Turkey Real Estate Investment Trusts (Turkish REITs) as the world is adjusting to the new normal situation in every aspect of REITs' business activities.

The prices of REITs were acquired from 26 Turkish REITs in this study, but owing to autocorrelation difficulties, 14 Turkish REITs were employed in the analysis. The ten-year long-term bond of the Turkish Government was also utilized and the period of data obtained was based on availability. The performance of Turkish REITs was evaluated using Sharpe's ratio and Treynor's ratio, and the volatility was assessed using MGARCH-BEKK.

The authors found out that Turkish REITs are constantly underperforming and the REITs' returns remain highly volatile and persistent. In addition, findings showed evidence of volatility clustering and the asymmetric impact of shocks. This study further revealed the uniqueness of each of the Turkish REITs due to the lack of evidence of multicollinearity.

However, the limitation of this study is the constraint in obtaining more macro-economic variables of more than ten-years of Turkey's Government bond and the study focused mainly on Turkish REITs.

The result suggests that since Turkish REITs are not mandatory to payout 90% of taxable earnings as dividends, high performance and an appropriate risk management approach are expected. The need for timely revealing performance of T-REITs and associated uncertainty may trigger better performance as discussed in the relationship between disclosure and performance which is recently emphasized in a recent study by Koelbl (2020). With current performance and associated uncertainty in Turkish REITs, the need to protect Turkish REITs investors is highly essential. The result further educates REIT investors that diversification benefits of REITs tend to reduce in extremely risky situations.

This is the first study in the context of Turkish REITs that comprehensively integrated market capitalization of REITs and simultaneous evaluation of performance and the volatility of the Turkish REITs as the world adjusts to the new normal.

The purpose of this paper is to examine the short-term and long-term interdependence among the stock markets of Africa and Middle East region. It also attempts to analyze the pattern of volatility spillover among the regional stock markets.

The study has used Granger causality test, variance decomposition test of vector auto-regression (VAR) model, vector error correction model (VECM), multivariate generalized conditional heteroskedasticity (MGARCH-BEKK) models and Johansen and Juselius multivariate cointegration techniques.

The study finds that the interlinkages of the stock markets are not uniform across all the countries of the region. The stock market of Israel, South Africa and Jordan are found to be highly connected stock market of the region followed by Egypt and Botswana. The study also finds significant spillover of lagged standardized volatility across the stock markets of the region. But the magnitude of the response of volatility spillover and its persistence is very minimum. However, the stock markets are found to be co-integrated and expected to share long-run equilibrium relationships among each other.

The study has the scope to be extended to capture the time-varying integration of market returns with transmission of monetary policy and exchange rate changes within the region. The results obtained from this study may assist the firm managers and international investors to understand the key drivers of market connectedness.

Empirically investigating the pattern of stock market connectedness in Africa and Middle East region with advanced methodology over a long study period is the originality of this study.

The purpose of this paper is to examine the conditional correlations and spillovers of volatilities across CEE markets, namely, Hungary, Poland, the Czech Republic, Romania and Croatia, in the post-2007 financial crisis period.

The authors use five-dimensional GARCH-BEKK alongside with the CCC and DCC models.

The estimation results of the three models generally demonstrate that the correlations between these markets are particularly significant. Also, own-volatility spillovers are generally lower than cross-volatility spillovers for all markets.

These results recommend that investors should take caution when investing in the CEE equity markets as well as diversifying their portfolios so as to minimize risk.

Unlike the previous studies in this field, this paper is the first study using multivariate GARCH-BEKK alongside with CCC and DCC models. The study makes an outstanding contribution to the existing literature on spillover effects and conditional correlations in the CEE financial stock markets.

The purpose of this paper is to analyze the optimal hedging strategy of the oil-stock dependence structure.

The methodology consists to model the data over the daily period spanning from January 02, 2002 to May 19, 2016 by a various copula functions to better modeling the dependence between crude oil market and stock markets, and to use dependence coefficients and conditional variance to calculate optimal portfolio weights and optimal hedge ratios, and to suggest the best hedging strategy for oil-stock portfolio.

The findings show that the Gumbel copula is the best model for modeling the conditional dependence structure of the oil and stock markets in most cases. They also indicate that the best hedging strategy for oil price by stock market varies considerably over time, but this variation depends on both the index introduced and the model used. However, the conditional copula method with skewed student more effective than the other models to minimize the risk of oil-stock portfolio.

This research implication can be valuable for portfolio managers and individual investors who seek to make earnings by diversifying their portfolios. The findings of this study provide evidence of the importance of stock assets for making an optimal portfolio consisting of oil in the case of investments in oil and stock markets. This paper attempts to fill the voids in the literature on volatility among oil prices and stock markets in two important areas. First, it uses copulas to investigate the conditional dependence structure of the oil crude and stock markets in the oil exporting and importing countries. Second, it uses the dependence coefficients and conditional variance to calculate dynamic hedge ratios and risk-minimizing optimal portfolio weights for oil–stock.

Capital markets thrive on information, and the information revolution has transformed these markets all over the world. Investors can now keep track of the movements of capital markets in real-time and they react to the flow of information from around the world. One of the concerns of stock market investors is whether the markets operate efficiently, independently, and with sound fundamentals. However, real market movements tend to exhibit a link as is evident from recent market movements across the world.

The assessment of interdependence between stock markets is an important aspect of international portfolio management. The aim of this chapter is to examine the shock and volatility spillover between the Standard and Poor’s 500 (S&P500) index from the United States (US) Stock Exchange and the Istanbul Stock Exchange 100 (BIST100) index from the Stock Exchange Istanbul.

S&P500 index, which is the most important index representing US markets, and BIST100 index, which is the index representing the Turkish market, were used as variables in this study. In the analysis, the causality in variance test was applied to determine the volatility spillover between these two markets. Later, multivariate GARCH (MGARCH) models were used to measure the volatility spillover in the markets. VAR(1)-GARCH (1,1)-Diagonal BEKK model was applied to the daily data to determine the shock and volatility spillover in the markets.

As a result of the variance causality test, it was found that there is a bi-directional volatility spillover between S&P500 index and BIST100 index. When the return spillover between the markets is examined, a one-way spillover from the S&P500 index to the BIST100 index emerged. Diagonal BEKK model results show that each market is affected by its own news (unexpected shocks) and volatility. Furthermore, the volatility is persistent for both markets. These findings demonstrate that the US market and the Turkish market interact with each other.

The purpose of this paper is to analyze the existence of volatility spillover effect in frontier markets. This study also examines whether any linkages exist among these markets or not.

Monthly data of regional frontier markets, from 2009 to 2016, are analyzed using Multivariate GARCH (BEKK and Dynamic Conditional Correlation (DCC)) models.

The result of cointegration test shows that the sample frontier markets are not linked in long run, and Granger causality test reveals that the markets under consideration do not cause each other even in the short run. BEKK test says that the effect of the arrival of shock from the own market does not last for longer, whereas shock from other markets lasts with the stronger persistence, and according to DCC test, the volatility spillover exists for all the markets.

The results of present study suggest that the frontier markets are not cointegrated in the long run as well as in the short run, which opens the doors for long-term investments in these markets in future, which may lead to decent returns. Long-term investors may draw the benefits from including the financial assets in their portfolios from these non-integrated frontier markets; nevertheless, they have to consider and implement diversification and hedging strategies during the period of financial turmoil, so as to protect themselves against economic and financial distress.

Significant work has been done on developed, developing and emerging markets but frontier markets are not explored much so far. This paper is an attempt to see the status of frontier stock markets as potential financial markets for diversification benefits.

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.

The purpose of this paper is to examine the price discovery and volatility spillovers in spot and futures prices of four currencies (namely, USD/INR, EURO/INR, GBP/INR and JPY/INR) and between futures prices of both stock exchanges namely, Multi-Commodity Stock Exchange (MCX-SX) and National Stock Exchange (NSE) in India.

The study applies cointegration test of Johansen’s along with VECM to investigate the price discovery. GARCH-BEKK model is used to examine the volatility spillover between spot and futures and between futures prices. The other two models namely, constant conditional correlation and dynamic conditional correlation are used to demonstrate the constant and time-varying correlations. In order to confirm the volatility spillover results, the study also applies test of directional spillovers suggested by Diebold and Yilmaz (2009, 2012).

The results of the study show that there is long-term equilibrium relationship between spot and futures and between futures markets. Between futures and spot prices, futures price appears to lead the spot price in the short-run. Volatility spillover results indicate that the movement of volatility spillover takes place from futures to spot in the short-run while spot to futures found in the long-run. However, the results of between futures markets exhibit the dominance of MCX-SX over NSE in terms of volatility spillovers. By and large, the findings of the study indicate the important role of futures market in price discovery as well as volatility spillovers in India’s currency market.

The results highlight the role of futures market in the information transmission process as it appears to assimilate new information quicker than spot market. Hence, policymakers in emerging markets such as India should focus on the development of necessary institutional and fiscal architecture, as well as regulatory reforms, so that the currency market trading platforms can achieve greater liquidity and efficiency.

Due to recent development of currency futures market, there is dearth of literature on this subject. With the apparent importance of currency market in recent time, this study attempts to study the efficient behavior of currency market by way of examining the price discovery and volatility spillovers between spot and futures and between futures prices of four currencies traded on two platforms. The study has strong implications for India’s stock market especially at the time when its currency is under great strain owing to the adverse impact of global financial crisis.