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This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.

The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.

First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.

This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.

Empirical studies have documented the linkage between exchange rate movement and food prices. However, the purpose of this study is to investigate the degree and direction of returns and volatility spillover transmission between exchange rate and domestic food prices in Nigeria.

The study uses weekly data from January 2010 to January 2019. Also, the study adopts the improved Diebold and Yilmaz (2012) approach to evaluate the return and volatility spillover between food price and naira to dollar exchange rate. The study also account for 2016 exchange rate crash in the interconnectedness between food prices and naira to dollar exchange rate.

The paper finds evidence of directional interdependence among the considered food prices and exchange rate based on the obtained spillover indexes. In addition, exchange rate returns and volatility transmission to food prices is more than it receives, particularly after the exchange rate crash.

The high consumption of staple foods requires policies on price stabilisation such as massive investment in local production and reduction in import dependence, in order to cushion the effects of exchange rate depreciation on domestic prices of food.

This study is the first empirical study to investigate the interconnectedness between exchange rate and domestic food prices for a food import–dependent developing country using the Diebold and Yilmaz approach.

The purpose of this paper is to investigate the volatility spillover from crude oil and gold to the BRICS stock markets, after removing the effect of co-movement of prices of crude oil and gold.

Three multivariate GARCH models (dynamic conditional correlation, constant conditional correlation, and Baba, Engle, Kraft and Kroner) are used to capture the dynamic relationship between the crude oil and gold returns. The innovations from gold and oil are orthogonalized, and the EGARCH model is employed for the spillover analysis. The influences of oil price shocks and gold price shocks are tested on the returns of each of the BRICS equity markets.

There is evidence of volatility spillover from both the crude oil and gold to the BRICS stock markets. A sub-sample analysis suggests that the volatility spillover from gold was not significant before the financial crisis of 2008, but became significant post-crisis. The volatility asymmetry, which was not significant before the crisis, also became significant after it.

This study examines the volatility spillover to the BRICS stock markets from crude oil and gold, after accounting for the co-movement in their prices. It can help equity investors to judge whether gold can provide incremental diversification benefit, if used in conjunction with crude oil. The study also provides insights into the changes caused by the 2008 financial crisis on this volatility spillover mechanism.

At the onset of the Global Financial Crisis in 2007–2008, majority of the analysts and policymakers have anticipated contagion from the markets volatility in the advanced economies (AEs) to the emerging markets (EMs). This chapter examines the volatility spillovers from the AEs’ equity markets (Japan, the United States and Europe) to the four key EMs, the BRIC (Brazil, Russia, India and China).

The period under study, from 2000 through mid-2014, reflects a time of varying regimes in markets volatility, including the periods of dot.com bubble, the Global Financial Crisis and the European Sovereign Debt Crisis, the Great Recession and the start of the Russian-Ukrainian geopolitical crisis. To estimate volatility cross-linkages between the AEs and BRIC markets, we use multivariate GARCH-BEKK model across a number of specifications.

We find that, the developed economies weighted return volatility did have a significant impact on volatility across all four of the BRIC economies returns. However, contrary to the consensus view, there was no evidence of volatility spillover from the individual AEs onto BRIC economies with the exception of a spillover from Europe to Brazil. The implied forward-looking expectations for markets volatility had a strong and significant spillover effect onto Brazil, Russia and China, and a weaker effect on India.

The evidence on volatility spillovers from the AEs markets to EMs puts into question the traditional view of financial and economic systems sustainability in the presence of higher orders of integration of the global monetary and financial systems. Overall, data suggest that we are witnessing less than perfect integration between BRIC economies and AEs markets to-date can offer some volatility hedging opportunities for investors.

Our chapter contributes to the growing literature on volatility spillovers from the AEs to the EMs in a number of ways. Firstly, we provide a formal analysis of the spillovers to the BRIC economies over the periods of recent crises. Secondly, we make new conclusions concerning longer-term spillovers as opposed to higher frequency volatility contagion covered by the previous literature. Thirdly, we consider a new channel for volatility contagion – the trade-weighted AEs volatility measure.

This study examines return and volatility spillovers from the US and Japanese stock markets to three South Asian capital markets – (i) the Bombay Stock Exchange, (ii) the Karachi Stock Exchange and (iii) the Colombo Stock Exchange. We construct a univariate EGARCH spillover model that allows the unexpected return of any particular South Asian market to be driven by a local shock, a regional shock from Japan and a global shock from the USA. The study discovers return spillovers in all three markets, and volatility spillovers from the US to the Indian and Sri Lankan markets, and from the Japanese to the Pakistani market. Regional factors seem to exert an influence on these three markets before the Asian financial crisis but the global factor becomes more important in the post-crisis period.

Purpose: This study investigates internal/own shock in the domestic market and three external volatility spillovers from India, the UK, and the USA to the Sri Lanka stock market.

Need for the Study: The external market’s internal/own shocks and volatility spillovers influence portfolio choices in domestic stock market returns. Hence, it is required to investigate the internal shock in the domestic market and the external volatility spillovers from other countries.

Methodology: This study employs a quantitative method using ARMA(1,1)-GARCH(1,1) model. All Share Price Index (ASPI) is the proxy for the Colombo Stock Exchange (CSE) stock return. It uses daily time-series data from 1^st April 2010 to 21^st June 2023.

Findings: The findings revealed that internal/own and external shocks substantially impact the stock price volatility in CSE. Significant volatility clusters and persistence with extended memory in ASPI confirm internal/own shock in the market. Furthermore, CSE receives significant volatility shock from the USA, confirming external shock. This study’s findings highlight the importance of considering internal and external shocks in portfolio decision-making.

Practical Implications: Understanding the influence of internal shocks helps investors manage their portfolios and adapt to market volatility. Recognising significant volatility spillovers from external markets, especially the USA, informs diversification strategies. From a policy standpoint, the study emphasises the need for robust regulations and risk management measures to address shocks in domestic and global markets. This study adds value to the literature by assessing the sources of volatility shocks in the CSE, employing the ARMA-GARCH, a sophisticated econometrics model, to capture stock returns volatility, enhancing understanding of the CSE’s volatility dynamics.

To estimate the volatility of exchange and stock markets and examine its spillover within and across the member countries of BRICS during COVID-19 and the conflict between Russia and Ukraine.

The study utilizes the “dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH)” approach of Gabauer (2020). The volatility of the markets is calculated following the approach of Parkinson (1980). The sample dataset comprises the daily volatility of the stock and exchange markets for 35 months, from November 2019 to September 2022.

The study confirms the existence of contagion effects among member countries. Volatility spillover between exchange and stock markets is low within the country but substantial across borders. Russian contribution increased significantly during the conflict with Ukraine, and other countries also witnessed a surge in the spillover index during the pandemic and war.

It adds to the body of literature by emphasizing the necessity of comprehending the economies' behavior and interdependence. Offers insightful information to decision-makers who must be more watchful regarding the financial crisis and its regional spillover.

The study is the first to explore the contagion of volatility among the BRICS countries during the two biggest crisis periods of the decade.

The purpose of this paper is to empirically examine the volatility and return spillover between exchange-traded funds (ETFs) and their respective benchmark indices in India. The paper uses time series data which consist of equity ETF and respective index returns.

The study uses autoregressive moving average–generalized autoregressive conditional heteroscedasticity and autoregressive moving average–exponential generalized autoregressive conditional heteroscedasticity models. The study uses data from the inception date of each ETF to December 2016.

The findings of the paper confirm that there is unidirectional return spillover from the benchmark index to ETF returns in most of the ETFs. Furthermore, ETF and benchmark index return have volatility persistence and show the presence of asymmetric volatility wherein a negative news has more influence on volatility compared to a positive news. Finally, unlike unidirectional return spillover, there is a bidirectional volatility spillover between ETF and benchmark index return.

The study has several practical implications for investors and regulators. A positive daily mean return over a fairly long period of time indicates that the passive equity ETFs can be a viable long-term investment option for ordinary investors. A bidirectional volatility spillover between the ETFs and benchmark index returns calls for the attention of the market regulators to examine the reasons for the same.

ETFs have seen fast growth in the Indian market in recent years. The present study considers the longest period data possible.

This paper examines the return and volatility spillovers among major cryptocurrency using daily data from 10/08/2015 to 15/04/2018.

The authors employ the Dielbold and Yilmaz (2012) spillover approach and rolling sample analysis to capture the inherent secular and cyclical movements in the cryptocurrency market.

The authors show that there is substantial difference between the behaviour of the cryptocurrency portfolios return and volatility spillover indices over time. The authors find evidence of interdependence among cryptocurrency portfolios given the spillover indices. While the return spillover index reveals increased integration among the currency portfolios, the volatility spillover index experiences significant bursts during major market crises. Interestingly, return and volatility spillovers exhibit both trends and bursts respectively.

This study makes a methodological contribution by adopting Dielbold and Yilmaz (2012) approach to quantify the returns and volatility transmissions among cryptocurrencies. To the best of our knowledge, little or no study has adopted the Dielbold and Yilmaz (2012) methodology to investigate this dynamic relationship in the cryptocurrencies market. The Dielbold and Yilmaz (2012) approach provides a simple and intuitive measure of interdependence of asset returns and volatilities by exploiting the generalized vector autoregressive framework, which produces variance decompositions that are unaffected by ordering.

This work investigates the volatility spillovers across stock markets and the nature of such spillovers through different periods of crises and tranquility.

Using daily stock return volatility data from June 2003 to June 2021, the generalized forecast error variance decomposition method (based on Diebold and Yilmaz, 2012 approach) is employed to measure the degree of volatility spillovers/connectedness among stock markets of 24 Asia–Pacific and 12 European Union (EU) economies.

The empirical results from static analysis suggested that about 28.1% (63.7%) of forecast error variance in return volatility for Asia–Pacific (EU) markets is due to spillovers. The evidence from dynamic analysis suggested that during mid of the global financial crisis, European debt crisis (EDC) and Covid-19, the gross volatility spillovers for Asia–Pacific (EU) was around 67% (80%), 65% (80%) and 73% (67%), respectively. The degree of net volatility transmission from Singapore (Denmark) to other Asia–Pacific (EU) markets was found to be highest.

The findings have crucial implications for the investors and portfolio managers in assessment of risk and optimum allocation of assets and investment decisions.

This study adds to the literature on risk management by systematically examining the impact of global financial crises, EDC and Covid-19 on the market interactions by capturing the magnitude, duration and pattern of the shock-specific market volatilities for a large sample of Asian and European markets using recent and large data set.