Volatility Linkages Research Articles

DYNAMIC LINKS BETWEEN COMMODITY MARKETS & PAKISTANI SECTORAL INDICES: IMPLICATIONS FOR PORTFOLIO DIVERSIFICATION

This research aimed to examine the inter-connections among international commodities markets and sectoral indices of Pakistan over the most recent period ranging from July 19, 2016, to December 29, 2023. This time period is selected based on recent important events of global significance including COVID-19 pandemics and recent geopolitical crisis emerged due to Russia-Ukraine war in Feb, 2022. This study is utilizing Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model for the deeper inquiry of interplay among the variables. The findings of the study indicate significant spillovers among variables with varying degrees of significance. The results show that various sectors of Pakistan economy showed asymmetric behavior indicating that some sectors were the risk transmitters while other were risk recipients. Moreover, volatility linkages are time-varying with heightened transmissions during turbulent periods. The results provide the significant information in reaching the desired conclusion and making decisions. The findings of study thus had important implications for investors (individual & institutional), fund managers and policy makers while devising strategies for diversification and risk mitigation in the Pakistani context especially in stressful periods.

Financial Interdependencies: Analyzing the Volatility Linkages between Real Estate Investment Trusts, Sukuk, and Oil in GCC Countries

This study investigates the financial interconnections among Real Estate Investment Trusts (REITs), sukuk (Islamic bonds), and oil in Gulf Cooperation Council (GCC) nations. The study sample comprises S&P GCC Composite Equity Real Estate Investment Trusts (REITs) Shariah, the S&P GCC Bond and Sukuk Index, and the OPEC crude oil basket on a daily basis. The duration of coverage spans from 2014 until the beginning of 2024. The TVP-VAR methodology is utilized to examine the interrelationship among the assets. The results indicate that Real Estate Investment Trusts (REITs) and oil are sources of volatility transmission, whereas sukuk is a recipient of volatility within the network. Examining the net pairwise directional linkages of two assets, namely REITs and oil markets, reveals that they transfer their volatility to the sukuk market. Moreover, a reciprocal relationship exists between REITs and oil regarding volatility spillover. It means that REITs act as transmitters to the oil markets during specific periods, while the influence is reversed at other times. This study implies that portfolio managers and investors can discern the volatility patterns of assets in order to enhance their risk-management techniques. For policymakers, comprehending the interdependence of certain asset classes provides valuable knowledge for formulating regulations that might stabilize the financial system and foster economic growth. From a research and academic perspective, this study enhances understanding of the interconnections between different financial asset classes and pricing dynamics in financial markets.

Carbon emission allowances and Nordic electricity markets: Linkages and hedging analysis

Unlike previous studies which tend to consider only return linkages between European emission allowances and electricity markets, this paper examines return and volatility linkages between the two markets and importantly conducts a hedging analysis. Using a dynamic conditional correlation model and daily price data covering European emission allowances and Nord Pool electricity markets from 28th January 2009 to 22th February 2022, which comprise the second and third phases of the European emission allowances trading system, the main results are summarized as follows: Firstly, volatility and returns flow from the Nordic electricity market to the European emission market, with no evidence of a feedback effect, suggesting that rapid changes in demand for electricity may have forced producers to ramp up carbon-intensive facilities. Secondly, the conditional dynamic correlation between the two markets is weak but varies with time, and its sensitivity to crisis periods is noted. Thirdly, the hedging analysis indicates that Nordic electricity market participants can lower their downside risk by including carbon emission allowances in their portfolios, as evidenced by the effectiveness of hedging returns of the Nordic electricity markets with European allowances, irrespective of the COVID-19 sub-periods.

Are Indian markets insulated from the impact of cryptocurrencies? Unveiling the volatility linkages through multi‐index dynamic multivariate GARCH analysis

AbstractThis paper investigates the dynamic relationships between the volatility of Bitcoin and major Indian stock market indices. Employing a dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) model, we explore how volatility shocks and information flow influence the correlations between these asset classes. Our findings reveal a key characteristic: volatility spillovers tend to be short‐lived, indicated by a relatively low DCC‐GARCH parameter (dcca1). This suggests that while a surge in volatility in one market might lead to a temporary increase in correlation with the other, this heightened correlation is unlikely to persist for extended periods. However, the model also highlights a high DCC‐GARCH parameter (dccb1), signifying that the correlations themselves are responsive to new information. This implies that volatility linkages can adjust rapidly in response to market events or economic data releases. To enhance accessibility for a broad audience, we translate these findings into economic intuitions. We illustrate how the model can be interpreted through real‐world examples, such as the impact of sudden policy changes in India or global market flash crashes. By understanding the short‐lived nature of volatility spillovers and the responsiveness of correlations, investors in the Indian markets can make more informed decisions when considering the potential influence of Bitcoin's volatility while contributing to a deeper understanding of the dynamic interactions between cryptocurrency and traditional financial markets in the Indian context.

Assessing the asymmetric volatility linkages of energy and agricultural commodity futures during low and high volatility regimes

AbstractThis study investigated the volatility linkages between energy and agricultural futures, including possible causes for these comovements, such as external macroeconomic and financial shocks during low and high volatility regimes. A combination of Markov‐switching regressions and quadrivariate VAR–DCC–GARCH and VAR–BEKK–GARCH modeling revealed that external shocks have an asymmetric effect on the relationship of these assets with higher cross‐correlations reported during high volatility regimes. This comovement effect outweighs the substitution effect between energy and agricultural products. Furthermore, the quadrivariate VAR–BEKK–GARCH model provides strong evidence of a bidirectional price volatility spillover between the agricultural and energy markets during periods of high volatility. Overall, the results suggest that energy futures can be effectively used for hedging in a portfolio comprising agricultural futures (and vice versa), while a combination of macroeconomic and financial index futures can serve as an effective hedging tool in investment portfolios comprising both energy and agricultural commodities.

Quantile time-frequency connectedness among G7 stock markets and clean energy markets

The rapid growth of clean energy markets as a distinct asset class has attracted significant investor attention. This study examines the interdependence between G7 stock markets and clean energy indices, specifically Renewable Energy Generation (REG), Energy Efficiency (EE), Advanced Materials (AM), and Clean Fuels (CF). Using a state-of-the-art volatility connectedness network and Maximum Overlaps Discrete Wavelet Transform (MODWT), we investigate the quantile time-frequency connectedness among the markets. Our findings reveal strong volatility linkages among all markets, with the exception of Clean Fuels, which has the least connection. We also observe higher dynamic spillover effects under extreme market conditions than normal conditions, with the US market being the most important transmitter of spillovers under bullish markets. Additionally, we highlight the importance of considering the time-varying nature of connectedness, emphasizing the heterogeneity between short-run, medium-run, and long-run transmission. Our study's implications suggest that investors should consider the dynamic nature of spillovers and connectedness when constructing portfolios containing clean energy and G7 stock market assets. The results also imply that the US market's performance has a substantial impact on other markets under bullish conditions, and that Clean Fuels may present an attractive investment opportunity for diversification purposes due to its relative independence.

Risk spillover effect of real estate industry and banking industry

The relationship between the real estate market and the banking industry has always been concerned, and its fluctuation may have a significant impact on the banking industry. In order to deeply understand this influence mechanism, this study uses DCC-GARCH model to analyze the sample data from 2012 to 2022, and reveals the volatility linkage between the real estate market and the banking industry, so as to more accurately analyze the risk transmission effect, with a view to providing support for risk management and policy formulation and helping to establish a more stable and sustainable financial system.

Volatility linkages and value gains from diversifying with Islamic assets

Islamic assets, assets compliant with ethical and religious norms as codified in Sharia law, broaden the investor base. Do such investments contribute to mean-variance efficiency, and if so, how? Using daily data on stock, bond, and money market indices from nine Islamic countries and 37 non-Islamic ones from May 2007 to June 2010, we show that adding Islamic assets to an existing portfolio of conventional (non-Islamic) assets can expand the mean-variance frontier and thereby create additional value through diversification. The “specialness” of Islamic assets comes from a smaller set of common information and a lower degree of cross-market hedging between Islamic and conventional markets. This reduces volatility linkages between Islamic and conventional assets relative to volatility linkages between two conventional assets. Including one Islamic asset lowers volatility linkages by up to 3.16 percentage points after controlling for country-level fixed effects and time-varying characteristics. Low volatility linkages are key to increasing diversification benefits that arise from improvements in the global mean-variance portfolio. Our research contributes to the international business literature by highlighting the potential benefits of bridging religious, ethical, and cultural differences to add new markets to an incomplete international market structure and in so doing increase diversification benefits.

Stock and Currency Market Linkages: An Empirical Analysis from Emerging Economies

Purpose: The Causality relationship between forex and stock market in any economy is dependent on its economic fundamentals. This study examines return and volatility linkages between stock and currency markets for 28 emerging economies weekly MSCI stock index values (in local currency) and foreign exchange rates (indirect quotes) from 1988 to 2019. Theoretical Framework: The understanding of the relationship between forex and stock markets through return and volatility spillover will help in predicting behavior of one market on account of the knowledge of movements in another market. Impact of global financial crisis (GFC) on this relationship is another dimension of research. This study finds the causal relationship between forex and stock markets through return and volatility spillover for all emerging economies along with the effect of GFC on the relationship. Design/Methodology/Approach: The empirical analysis is conducted for the total period and three sub-periods namely pre-global financial crisis, crisis, and post-crisis periods by using the Granger Causality test (Granger 1969) followed by Vector Auto Regression (VAR) model and finally the Dynamic Conditional Correlations (DCC), a multivariate model proposed by Engle (2002). The volatility linkages are studied by employing BEKK-GARCH (Baba, Engle, Kraft, & Kroner, 1990) Findings: It is found that return spillovers are predominantly from Stock to forex markets during the pre-crisis and crisis period but from forex to stock market in the post-crisis period. The increasing presence of return relationships from 10 countries in the pre-crisis period to 19 countries during the crisis period, implying a contagion effect. The BEKK-GARCH result confirm that volatility spillovers are observed throughout from forex to stock markets. Research, practical & social implications: More extensive return and volatility associations between stock and forex market after the global financial crisis confirm the increasing importance of economic fundamentals. Return linkages exhibit contagion against the decoupling effect observed in volatility spillovers during the crisis period. Originality/Value: Based on empirical observations, the study attempts to provide important policy implications for Policy makers, global investors, and academic community.

Asymmetric volatility spillover among global oil, gold, and Chinese sectors in the presence of major emergencies

The volatility of international crude oil and gold markets has affected stock markets through several economic channels, and the impact tends to be more evident with the appearance of emergencies. However, the volatility linkages between commodities and Chinese sector stocks in the presence of emergencies are understudied. To examine the asymmetric relationship and time-varying connectedness between commodities and Chinese sector stocks, this paper first employs GJR-GARCH to capture the realized volatility of international oil, gold, and Chinese sector stocks. Secondly, we decompose the realized volatility of international oil and gold into bad and good volatility and then employ the TVP-VAR-DY approach to obtain the connectedness index. The final result shows asymmetric volatility spillover among oil, gold, and Chinese sector stocks. During the COVID-19 outbreak, the gold good volatility transmission is intenser than bad volatility. Thirdly, the analysis is also carried out under different subperiods. They include three international events: the global financial crisis and the European debt crisis, the oil crisis, and COVID-19. The result reveals heterogeneity exists in the impact of international oil and gold on the Chinese sector stocks under different emergencies. These findings are of great significance for policymakers to improve the sector management under the impact of different emergencies and for investors to design diversified portfolios according to the commodity-sector risk spillover effects.

The US-China trade war and the volatility linkages between energy and agricultural commodities

Any disruptive changes in the competitive environment, such as the U.S.-China trade war, may influence the price volatility of crude oil and agricultural commodities. This study examines the volatility linkage between crude oil and agricultural commodity markets in the context of the U.S.-China trade war and compares the impact of the trade war with that of other exogenous shocks. The results show that the volatility of soybeans exhibits the highest level of responsiveness to the U.S.-China trade war - which is not surprising given that the U.S. agribusiness trade to China is dominated by soybeans - followed by coffee and cotton. The sizes and dynamics of the impacts of shocks are largely commodity-specific. Notably, the trade war impacts most agricultural commodities more extensively than other exogenous shocks, including the global financial crisis and the COVID-19 pandemic and associated recession. These findings matter not only for the decision-making of investors and portfolio managers but also for commodity-exporting and importing countries because changes in the volatility dynamics of crude oil and agricultural commodities often impact export revenues and import expenditures and consequently feed through exports to the global supply chain under exogenous shocks such as the U.S.-China trade war.

Does natural gas volatility affect Bitcoin volatility? Evidence from the HAR-RV model

ABSTRACT While volatility spillover is a vital research area in financial economics (due to its importance for risk valuation and portfolio diversification strategies), the volatility linkage between Bitcoin and electricity/energy markets has not received adequate attention. As the Bitcoin mining cost comes mainly from electricity (which is highly dependent on natural gas), we hypothesize that natural gas is a non-trivial Bitcoin price volatility driver and aim to test if this is the case. Specifically, we employ a widely used model called the HAR-RV model to assess volatility spillover across Bitcoin and natural gas using high-frequency data. We find a spillover effect from natural gas to Bitcoin, and the positive (negative) component of natural gas volatility stabilizes (destabilizes) Bitcoin volatility. The spillover effect is further examined and confirmed using an out-of-sample approach.

CDS and equity markets’ volatility linkages: lessons from the EMU crisis

CDS and equity markets’ volatility linkages: lessons from the EMU crisis

Volatility spillover and hedging strategies between the European carbon emissions and energy markets

Much attention has been paid to the complex risk transmission between carbon and energy markets along with the increasing global financial market integration. This research thus uses the DCC-MVGARCH model and spillover index method to investigate volatility linkages between the European carbon emissions and energy markets. The results make it clear that there are indeed volatility correlations and bidirectional spillover effects for the above two markets. In particular, the volatility correlations and the spillover index dramatically change when global economic turbulence and political events occur. Apart from the strongest volatility correlation between coal and carbon markets, the volatility spillover effect from the renewable energy market to the carbon market is gradually increasing. The role of the carbon market is also changing: the net information recipient becomes a transmitter from phase II to phase IV. Therefore, our findings provide investors with flexible portfolio strategies by making full use of dynamic volatility linkages between the two markets. This research also gives a decision-making basis for market regulators to improve the carbon market's risk management mechanism. It means that regulators should pay close attention to potential market risk sources. Further policy recommendations are put forward in the conclusion section.

Global pandemic crisis and risk contagion in GCC stock markets

This study investigates how the COVID-19 outbreak has shaped the volatility spillover between oil and Gulf Cooperation Council (GCC) stock markets. Contagion analysis is conducted by implementing a vector error correction (VECM) asymmetric BEKK model, wherein both cointegration and asymmetric features are considered. Financial market uncertainty caused by the recent health crisis is captured using Baker et al.’s (2020) newly developed infectious disease tracker. Our results indicate a significant discrepancy in the GCC group, as shock and volatility linkages between oil and equities are more apparent for some countries but not for others. The estimated VECM-asymmetric BEKK model reveals cross-market asymmetric spillover effects only in Kuwait, Qatar, and Saudi Arabia. We report that the global pandemic has strongly affected crude oil market volatility, while the GCC region seems to be less affected by the emergence of the new infectious disease. Our findings underscore the diversification opportunities offered by Gulf equity markets to international investors.

Dynamic volatility connectedness between thermal coal futures and major cryptocurrencies: Evidence from China

Despite the crucial role of thermal coal in generating the electricity used for cryptocurrency mining, the volatility linkage between the cryptocurrency and thermal coal markets is yet to be studied. We investigate the time-varying volatility connectedness between the two markets using their realized variances and semi-variances. Employing a multivariate Heterogeneous Autoregressive model, which accounts for both long memory and structural breaks in realized volatility time series, we find that China's thermal coal futures market is significantly dependent on the cryptocurrency market's volatility while the impact of the energy market on the cryptocurrency market is inconsequential. Moreover, the connectedness is asymmetrical in the sense that the bad volatility connectedness is greater than the good volatility connectedness. Finally, the determinants of the dynamic connectedness highlight the role of the production channel in fuelling the volatility transmission between these two markets.

The linkage between international dairy commodity prices and volatility: a panel-GARCH analysis

PurposeThe study's purpose is to investigate the price volatility of four dairy commodities (skim milk powder [SMP], whole milk powder [WMP], butter and cheddar cheese) in the three most significant regional markets (EU, Oceania and US) in the international dairy market.Design/methodology/approachThe study uses a panel-Generalized Autoregressive Conditional Heteroskedastic (panel-GARCH) modeling technique and data from January 12, 2001, to April 28, 2017.FindingsConditional volatility was higher during subperiods 2007–2010 and 2014–2016 when conditional cross-correlations between prices had the lowest values. In some cases, they were negative (i.e. between the EU and the USA and between Oceania and the USA for both butter and cheese). Interdependence across the three dairy markets, especially for SMP and WMP markets and for the butter market between EU and Oceania is also strongly evidenced. Interdependence is responsible for the spillover of price shocks across the three regions.Research limitations/implicationsThe data set used should be extended to cover the COVID-19 pandemic period.Originality/valueThis is the first study to use panel-GARCH to examine international dairy prices and volatility linkages, where previous studies mainly used multivariate GARCH models. Panel-GARCH allows a high-dimensional data series (i.e. 12 dairy prices) and generates potential efficiency gains in estimating conditional variances and covariances by incorporating information about heterogeneity across markets and considering their interdependence.

Cross-time-frequency analysis of volatility linkages in global currency markets: an extended framework

This research aims to detect cross-border volatility linkages among various currencies within the foreign exchange market with respect to different sampling frequencies. Eleven currency pairs are included in the sample, which covers a period from 2009 to 2020. Volatility linkages among these selected exchange rates were tested by utilizing a multivariate VAR-BEKK-GARCH model. Results indicate that volatility linkages among currencies sampled are far stronger in higher frequency terms. Strikingly, the results denote that the major currencies do not play a strong leading role in volatility transmission. This finding is more apparent when daily and intraday results are compared.

Information and volatility linkages between real estate, equity, bond and money markets in Australia

PurposeThe purpose of this paper is to examine information and volatility linkages among real estate, equity, bond and money markets in Australia.Design/methodology/approachA novel rational expectations framework of financial contagion (Kodres and Pritsker, 2002), along with a combination of robust statistical methods including simple and dynamic correlations and generalized impulse response (Fereidouni et al., 2014) have been employed using data covering three dynamic pre-pandemic economic cycles, namely, global financial crisis (GFC) period, pre-pandemic housing boom and pre-pandemic housing downturn from 2008 (February) to 2019 (December).FindingsResults reveal information linkages across real estate, equity, bond and money markets through correlations in return and volatilities of these series. Finding indicates that the three financial markets (equity, bond and money markets) are interdependent and integrated through information and volatility linkages during the GFC period and pre-pandemic housing downturn period. Financial markets have stronger associations with real estate market during pre-pandemic housing boom. The findings contribute to the general notion that the performances of three financial markets are closely related to the “boom” phase of the real estate cycle.Originality/valueThis research provides an extension of existing literature regarding the information and volatility contagion of the expanded set of core investment markets in Australia. The findings could assist household buyers and investors in designing strategic investment portfolios/hedging strategies and minimizing asset specific risks through diversification over short-term and long-term. In addition, results could support the maintenance, growth and development of a combination of competitive balanced investment markets including real estate, equity, bond and money markets in post-pandemic economy.

Return and volatility linkages between international energy markets and Chinese commodity market

This research investigates the return and volatility linkages between international energy markets and Chinese commodity market at the micro and macro level by employing the Vector Autoregressive combined with BEKK Autoregressive Conditional Heteroskedasticity model (VAR-BEKK-GARCH). Furthermore, this paper also analyzes the changes in return and volatility linkages stepping across the China's exchange rate regime reform in 2015 by splitting the sample into 2 stages: the Pre-reform period (19 June 2010-10 August 2015), and the Post-reform period (11 August 2015-31 December 2021). The empirical results show significant return and volatility spillovers between the international energy markets and China's commodity market, nevertheless, the return spillover effects has been weakened significantly and the vaolatility spillovers have been strengthened significantly after the 2015 China's exchange rate regime reform. The empirical results also provide evidence that the international energy market can effectively hedge the risks of China's commodity market, but the portfolio diversification strategies should be modified across time. Due to the decline in price co-movement, investors have been able to hedge risk in China's commodity market at a lower cost since the reform of the RMB exchange rate system in 2015. However, the efficiency of risk diversification has also declined due to the increased risk linkage between domestic and international markets. In the future, if another reform of the exchange rate system is ought to be initiated, price shocks coming from the external energy markets as well as the risk linkages are all factors needed to be taken into control. Finally, our research also provides a clear way for investors to hedge domestic commodity market risk through international energy markets.