Bidirectional Volatility Spillover Research Articles

Cross-market volatility dynamics in crypto and traditional financial instruments: quantifying the spillover effect

PurposeThis paper examines the volatility spillover effects from traditional financial assets to cryptocurrency markets and vice versa. It aims to provide insights into the dynamic interconnectedness of these markets.Design/methodology/approachThis paper employs the time-varying parameter vector autoregression technique to examine the volatility spillover among the crypto markets (across leading cryptocurrencies such as Bitcoin (BTC), USD Tether, NEAR Protocol (NEAR), Immutable and Dogecoin) and traditional financial instruments (Treasury Bills (TBILL) and Volatility Index).FindingsThe results reveal significant bidirectional volatility spillovers between cryptocurrencies and traditional financial assets. NEAR and BTC act as a major transmitter of volatility, both influencing others significantly (71.63 and 68.17%, respectively) and being influenced by others (54.74 and 62.3%, respectively). TBILL and Grayscale Bitcoin Trust ETF are the largest net receivers of volatility, indicating a higher dependency on other assets’ volatility.Practical implicationsUnderstanding the volatility spillover dynamics can aid investors in portfolio diversification and risk management. The findings provide actionable insights for constructing portfolios that include both cryptocurrencies and traditional financial assets, allowing for more informed investment decisions under volatile market conditions.Originality/valueThis paper contributes to the literature by analyzing volatility spillovers among traditional financial markets and various major cryptocurrencies. It offers a framework for assessing how shocks in one market or cryptocurrency can propagate to others, thereby enhancing the understanding of interconnectedness between markets. This understanding improves our ability to risk manage modern portfolios, which increasingly include significant alternative assets like cryptocurrencies.

The Post-Internationalization Evolution of the Price Discovery Pattern in China’s Iron Ore Markets

Previous literature provided evidence of a negative impact of internationalization on the quality of China’s iron ore futures market within a 6-month window (i.e. June 1, 2018 to November 31, 2018), but little is known on the long-term impact. Using a longer, 4-year-7-month window from June 1, 2018 to December 30, 2022, we examine the market’s price discovery function, an important measure of market quality. We find significant structural break in China’s iron ore data series in August 2021, which largely coincide with a period of rising commodity prices to all-time high. Before the breaks, the price discovery function of China’s iron ore futures appears quite weak, with the spot market leading the futures market, which is consistent with the findings of Fan et al. During the post-break period, however, the futures market demonstrates a stronger price discovery function and takes over the leading role. The day-of-the-week effects in iron ore futures also seem to weaken post-break as well. Our GARCH model results exhibit significant bi-directional volatility spillover between the futures and spot markets.

COVID-19 pandemic and linkage between stock markets in Middle Eastern countries

PurposeThe purpose of this study is to evaluate the linkage between stock markets in Middle Eastern countries before and during the COVID-19 pandemic by using daily and monthly data sets for the period from 2011 to 2021.Design/methodology/approachThe multivariate BEKK-GARCH model was computed to evaluate the existence of non-linear linkage among Middle Eastern stock markets. A correlation approach was used in this study to determine the type of linear connectivity between Middle Eastern stock markets. The study used monthly and daily data sets covering the years 2011 to 2021 to investigate the linkage between stock returns and the volatility spillover between the stock markets in Palestine, Jordan, Syria and Lebanon, both before and during COVID-19. To understand the types of relationships between markets before and during COVID-19, the daily data set was split into two periods.FindingsResults from the pre-COVID-19 suggest that the Syria stock market is not related to any stock market in the Middle East markets; the Palestine and Lebanon stock markets exhibit a weak relationship, but Jordan and Palestine stock markets are strongly linked. Conversely, results from COVID-19 evince a very strong bidirectional volatility spillover between Middle East stock markets. Overall, the results indicate the existence of increased linkage during the COVID-19.Research limitations/implicationsThe data collection on a daily and monthly basis, both before and during COVID-19, presents certain limitations for the paper. Another limitation is that the data cannot be generalized to all other Middle Eastern countries; rather, the conclusions drawn can only be applied to these four countries. This is especially true if the scholars collected most of the necessary data but were unable to obtain certain data for various reasons.Practical implicationsThese findings have implications for risk management, market regulation and the growth of local stock markets. Facilitating the growth of smaller, more specialized markets to improve integration with other Middle Eastern markets is one of the goals of the domestic stock market development policy. To ensure financial stability, Middle Eastern stock market linking policies should consider spillover risk and take steps to minimize it. Enhancing the range of investment opportunities accessible to shareholders and functioning as confidential risk-sharing mechanisms to facilitate improved risk management in Middle Eastern stock markets will not only significantly influence the mobilization of private capital to promote investment and local economic growth but also lay groundwork for integrated market platforms.Originality/valueThis paper adds to the body of literature by demonstrating the nature of the connections between these small markets and the larger markets in the Middle East region. Information from the smaller markets provides institutional insights that enhance the body of existing research, guide the formulation of evidence-based policies and advance financial literacy in these markets. This study contributes by comparing data from different stock markets to better understand the type and strength of the link and relationship between Middle Eastern stock markets, as well as any underlying or reinforcing factors that might have contributed to the relationship and the specific types of links that these markets shared prior and during COVID-19.

Global oil price and stock markets in oil exporting and European countries: Evidence during the Covid-19 and the Russia-Ukraine war

The relationship between oil price movements and stock markets during the COVID-19 pandemic and the geopolitical crisis like the ongoing Russian-Ukraine war is yet unexplored extensively. This study therefore examines the return-correlation effects of oil prices on stock markets and their spillover effects in oil-exporting and European countries using daily closing data. After estimating the GARCH process, we employ the static and dynamic Markov Switching model that allow the relationship between oil price and stock market to switch between two regimes coined the COVID-19 and the Russia-Ukraine war periods. The static model shows stock price returns to respond positively and significantly to oil price returns in Italy, Germany and the US during the Covid-19 period while the response is significantly positive only for US in the Russia-Ukraine war period. As regards the volatility spillover, significant spillover is found from stock to oil market for Nigeria, vice versa for Saudi Arabia and bi-directional volatility spillover found for the US, Italy and Germany during the COVID-19 period. The policy implication is that Nigeria and Saudi Arabia should prioritize financial policy and energy policy respectively while US, Italy and Germany should adopt policy coordination to stabilize oil-stock market volatility during low oil price period like the COVID-19 period.

Spillover Effect of Network Public Opinion on Market Prices of Small-Scale Agricultural Products

Network public opinion plays a crucial role in the behavior and decision making of various stakeholders, including farmers, middlemen, and consumers. It also affects the price fluctuations of small-scale agricultural products. Understanding the transmission path and spillover effect of network public opinion on the price fluctuations of these products is essential for ensuring their sustainable development and price stability. This paper selects the monthly data of network public opinion and related market prices of small-scale agricultural products from January 2014 to December 2021, constructs a network public opinion value through the sentiment classification results of deep learning models, and uses the trivariate VAR-BEKK-GARCH(1,1) model and spillover index model to study the spillover effect and spillover index of network public opinion on the market prices of small-scale agricultural products (national average price and origin price). The results show that: (1) There is a bidirectional volatility spillover effect between public opinion sentiment and the market prices of small-scale agricultural products. Additionally, this two-way volatility spillover effect is also evident between the average market prices and the origin prices of these commodities. (2) The influence of network public opinion on the market prices of small-scale agricultural products is substantial, with the spillover index being more pronounced for origin prices than for national average prices and reaching its zenith earlier. Consequently, based on these results, recommendations are provided to adapt planting and inventory strategies, enhance vigilance towards price risk transmission amongst small-scale agricultural product markets, and improve the comprehensive information platform encompassing the entire industry chain.

Odnos ruskog i turskog sektorskog tržišta akcija - uticaji sukoba između Rusije i Ukrajine

In this paper, the effects of the Russia-Ukraine conflict on the stock markets of Turkey (BIST), which has strong economic relations with both countries, and Russia (MOEX), one of the parties to the conflict, are investigated. The relationship between the stock indices for the overlapping sectors of both stock markets (namely the consumption, electricity, financial, oil and telecom sectors) are examined using the Fourier volatility spillover and Fourier-Granger causality tests. The findings of the paper indicate that there is a bidirectional causality relationship between both countries in the electricity sector, and a causality relationship between BIST and MOEX in the telecom sector. In addition, there is a bidirectional volatility spillover in the electricity, finance and oil sectors between the stock markets of the two countries. However, there is also a volatility spillover from MOEX to BIST in the food sector. The COVID-19 epidemic and the Russia-Ukraine war can be quoted as the reasons for this situation. This volatility spillover between the countries seems likely to harm the Turkish economy in the case of possible negative developments during the war. The results obtained in this study provide valuable information for portfolio diversification to the investors who will invest in these sectors as long as the war conditions continue.

Returns and Asymmetric Volatility Interdependencies between Sustainable and Conventional Stock Indices: Evidence from Developed and Emerging Countries

The study investigates the co-integration and asymmetric volatility interdependence between the sustainable and conventional stock indices of emerging and developed countries. Daily closing values are used from 1st January 2015 to 15th July 2022. The study employs ARDL and VAR-Granger causality model to examine long-run association and cause-effect relation, respectively. Moreover, the Bivariate EGARCH model is also used to analyse return and asymmetric volatility spillover between two indices. The analysis reveals no evidence of co-integration between sustainable and conventional indices. However, bidirectional causality exists in all countries except the United Kingdom (UK) and United Arab Emirates (UAE). The return spillover result exhibits that return of the conventional index of Japan and Brazil are negatively affected by changes in its sustainable index. The EGARCH results reveal the bidirectional volatility spillover in all the markets. The volatility shocks from the sustainable index of the United States of America (USA) and China have an asymmetric effect on the conventional indices of these countries. Further, positive asymmetric spillover was observed between the sustainable and conventional indices of Brazil and UK. The knowledge of linkage and asymmetric volatility spillover will assist the investors in portfolio management and formulating hedging strategies during financial and economic adversities.

Spillover of volatility among financial instruments: ASEAN-5 and GCC market study.

The research examines a comovement and spillover of volatility among foreign exchange, conventional and shariah stock markets in Association of South East Asian Nation-5 (ASEAN) countries and Gulf Cooperation Council (GCC) countries. Generalized Autoregressive Conditional Heteroskedasticity-Baba, Engle, Kraft and Kroner (GARCH-BEKK) and Dynamic Conditional Correlation (GARCH-DCC) models are used to capture the correlation and transmission volatility of the markets. The overall results show that both the Shariah and the conventional stock indices respond similarly to each country's currency. A bidirectional (two-way relationship) volatility spillover exists only in Malaysia and a unidirectional (one-way relationship) volatility is observed in Indonesia, Singapore, Thailand, and Bahrain. The rest of the markets-the Philippines, Saudi Arabia, and the United Arab Emirates (UAE)-do not have any volatility spillover evidence. Based on DCC outcomes, the conventional and Shariah stock in ASEAN-5 countries and GCC countries reveal the market efficiency, i.e., a positive high conditional correlation. Only Bahrain shows less efficiency than the other countries. It implies no portfolio diversification advantage in conventional and Shariah stock indices. Contrarily, currency and stock (conventional and Shariah) markets provide portfolio diversification benefits for all ASEAN-5 and GCC countries.

Exploring the interconnectedness of China's new energy and stock markets: A study on volatility spillovers and dynamic correlations

In its efforts to achieve carbon peak and carbon neutrality, China has focused on new energy as a key driver, with significant implications for China's new energy and stock markets. However, few studies have examined the relationship between the two markets. Based on multivariate generalized autoregressive conditional heteroskedasticity models, we investigate the volatility spillovers and dynamic correlations between China's new energy and stock markets using daily data from 2009 to 2023. And we also explore how these dimensions changed during the financial crisis in 2015 and the COVID-19 period. Our findings indicate that there are bidirectional volatility spillovers and asymmetric effects between these markets, suggesting that risks can accumulate and negative shocks may have greater impacts than positive ones. These findings are still robust after changing the distribution of the error term and excluding the impact of COVID-19. Significantly, volatility spillovers between markets increased and asymmetric effects disappeared during the two events due to the extreme turbulence in the stock market. Additionally, we find that the two markets exhibit high interdependence, implying the existence of risk synergy effects and limited possibilities for portfolio diversification. Finally, our analysis of the marginal expected shortfall indicates that losses in China's new energy market increased during the financial crisis in 2015, implying that this strategic market is more exposed to the negative shocks of the stock market. These results are valuable to policymakers, investors, and companies involved in China's new energy market.

Exploring the relationship between digital trails of social signals and bitcoin returns

PurposeThis study aims to empirically investigate the linkages between digital trails of social signals (content and profile features of bitcoin-related tweets) and bitcoin price return using a VAR-BEKK-GARCH model.Design/methodology/approachBitcoin-related tweets were collected every hour for six months from September 1, 2020, to February 29, 2021. The analysis involved two steps: first, examining tweet content, profiles, sentiment and emotions; and second, investigating the relationship between social signal volatility and hourly bitcoin price return.FindingsResults indicate that bitcoin price changes can impact the sentiment expressed in tweets about bitcoin, and vice versa. While sadness exhibits a bidirectional volatility spillover with bitcoin, fear and anger display a one-period lag. Quartile analyses reveal that only fear in the second quartile shows a bidirectional spillover effect with bitcoin, while all other emotions except sadness demonstrate a unidirectional spillover effect in all remaining quartiles.Originality/valueThe study uses a novel two-step approach to analyze volatility spillovers between social signals and bitcoin price returns. Findings can guide investors and portfolio managers in making better allocation decisions and assist policymakers and regulators in reducing the adverse effects of bitcoin’s volatility on financial system stability.

Exploring the Contagion Effect from Developed to Emerging CEE Financial Markets

The paper aims to analyze the contagion effect coming from the developed stock markets of the US and Germany to the emerging CEE stock markets of Romania, Czech Republic, Hungary, and Poland using daily data for the period April 2005–April 2021. The paper also captures the level of integration of these emerging stock markets by analyzing the volatility spillover phenomenon. The quantification of the contagion effect coming from the developed to the emerging stock markets consisted of an empirical analysis based on the DCC-GARCH (Dynamic Conditional Correlation) model. Through this multivariate model, the time-varying conditional correlations were analyzed, both in periods of normal economic development and in times of economic instability, when there was a significant increase in the correlation coefficients between developed and emerging stock market indices. Furthermore, the level of connectedness between these markets has been analyzed using the volatility spillover index developed by Diebold and Yilmaz. The empirical results surprised the high level of integration of the analyzed stock markets in Central and Eastern Europe, with the intensity of volatility transmission between these markets increasing significantly during times of crisis. All stock market indices analyzed show periods during which they transmit net volatility and periods during which they receive net volatility, indicating a bidirectional volatility spillover phenomenon. Mostly, the BET, PX, and WIG indices are net transmitters of volatilities, whereas the BUX index is net recipient, except during the COVID-19 crisis, when it transmitted net volatility to the other three indices. Finally, using a Markov switching-regime VAR approach with two regimes, we explored the contagion effect between emerging CEE and developed stock markets during the COVID-19 pandemic. The empirical results proved a shift around the outbreak of the health crisis, after which the high volatility regime dominates the CEE markets. The contagion effects from developed stock markets to emerging CEE markets significantly increased during the first stage of the health crisis.

Persistence and volatility spillovers of bitcoin price to gold and silver prices

The paper investigates persistence, returns and volatility spillovers from the bitcoin market to the gold and silver markets using daily datasets from January 2, 2018 to July 31, 2020 by employing the fractional persistence framework. The results show strong price persistence with bitcoin posing the highest volatility persistence, while silver poses the lowest volatility persistence. The results of multivariate GARCH modelling, using the CCC-VARMA-GARCH model and other lower variants indicate the impossibility of returns spillover between the bitcoin and gold (or silver) market, while there exist bi-directional volatility spillovers. Appropriate portfolio management and hedging strategies render towards the end of the paper require more gold and silver investments in the portfolio of bitcoin to fully have the diversification advantage and reduce risk to the minimum without reducing the expected returns of their portfolio.

Impact of Brexit on bond yields and volatility spillover across France, Germany, UK, USA, and India’s debt markets

Britain’s decision to exit the EU lead to disruptions in global markets. This study investigates the change in the return and volatility spillover pattern due to the repercussions of the Brexit vote between the US, France, the UK, Germany, and India’s 10-year government bond yields by applying the VAR and GARCH-BEKK models. The findings demonstrate a substantial rise in the return spillover to India and USA 10-year government bond yields following the Brexit vote compared to the pre-Brexit vote era. In addition, the results showed evidence of unidirectional volatility spillover from India to France, bidirectional volatility spillover between the USA and India, and unidirectional volatility spillover from the UK to India 10-year government bond market post-Brexit vote. However, there was no interconnection between these markets before the Brexit vote. Therefore, the Brexit vote did affect and significantly increased the linkage between the US, France, the UK, and India’s 10-year government bond market. The increase in correlation in India-US, India-UK, and India-France’s 10-year government bond markets will help predict and have an important implication for hedgers, decision-makers, and portfolio managers if similar political events occur in the future.

Volatility spillovers between ethanol and corn prices: A Bayesian analysis

The relationship between corn and ethanol markets has become a popular topic and has been investigated in various studies. However, examining the co-volatility spillover between corn and ethanol markets remains neglected in the literature. This paper aims to fill this gap by analyzing the co-volatility spillover between corn and ethanol markets in the world’s largest ethanol producers and consumers, including the United States, Brazil, and China. To achieve this purpose, we utilize the Bayesian BEKK-GARCH(1,1) model to estimate the degree of co-volatility of corn and ethanol returns. Our empirical results indicate a significant bidirectional volatility spillover between corn and ethanol in all countries. We also find that the co-volatility between corn and ethanol returns is not stable and fluctuates over time, particularly in 2016 and 2020, which correspond to the 2010s oil glut and the COVID-19 pandemic, respectively.

Volatility Behaviour of Bitcoin as a Digital Asset

The objective of this study is to use the South African financial markets (Johannesburg Stock Exchange or JSE and USD/ZAR) as a case study to understand the volatility spillover dynamics of Bitcoin as a digital asset. Methodologically, the study applies the exponential generalized autoregressive conditional heteroskedastic (EGARCH) model, followed by a robustness check by applying the time-varying conditional correlation multivariate GARCH (VCC-MGARCH) model. The study utilizes the data set for the period 2011 to 2019, a period before the COVID‑19 pandemic. The research outcome revealed three interesting observations. First, Bitcoin and the South African stock market are independent of each other. Second, there is a bidirectional shock transmission between Bitcoin and USD/ZAR in the mean returns only, but not variance. Lastly, results confirm the existence of a bidirectional volatility spillover in both the mean and variance between the JSE stock market and the USD/ZAR market. The study outcome should enlighten investors who may want to consider Bitcoin as a diversifier in their investment and portfolio strategies.

On the Dynamic Connectedness of the Stock, Oil, Clean Energy, and Technology Markets

Using monthly data from September 2004 to February 2020, this paper investigates the connectedness of the renewable energy, common stock, oil, and technology markets. The time-domain Diebold and Yilmaz spillover index approach is used to analyze the volatility spillover between these four markets. The study’s findings reveal that the oil and clean energy markets have bidirectional volatility spillover. The oil market has been found to be a net receiver of volatility. Furthermore, the study shows that volatility spillover is stronger in extreme positive and negative shock periods than in medium shock periods. Our findings show that, during crisis periods, the volatility spillover index rises, while the total connection reached its lowest point in 2015. Our findings suggest that policymakers should be informed that, as long as oil prices remain low, alternative energy-producing industries will not require specific policies to mitigate their vulnerability to crude oil price shocks. However, large spillover in the tails—particularly in the right tail—indicates vulnerability to extreme events, such as the negative effect of oil price increases.

Return and volatility spillover between India, UK, USA and European stock markets: The Brexit impact

The 2016 Brexit referendum created potential turmoil in financial markets. The purpose of this study is to examine the impact of the Brexit referendum on the return and volatility spillover between the EU, the UK, and the USA stock markets and the Indian stock market during the pre- and post-Brexit referendum period. The VAR and bivariate GARCH BEKK models were employed. The study results suggest that before the Brexit referendum, Indian stock market returns made no significant return spillover on the other markets. On the contrary, following the referendum, Indian stock returns significantly spilled over to France, Germany, the UK, and the USA stock market returns. The study results also identified a substantial increase in the bidirectional volatility spillover between India-France, India-UK, and India-USA during the post-Brexit referendum period. Therefore, the investors’ opportunity to invest simultaneously in India, UK, EU, and US stock markets for portfolio diversification is limited. India was affected mainly by its own past shocks before the Brexit referendum. However, after the Brexit referendum, Indian markets are getting more and more integrated with other markets. In order to reap the diversification benefits, a prudent investment strategy will need to be developed in the future, especially during times of economic and political uncertainty and market crisis.

Dynamic Impacts of Economic Policy Uncertainty on Australian Stock Market: An Intercontinental Evidence

This study empirically investigates the impacts of economic policy uncertainty (EPU) of five countries from four continents on the Australian stock market with monthly observations from January 1998 to January 2021. The dynamic linkage model reports that EPUs are negatively influenced by their own lagged effect along with bidirectional volatility spillover and the returns of stock markets unidirectionally spillover to the EPU of the corresponding economy. The study documents that shocks originated in the Australian stock market spillover negatively onto its own EPU and that of China and positively onto EPUs of Europe and Japan. The shocks originated in EPUs of Australia, Europe, China, and Japan significantly negatively impact the Australian stock market. The bidirectional volatilities of EPUs can offer insight for portfolio investors in searching the possible hedging opportunities in Australia. The reported drivers of Australian EPU can be incorporated in formulating and implementing the EPU-sensitive Australian trade policies. JEL: G15, G17, G18

Spillovers and Dynamic Correlations between REITs, Exchange Rates, and Equities in Japan

This paper investigates return transmission, volatility spillovers, and dynamic correlations between the Tokyo Stock Exchange (TSE) Real Estate Investment Trust (REIT) index, the Nikkei 225 index, and the yen/dollar exchange rate. As a result, we find many new findings and these all show our significant contributions as follows. First, there is return transmission from the Nikkei 225 to the TSE REIT index. Second, there is bidirectional return transmission between the Nikkei 225 and the yen/dollar exchange rate. Third, there are bidirectional volatility spillovers between the Nikkei 225 and the TSE REIT index. Fourth, there are volatility spillovers from the Nikkei 225 to the yen/dollar exchange rate. Fifth, dynamic conditional correlations (DCCs) between TSE REIT returns and Nikkei 225 returns are not low. Moreover, DCCs between Nikkei 225 returns and yen/dollar exchange rate changes are not high. Furthermore, DCCs between TSE REIT returns and yen/dollar exchange rate changes are quite low. These our new findings shall be useful for not only deepening our understanding of financial markets but also our related future research.

The Price Discovery Processes in China, India, and Russia’s Stock Index Futures Markets

In this paper, we examine the price discovery patterns in the three BRICS countries’ stock index futures markets which were launched after 2000 – China, India, and Russia. We find the futures market dominates the price discovery process in China and India, but less so in Russia. A closer examination reveals the dynamic nature of the price discovery process, and the significant impacts on futures’ price discovery functions from China’s regulatory changes in September 2015 and Russia’s economic sanctions in March 2014. The results also show a more balanced and bidirectional volatility spillover between futures and spots in China and India than in Russia.