Dynamic Volatility Spillovers Research Articles

Dynamic volatility spillover connectedness of sectoral indices of commodity and equity: evidence from India

Dynamic volatility spillover connectedness of sectoral indices of commodity and equity: evidence from India

A Bibliometric Review of Volatility Spillovers in Financial Markets: Knowledge Bases and Research Fronts

ABSTRACT This paper uses the bibliometric method of knowledge mapping analysis to clearly present the knowledge base and research fronts of cross-market volatility spillovers. The results provide strong evidence that, first, the general theme of volatility spillovers can be divided into a variety of research topics, four of which are on the dynamics of volatility spillovers in world financial markets of various types based on multivariate GARCH or VAR models and construct a crucial knowledge base for this field; second, three research fronts can be identified using burst analysis, and they focus on examining spillover directions and magnitudes, testing volatility spillovers related to oil markets and international risk transmission mechanism of emerging markets; and, third, the major contributing scholars come from institutions in the United States,China and European economies. Our conclusions offer some recommendations for market practitioners in their risk management and policy-making.

Dynamics of volatility spillover in commodity markets: Linking crude oil to agriculture

This paper examines spillover effects among markets of crude oil and ten major agricultural commodities by employing the Diebold and Yılmaz (2009, 2012) spillover frameworks to returns and EGARCH filtered volatilities. We account for structural variations in data by dividing the data into two subsamples: from July 1986 to December 2005 (pre-2006 subsample) and from January 2006 to June 2016 (post-2006 subsample). Our findings indicate that there is minuscule information transmission among crude oil and agricultural commodities over the pre-2006 subsample, however, crude oil becomes the net receiver of information over the post-2006 subsample. Second, our findings indicate asymmetric and bidirectional flow of information among crude oil and agricultural commodities that intensifies during periods of financial and economic turmoil. Last, net volatility spillover increases in periods of large declines in the crude oil price, such as in 2008 and later in 2014. Overall, we document a more detailed insight into channels of connectedness among the underlying commodities, which may assist developing policy recommendation, portfolio designs, and risk management decisions.

Dynamics of Volatility Spillover Between Stock and Foreign Exchange Market: Empirical Evidence from Central and Eastern European Countries

Dynamics of Volatility Spillover Between Stock and Foreign Exchange Market: Empirical Evidence from Central and Eastern European Countries

Political tensions, stock market dependence and volatility spillover: Evidence from the recent intra-GCC crises

This study examines the impact of the two recent political and economic crises of March 2014 and June 2017 on the stock market dependence and volatility spillover between Qatar and the other GCC countries (Saudi Arabia, the United Arab Emirates, Bahrain, Kuwait and Oman). To this end, the Bai and Perron testing procedure for structural breaks and two dummy variables reflecting the two intra-GCC crises were used to examine the impact of these two crises on the dynamic conditional correlation of the stock market obtained from estimating several different multivariate GARCH models (namely, DCC-, ADCC- and cADCC-GARCH). In addition, to assess the volatility spillover and the degree of connectedness between the different stock markets, we use the static and dynamic volatility spillovers developed by Diebold and Yilmaz (2012, 2014). Using data of stock markets returns covering the period from January 2011 to September 2018, the empirical results show that only the recent GCC crisis of June 2017 significantly affected the level of stock market dependence and volatility spillovers between Qatar and the other GCC countries, except for Bahrain. In particular, the results suggest that the economic blockade on Qatar since June 2017 only lowered the level of dependence and did not totally sever the financial links between the countries. The results show also that after the second GCC crisis, the Qatar net spillover was approximately zero except for Saudi Arabia, which was negative. The results have implications for investors and policymakers in the region.

Stock Returns and Asymmetric Volatility Spillover Dynamics Between Asian Emerging Markets

This study investigates the dynamics of volatility spillover among Asian emerging stock markets over the period from 1 January 2002 to 29 December 2017. This study applies extended EGARCH model to estimate the asymmetric volatility spillovers. The findings of this study are interesting. This study finds statistically significant own past volatility spillovers in all selected stock markets. We find bidirectional significant spillovers of volatility in most of the selected markets. Moreover, we find significant asymmetric volatility spillover in all case of stock markets. Furthermore, the findings reveal statistically insignificant volatility spillover from China to India, China to Indonesia, China to Pakistan, Pakistan to China, Pakistan to Indonesia, Pakistan to Korea and Pakistan to Taiwan in this study period. The knowledge of return linkages and volatility spillover amongst Asian emerging financial markets has great implications for global investors, portfolio managers and policymakers.

INTER-MARKETS VOLATILITY SPILLOVER IN U.S. BITCOIN AND FINANCIAL MARKETS

This paper investigates the volatility spillover dynamics between U.S. Bitcoin and financial markets from July 19, 2010 to December 29, 2017. Diebold and Yilmaz (2012) volatility spillover index, Barunik, Kocenda, and Vacha (2017) Spillover Asymmetry Measure, and Barunik and Krehlik (2018) frequency connectedness methodologies are applied to investigate the time varying dynamics of volatility spillover among U.S. Bitcoin and financial markets. The findings of the study indicate the presence of low level of integration and contagion between U.S. Bitcoin and financial markets. Asymmetric nature of volatility spillover is also detected. The connectedness among the U.S. Bitcoin and financial markets is found to be concentrated at high frequency, suggesting that markets process information rapidly. Moreover, the turbulence in Bitcoin market will have insignificant effect on U.S. financial markets. This non-contagion nature of Bitcoin markets provides significant risk hedging and diversification benefits for domestic and foreign investors in the U.S.

Volatility spillover in crypto-currency markets: Some evidences from GARCH and wavelet analysis

We study the dynamics of volatility spillover across four major cryptocurrency returns namely Bitcoin, Ethereum, Ripple and Litecoin from 15−08−2015 to 18−01−2018 . In the first step, an IGARCH (1,1)-DCC (1,1) multivariate GARCH model is estimated to quantify the nature of volatility spillovers. From GARCH results, it is seen that there is statistically significant volatility spillover from Bitcoin to Ethereum and Litecoin during the period of analysis. The conditional correlation measures point towards the possibility of moderate return co-movement among the crypto-currency returns. The conditional covariance measures show negligible volatility spillover during the initial periods and provide evidence towards increased volatility spillover after 2017. Wavelet coherence measures shows evidence towards correlation among the crypto-currencies to be persistent across the short run, while the pairwise wavelet cross-spectral analysis confirms the findings obtained from conditional covariance measures. It is found that other crypto-currencies are influenced by fluctuations in bitcoin prices. Overall, the results indicate the possibility of turbulence in the crypto-currency markets and point towards the possibility of herding behaviour in crypto-currency markets.

Dynamic Volatility Spillover Network of Chinese Financial Institutions

Dynamic Volatility Spillover Network of Chinese Financial Institutions

The network connectedness of volatility spillovers across global futures markets

This paper analyzes the dynamic volatility spillovers and network connectedness between stock index and commodity futures markets using the multivariate DECO-FIGARCH model and the spillover index method of Diebold and Yilmaz (2014). We estimate a positive equicorrelation between the index and commodity futures and find the highest level of spillover index during the 2008–2009 global financial crisis and 2010–2012 European sovereign debt crisis. Further, we adopt both static and dynamic spillover approaches to identify the net spillover transmitter or receiver across global futures markets. We also measure the directional spillover and assess the net pairwise spillover across global futures markets. Finally, our network connectedness provides specific information on the net pairwise connectedness and intensity of connectedness in different sub-periods.

Dynamics of Volatility Spillovers with structural breaks in Indian Foreign exchange market

This research examines volatility spillovers with structural breaks in case of United States dollar (USD), Great Britain pound (GBP), Euro (EURO) and Japanese yen (JPY) of the Indian foreign exchange market from 3 January 1999 to 27 July 2018. First, the Bai and Perron test has been applied to know the structural break dates. We have found significant evidence of structural breaks in case of the respective currencies indicating one structural break in case of USD, two structural breaks in case of EURO, JPY and no structural break in case of GBP. Later on, the volatility has been checked applying the GARCH and EGARCH models on the total sample and the various sub-samples as defined by the structural breaks. In comparison to the full sample, the results of the model parameters estimates vary substantially across the various sub-samples.

Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective

We examine the frequency dynamics of volatility spillovers between crude oil and China's stock markets in a spectral representation framework of generalized forecast error variance decomposition using sectoral stock indices data. We find evidence of total volatility spillover driven mainly by short-term spillovers. The net spillovers of the oil market are almost all positive and dominated by short-ter.m components, although the spillover during China's 2015 financial crisis is negative and attributable to long-term components. In addition, there exists heterogeneity in net pairwise (frequency) spillovers between the oil and sectoral stock markets. Moreover, structural breaks in volatilities appear to be a significant feature of volatility spillovers. Finally, frequency spillovers in our system can predict future stock market volatility. These results have economic implications for investors and policymakers.

Fed’s Unconventional Monetary Policy and Risk Spillover in the US Financial Markets

This study examines volatility spillover dynamics among the S&P 500 index, the US 10-year Treasury yield, the US dollar index futures and the commodity price index. The focus of the study is to analyze effects of Fed’s unconventional monetary policy on the US financial markets. We use realized volatility measures based on daily data covering the period from December 29, 1996 to November 12, 2018. To address nonlinear and asymmetric spillover dynamics in low and high volatility states, we propose a new regime-dependent spillover index based on a smooth transition vector autoregressive (STVAR) model, extending the study of Diebold and Yilmaz (2009,2012) to regime switching models. When applied to US financial data, we find strong evidence that the US financial market risk structure changes after the announcement of quantitively easing (QE) through the portfolio balance channel. The risk spillover moves from purchased assets to non-purchased assets after the QE announcements.

Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis

This study examines the nature and dynamics of volatility spillovers between crude oil and agricultural commodity markets since the 2008–09 financial crisis. We tested for volatility spillovers with a flexible bivariate heterogeneous autoregressive model to identify the short-, mid-, and long-term spillover effects. We observed bidirectional spillovers of short-term volatilities between crude oil and agricultural commodity markets in the crisis period, compared to mid-term and long-term volatilities of corn being transmitted to the crude oil volatility in the post-crisis period. These findings suggest that crude oil and agricultural commodity markets have become less integrated after the 2008–09 crisis.

Volatility spillover between stock and foreign exchange market of China: evidence from subprime Asian financial crisis

PurposeThis paper aims to examine the volatility spillover dynamics between stock and foreign exchange market of China considering subprime 2007 financial crisis period.Design/methodology/approachThis study considered daily data from January 2, 2002, to December 31, 2013. The sample period has been further divided into three periods; full sample period (January 2002-December 2013), pre-crisis period (January 2002-October 2007) and post-crisis period (October 2007-December 2013). This study opted Exponential Generalized Autoregressive Heteroskedasticity (EGARCH) model for the purpose of investigating asymmetric volatility spillover.FindingsThe results obtained using the EGARCH model imply that volatility spillover dynamics varies from period to period. In full sample period, the results show evidence of significant unidirectional volatility spillover from foreign exchange market to stock market. In pre-crisis period, the results indicate unidirectional volatility spillover from stock market to foreign exchange market. However, in post-crisis period, the results reveal significant bidirectional volatility spillover between stock and foreign exchange market.Practical implicationsThe results of the study are important for policy makers because understanding the behavior of the financial markets, i.e. stock and foreign exchange market, would increase the success of policies implemented in a crisis situation. The results would help investors to formulate efficient portfolios.Originality/valueThis study is an important contribution to the existing literature in terms of analyzing volatility spillover between stock and foreign exchange market in an emerging economy, China. Furthermore, this study explored the volatility spillover dynamics between the two markets by considering the pre and post subprime Asian crisis period.

Dynamic Volatility Spillovers and Structural Breaks across Asian Emerging CDS Markets

This study examines the contagion effect across the six Asian credit debt swaps (CDS) markets using the multivariate DECO-GARCH model. In addition, we also identify potential structural breaks, which are associated with the 2007-2009 global financial crisis (GFC). This crisis might intensify the dynamic equicorrelations, increasing the linkages of CDS markets. Our empirical results show strong evidence of equicorrelation in the volatility and significant dynamic spillovers across emerging CDS markets. Moreover, we find several structural breaks in Asian emerging CDS markets using ICSS algorithm. These structural breaks are associated with GFC of 2007-2008. Finally, these volatility spillover trends are more pronounced in the aftermath of the recent financial crisis, namely the GFC of 2007-2008. This implies that structural breaks intensify the spillovers across Asian CDS markets and diminishes the portfolio benefits in these credit markets. Thus, our finding supports the contagion effect of CDS markets during the market turmoils.

Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets

This paper investigates the volatility spillover and connectedness among global and regional stock markets and those of Greece, Ireland, Portugal, Spain, and Italy (GIPSI). For this investigation, we perform a static and rolling-window analysis to measure volatility spillovers using the Diebold and Yilmaz (2012, 2014) methodology. We also examine the network connectedness at different stages of recent crises. Our finding indicates that recent crises intensify volatility spillovers, supporting the financial contagion effects. Furthermore, the GIPSI (except Spain and Greece markets), global and regional U.S. markets are net transmitter of shocks while the rest stock markets are net receiver of shocks.

Islamic and conventional equity index co-movement and volatility transmission: Evidence from Pakistan

This study investigates the Islamic and conventional Index integration over the period 3rd September, 2008 to 30th September, 2015. This study uses Johansen and Juselius cointegration method for exploring the long run association. The short run association is explored using VECM model. The volatility spillover dynamics is examined using the GARCH and EGARCH models. The robustness of the results is analyzed by using Granger causality method, Variance Decomposition method, and Impulse Response Function. The estimation results show significant long run and short run association between Islamic and Conventional index. Furthermore, this study finds asymmetric bidirectional volatility spillovers between Islamic and conventional index. The findings suggest that domestic investors have low diversification opportunities by adding both Islamic and conventional index in their portfolios. However, international investors can add one of the indices in their portfolios, in order to benefit from portfolio diversification.

The Dynamics of Volatility Spillover between African Stock Markets in the Context of Political Uncertainty: The Case of Nigeria and South Africa

The economies of Nigeria and South Africa have, in the last decade and a half, been a significantly important destination for investment, chiefly because of their size, political and economic stability they enjoyed during the period. Investors have therefore come to regard the two economies as both complements and alternatives competing for their investible funds. There are, however, a number of political, economic and security challenges facing Nigeria, which have raised the political and economic uncertainty that such investors have to face. These events include the heightened political tension in the period running to the 2015 general elections, the rising terror attacks on people, properties and businesses by Boko Haram in the North East and Niger Delta insurgents in the South-South of Nigeria. South Africa has also experienced spates of violent civil uprisings. These events, being key determinants of (portfolio) investment could have an important implication on the level of investment flows between the two countries and, hence, the volatility dynamics of their respective stock markets. This paper tests the hypothesis that the volatilities introduced by these events have significant spillover effects between the Nigerian and South African Stock Markets. The paper, hence, first examines the impact of political uncertainty on the stock markets, and then examines the nature and dynamics of the volatility spillover between two African stock markets. The paper employs two multivariate GARCH model of Conditional Correlation (CC). Our main findings are as follows. First, by distinguishing between South African and Nigeria’s stock markets indices, it was found that investments in these two markets react heterogeneously to the political turmoil. Specifically, the paper documents a significantly high volatility in the two market returns; the CC of the volatility spillover between the two markets was found to be negative and statistically significant; that regardless of the impact of political uncertainty on the volatility spillover, there is little evidence to suggest that the two markets have become more integrated within the period. In general, these results are robust to model specifications and are consistent with the notion that political uncertainty (caused by corruption, bribery and misappropriation of resources) contributing to the significant financial volatility spillover. Overall, the findings are important in understanding the role of political uncertainty on stock market stability and are of great significance to investors and market regulators.

Volatility Spillovers Across European Stock Markets Around the Brexit Referendum

The vote of the people of the United Kingdom to leave the European Union following the referendum on June 23, 2016, created tremendous uncertainty in the financial markets. This paper documents the stock market interdependence across four major European markets around this rare and unique event. We uncover the characteristics of the volatility spillover dynamics across France, Germany, Switzerland and the United Kingdom using intraday data at 15-minute intervals. Specifically, we quantify four types of volatility spillover measures: total (non-directional) spillovers, gross directional spillovers, net directional spillovers, and net pairwise spillovers. Our results point to considerable interdependence among the four stock markets. We find that France and Germany were in general the net volatility transmitters to others, while Switzerland and the United Kingdom the net receivers from others during January 4, 2016 to September 30, 2016. Around the day of the Brexit referendum, France and the United Kingdom appear to be net transmitters, while Germany and Switzerland net receivers. Our empirical analysis uncovers important information regarding stock market interdependence, which will be beneficial to both policymakers and practitioners.