Volatility spillovers among G7, E7 stock markets and cryptocurrencies

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Berna Aydoğan ◽  
Gülin Vardar ◽  
Caner Taçoğlu
Keyword(s):  
Financial Market ◽  
Portfolio Management ◽  
Stock Markets ◽  
Negative Impact ◽  
Spillover Effects ◽  
Volatility Spillover ◽  
Content Type ◽  
Volatility Spillovers ◽  
Dynamic Relationship ◽  
The Stability

PurposeThe existence of long memory and persistent volatility characteristics of cryptocurrencies justifies the investigation of return and volatility/shock spillovers between traditional financial market asset classes and cryptocurrencies. The purpose of this paper is to investigate the dynamic relationship between the cryptocurrencies, namely Bitcoin and Ethereum, and stock market indices of G7 and E7 countries to analyze the return and volatility spillover patterns among these markets by means of multivariate (MGARCH) approach.Design/methodology/approachApplying the newly developed VAR-GARCH-in mean framework with the BEKK representation, the empirical results reveal that there exists an evidence of mean and volatility spillover effects among Bitcoin and Ethereum as the proxies for the cryptocurrencies, and stock markets reviewed.FindingsInterestingly, the direction of the return and volatility spillover effects is unidirectional in most E7 countries, but bidirectional relationship was found in most G7 countries. This can be explained as the presence of a strong return and volatility interaction among G7 stock markets and crypto market.Originality/valueOverall, the results of this study are of particular interest for portfolio management since it provides insights for financial market participants to make better portfolio allocation decisions. It is also increasingly important to understand the volatility transmission mechanism across these markets to provide policymakers and regulatory bodies with guidance to eliminate the negative impact of cryptocurrency's volatility on the stability of financial markets.

Shock and volatility spillovers between oil and emerging seven stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muzammil Khurshid ◽  
Berna Kirkulak-Uludag
Keyword(s):  
Stock Returns ◽  
Stock Markets ◽  
Design Methodology ◽  
Spillover Effects ◽  
Volatility Spillover ◽  
Causality Test ◽  
Content Type ◽  
Volatility Spillovers ◽  
Oil Market ◽  
High Level

Purpose This study aims to examine the volatility spillover effects between oil and stock returns in the emerging seven economies. Design/methodology/approach In this study, the Granger causality test and vector autoregression-generalized autoregressive conditional heteroskedasticity approach to analyze the volatility spillover from 1995 to 2019 were used. The findings provide evidence of significant volatility spillover between oil and Brazil, China, India, Indonesia, Mexico, Russia and Turkey (E7) stock markets. Findings All emerging seven stock markets exhibit positive and low constant conditional correlations with oil assets. The magnitude of the correlation changes in respond to the country’s net position in the crude oil market. While a relatively high level of correlation exists between oil and the stock markets of net oil-exporting countries, a relatively low level of correlation exists between oil and the stock markets of net oil-importing countries. Originality/value The findings suggest that oil asset improves the risk-adjusted performance of a well-diversified portfolio of stocks. However, investors should invest a larger portion of their portfolios in E7 stock markets than in oil.

Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yosuke Kakinuma
Keyword(s):  
Southeast Asia ◽  
Stock Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Southeast Asian ◽  
Series Data ◽  
Financial Assets ◽  
Volatility Spillover ◽  
Content Type ◽  
Asset Classes

Purpose This study aims to provide empirical evidence on the return and volatility spillover effects between Southeast Asian stock markets, bitcoin and gold in the periods before and during the COVID-19 pandemic. The interdependence among different asset classes, the two leading stock markets in Southeast Asia (Singapore and Thailand), bitcoin and gold, is analyzed for diversification opportunities. Design/methodology/approach The vector autoregressive-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity model is used to capture the return and volatility spillover effects between different financial assets. The data cover the period from October 2013 to May 2021. The full period is divided into two sub-sample periods, the pre-pandemic period and the during-pandemic period, to examine whether the financial turbulence caused by COVID-19 affects the interconnectedness between the assets. Findings The stocks in Southeast Asia, bitcoin and gold become more interdependent during the pandemic. During turbulent times, the contagion effect is inevitable regardless of region and asset class. Furthermore, bitcoin does not provide protection for investors in Southeast Asia. The pricing mechanism and technology behind bitcoin are different from common stocks, yet the results indicate the co-movement of bitcoin and the Singaporean and Thai stocks during the crisis. Finally, risk-averse investors should ensure that gold constitutes a significant proportion of their portfolio, approximately 40%–55%. This strategy provides the most effective hedge against risk. Originality/value The mean return and volatility spillover is analyzed between bitcoin, gold and two preeminent stock markets in Southeast Asia. Most prior studies test the spillover effect between the same asset classes such as equities in different regions or different commodities, currencies and cryptocurrencies. Moreover, the time-series data are divided into two groups based on the structural break caused by the COVID-19 pandemic. The findings of this study offer practical implications for risk management and portfolio diversification. Diversification opportunities are becoming scarce as different financial assets witness increasing integration.

Returns and volatility spillovers among cryptocurrency portfolios

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ismail Olaleke Fasanya ◽  
Oluwatomisin Oyewole ◽  
Temitope Odudu
Keyword(s):  
Design Methodology ◽  
Asset Returns ◽  
Volatility Spillover ◽  
Content Type ◽  
Vector Autoregressive ◽  
Volatility Spillovers ◽  
Dynamic Relationship ◽  
Major Market ◽  
Daily Data ◽  
Variance Decompositions

PurposeThis paper examines the return and volatility spillovers among major cryptocurrency using daily data from 10/08/2015 to 15/04/2018.Design/methodology/approachThe 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.FindingsThe 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.Originality/valueThis 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.

The dynamics of return co-movements and volatility spillover effects in Greater China public property markets and international linkages

2014 ◽  
Vol 32 (6) ◽  
pp. 610-641 ◽  
Author(s):  
Kim Hiang Liow
Keyword(s):  
Real Estate ◽  
Spillover Effects ◽  
Real Estate Market ◽  
Market Volatility ◽  
Volatility Spillover ◽  
Content Type ◽  
Real Estate Markets ◽  
Volatility Spillovers ◽  
Public Property ◽  
Property Markets

Purpose – The purpose of this paper is to examine weekly dynamic conditional correlations (DCC) and vector autoregressive (VAR)-based volatility spillover effects within the three Greater China (GC) public property markets, as well as across the GC property markets, three Asian emerging markets and two developed markets of the USA and Japan over the period from January 1999 through December 2013. Design/methodology/approach – First, the author employ the DCC methodology proposed by Engle (2002) to examine the time-varying nature in return co-movements among the public property markets. Second, the author appeal to the generalized VAR methodology, variance decomposition and the generalized spillover index of Diebold and Yilmaz (2012) to investigate the volatility spillover effects across the real estate markets. Finally, the spillover framework is able to combine with recent developments in time series econometrics to provide a comprehensive analysis of the dynamic volatility co-movements regionally and globally. The author also examine whether there are volatility spillover regimes, as well as explore the relationship between the volatility spillover cycles and the correlation spillover cycles. Findings – Results indicate moderate return co-movements and volatility spillover effects within and across the GC region. Cross-market volatility spillovers are bidirectional with the highest spillovers occur during the global financial crisis (GFC) period. Comparatively, the Chinese public property market's volatility is more exogenous and less influenced by other markets. The volatility spillover effects are subject to regime switching with two structural breaks detected for the five sub-groups of markets examined. There is evidence of significant dependence between the volatility spillover cycles across stock and public real estate, due to the presence of unobserved common shocks. Research limitations/implications – Because international investors incorporate into their portfolio allocation not only the long-term price relationship but also the short-term market volatility interaction and return correlation structure, the results of this study can shed more light on the extent to which investors can benefit from regional and international diversification in the long run and short-term within and across the GC securitized property sector, with Asian emerging market and global developed markets of Japan and USA. Although it is beyond the scope of this paper, it would be interesting to examine how the two co-movement measures (volatility spillovers and correlation spillovers) can be combined in optimal covariance forecasting in global investing that includes stock and public real estate markets. Originality/value – This is one of very few papers that comprehensively analyze the dynamic return correlations and conditional volatility spillover effects among the three GC public property markets, as well as with their selected emerging and developed partners over the last decade and during the GFC period, which is the main contribution of the study. The specific contribution is to characterize and measure cross-public real estate market volatility transmission in asset pricing through estimates of several conditional “volatility spillover” indices. In this case, a volatility spillover index is defined as share of total return variability in one public real estate market attributable to volatility surprises in another public real estate market.

Return and volatility spillovers between Bitcoin and other asset classes in Turkey

2019 ◽  
Vol 14 (3) ◽  
pp. 209-220 ◽  
Author(s):  
Gulin Vardar ◽  
Berna Aydogan
Keyword(s):  
Spillover Effects ◽  
Portfolio Diversification ◽  
Volatility Spillover ◽  
Policy Makers ◽  
Content Type ◽  
Empirical Results ◽  
Volatility Spillovers ◽  
Regulatory Bodies ◽  
Asset Classes ◽  
Econometric Technique

Purpose With a substantial return and volatility characteristic of Bitcoin, which may be seen as a new category of investment assets, better understanding of the nature of return and volatility spillover can help investors and regulators in achieving the potential goal from portfolio diversification. The paper aims to discuss these issues. Design/methodology/approach This paper explores the return and volatility transmission between the Bitcoin, as the largest cryptocurrency, and other traditional asset classes, namely stock, bond and currencies from the standpoint of Turkey over the period July, 2010–June, 2018 using the newly developed multivariate econometric technique, VAR–GARCH, in mean framework with the BEKK representation. Findings The empirical results reveal the existence of the positive unilateral return spillovers from the bond market to Bitcoin market. Regarding the results of shock and volatility spillovers, there exists strong evidence of bidirectional cross-market shock and volatility spillover effects between Bitcoin and all other financial asset classes, except US Dollar exchange rate. Originality/value The important extention is the adoption of a newly developed multivariate econometric technique, VAR–GARCH, in mean framework with the BEKK representation, proposed by Engle and Kroner (1995), which is employed for the first time specifically to examine the extent of integration in terms of volatility and return between Bitcoin and key asset classes. Second, Bitcoin has experienced a rapid growth since around a decade and a number of investors are showing interest in its potential as an integrative part of portfolio diversification. The information provided by empirical results gives empirical bases from which to address topics concerning hedging purposes and optimal portfolio allocation. It is also increasingly important to analyze the current behavior of Bitcoin in relation to other assets to provide policy makers and regulatory bodies with guidance on the role of the Bitcoin as an investment asset in Turkey. Thus, this is the first serious attempt at exploring the potential for Bitcoin to offer diversification opportunities in the context of Turkey.

Volatility spillover from crude oil and gold to BRICS equity markets

2018 ◽  
Vol 45 (2) ◽  
pp. 426-440 ◽  
Author(s):  
Vikas Pandey ◽  
Vipul Vipul
Keyword(s):  
Financial Crisis ◽  
Crude Oil ◽  
Stock Markets ◽  
Equity Markets ◽  
Multivariate Garch ◽  
Volatility Spillover ◽  
Conditional Correlation ◽  
Price Shocks ◽  
Content Type ◽  
Dynamic Relationship

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Return and volatility spillover effects between the Turkey and the Russia stock market

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Melih Kutlu ◽  
Aykut Karakaya
Keyword(s):  
Stock Exchange ◽  
Spillover Effects ◽  
Stock Exchanges ◽  
Volatility Spillover ◽  
Full Sample ◽  
Content Type ◽  
Crisis Period ◽  
Volatility Spillovers ◽  
Volatility Analysis ◽  
Economic Developments

PurposeThis study aimed to investigate return and volatility spillover between the Borsa Istanbul (BIST) and the Moscow Stock Exchange (RTS).Design/methodology/approachThis study used generalized autoregressive conditionally heteroscedasticity (GARCH) model for volatility and the Aggregate Shock (AS) model for return and volatility spillover. The data are divided into six sub-periods. Period events take place between Turkey and Russia.FindingsBIST investors considered the return and volatility of the RTS, it is observed that Moscow Stock Exchange investors considered only the return of BIST at the full sample. It is only a return spillover from BIST to RTS and neither the return nor the volatility of the RTS is spillover to BIST in the pre-crisis period. No evidence of return and volatility spillover between the BIST and the RTS in the post-crisis period. The returns and volatility spillovers between Russia and Turkey are mutual feedback in the jet crisis period.Practical implicationsEconomic developments between Turkey and Russia is growing rapidly in recent years. The return and volatility analysis between the stock exchanges of these two countries is important for investment decisions.Originality/valueThere are many studies in the literature about emerging markets. There are also Turkish and Russian stock exchanges in these studies. However, this study only examined return and volatility spillover analysis between the Turkish and Russian stock exchanges and prevents the results from being overlooked among other countries.

MEASURING VOLATILITY SPILLOVERS BETWEEN DEVELOPED AND SOUTHEAST ASIAN EMERGING STOCK MARKETS: A MULTIVARIATE GARCH APPROACH

2018 ◽  
Author(s):  
Anh Nguyễn Thị Hoàng ◽  
Huyền Trần Thị Thanh ◽  
Minh Huỳnh Ngọc Kim ◽  
Trân Nguyễn Thị Ngọc
Keyword(s):  
Emerging Markets ◽  
Stock Markets ◽  
Spillover Effects ◽  
The United States ◽  
Southeast Asian ◽  
Multivariate Garch ◽  
Volatility Spillover ◽  
Sample Analysis ◽  
Volatility Spillovers ◽  
Developed Markets

In this paper, we measure volatility spillovers among eleven stock markets, including five developed markets (the United States, Japan, Germany, the United Kingdom, Hong Kong) and six Southeast Asian developing markets (Indonesia, Malaysia, Philippines, Singapore, Thailand and Vietnam) over the 25-year period from January 1, 1993 to December 31, 2017. Employing the GARCH-DCC model and non-parametric sign tests on the correlations between developed markets and emerging markets, we find that correlations between developed markets and the Southeast Asian markets have risen sharply during periods of crisis, indicating the existence of volatility spillover effects from the developed markets to emerging ones. Full sample analysis suggests that volatility spillover from Japanese and the UK markets to the Southeast Asian emerging markets is stronger and more apparent than those transmitted from the US and Germany markets. Sub-sample analysis is able to identify the markets transmitting shocks to others. Results also suggest that Vietnam market is not fully integrated to the regional and global markets.

scholarly journals To What Extent are Stock Returns Driven by Mean and Volatility Spillover Effects? – Evidence from Eight European Stock Markets

2013 ◽  
Vol 13 (1) ◽  
pp. 3-29 ◽  
Author(s):  
Abdulla Alikhanov
Keyword(s):  
Stock Returns ◽  
Stock Markets ◽  
Spillover Effects ◽  
Volatility Spillover ◽  
Volatility Spillovers ◽  
The Us ◽  
Variance Ratios ◽  
Market Shocks ◽  
European Stock Markets ◽  
The U.S

Abstract The paper investigates mean and volatility spillover effects from the U.S and EU stock markets as well as oil price market into national stock markets of eight European countries. The study finds strong indication of volatility spillover effects from the US-global, EU-regional, and the world factor oil towards individual stock markets. While both mean and volatility spillover transmissions from the US are found to be significant, EU mean spillover effects are negligible. To evaluate the magnitude of volatility spillovers, the variance ratios are also computed and the results draw to attention that the individual emerging countries’ stock returns are mostly influenced by the U.S volatility spillovers rather than EU or oil markets. Additionally, examination of only global and regional stock markets spillover transmissions into European stock markets also confirms the dominating presence of the U.S spillover transmissions. Furthermore, I also implement asymmetric tests on stock returns of eight markets. The stock market returns of Hungary, Poland, Russia and the Ukraine are found to respond asymmetrically to negative and positive shocks in the US stock returns. The weak evidence of asymmetric effects with respect to oil market shocks is found only in the case of Russia and the quantified variance ratios indicate that presence of oil market shocks are relatively higher for Russia. Moreover, a model with dummy variable confirms the effect of European Union enlargement on stock returns only for Romania. Finally, a conditional model suggests that the spillover effects are partially explained by instrumental macroeconomic variables, out of which exchange rate fluctuations play the key role in explaining the spillover parameters rather than total trade to GDP ratios in most investigated countries.

International stock markets Integration and dynamics of volatility spillover between the USA and South Asian markets: evidence from Global financial crisis

2020 ◽  
Vol 14 (5) ◽  
pp. 779-794
Author(s):  
Umm E. Habiba ◽  
Shen Peilong ◽  
Wenlong Zhang ◽  
Kashif Hamid
Keyword(s):  
Financial Crisis ◽  
South Asian ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Volatility Spillover ◽  
Policy Makers ◽  
Content Type ◽  
Volatility Spillovers ◽  
Emerging Stock Markets ◽  
The Usa

Purpose The purpose of this paper is to investigate the cointegration and volatility spillover dynamics between the USA and South Asian stock markets, namely, India, Pakistan and Sri Lanka. The main objective of this study is to provide the knowledge about integration of financial market and volatility spillovers before, during and after global financial crisis to investors, fund managers and policy-makers. Design/methodology/approach The Johansen and Juselius cointegration test, Granger Causality test and bivaraite EGARCH model have been applied in this study to examine integration and volatility spillovers between selected stock markets. Findings The findings show that long-term integration between the USA market and South Asian emerging stock markets. It is found that USA stock market has causal relationship with emerging stock markets in short-term. The findings of EGARCH model reveal that asymmetric volatility spillover effects significant in all selected stock markets in pre, during and post-crisis periods. Furthermore, significant volatility spillover is found from stock markets of USA to all selected South Asian markets during and post-crisis periods. However, volatility spillovers from USA to India and Sri-Lanka markets are significant, while insignificant in case of Pakistani market in pre-crisis period. Overall, we find that returns and volatility spillover effects are higher in financial crisis period as compared to non-financial crisis period. Practical implications The findings of this paper have important implications for investors, portfolio managers and policy-makers. They can take potential benefits from international portfolio diversification by considering all these facts. The understanding and knowledge of across volatility transmission help them to maximize the gains from diversification and minimize the risk. Policy-makers can develop such strategies which protect the markets of these economies from future financial crisis. Originality/value Although in finance literature numerous studies have been conducted on integration between different stock markets, most of the studies investigated the integration and volatility spillovers between developed stock markets. However, many studies also analyzed the integration among emerging stock markets in literature review but it is hard to find studies in the context of South Asian stock markets on the effect of global financial crisis on stock markets. The main contribution of this study is to investigate the stock markets integration and volatility transmission between the USA and South Asia by considering the effect of recent 2007 US subprime financial crisis.

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