scholarly journals Volatility spillover effects between Islamic stock markets and exchange rates: Evidence from three emerging countries

2020 ◽  
Vol 20 (4) ◽  
pp. 322-333 ◽  
Author(s):  
Seyfettin Erdoğan ◽  
Ayfer Gedikli ◽  
Emrah İsmail Çevik
Keyword(s):  
Exchange Rates ◽  
Stock Markets ◽  
Spillover Effects ◽  
Emerging Countries ◽  
Volatility Spillover

scholarly journals RMB Exchange Rates and Volatility Spillover across Financial Markets in China and Japan

Risks ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 120 ◽  
Author(s):  
Fengming Qin ◽  
Junru Zhang ◽  
Zhaoyong Zhang
Keyword(s):  
Financial Markets ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Stock Markets ◽  
Spillover Effects ◽  
Policy Implications ◽  
Foreign Exchange Markets ◽  
Volatility Spillover ◽  
Exchange Markets ◽  
China And Japan

This study examines empirically the volatility spillover effects between the RMB foreign exchange markets and the stock markets by employing daily returns of the Chinese RMB exchange rates and the stock markets in China and Japan during the period in 1998–2018. We find evidence that there exist co-volatility effects among the financial markets in China and Japan, and the volatility of RMB exchange rates contribute to the co-volatility spillovers across the financial markets. Reversely, the return shock from the stock markets can also generate co-volatility spillover to the foreign exchange markets. The bidirectional relationship reveals that both the fundamental hypothesis and the investor-induced hypothesis are valid. Our estimates also show that the spillover effects led by the stock market in Japan are stronger than that from the foreign exchange markets and the Chinese stock markets, implying that market with higher accessibility has greater spillover effects onto other markets. We also found that the average co-volatility spillover effects among the RMB exchange markets and the stock markets in Japan and China are generally negative. These findings have important policy implications for risk management and hedging strategies.

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.

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.

scholarly journals THE INVESTIGATION OF VOLATILITY SPILLOVER EFFECT BETWEEN STOCK MARKETS OF TURKEY, ITALY, GREECE AND RUSSIA

2020 ◽  
Vol 8 (2) ◽  
pp. 1576-1598
Author(s):  
Murat BERBEROĞLU
Keyword(s):  
Heat Wave ◽  
Stock Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Meteor Shower ◽  
Volatility Spillover ◽  
Short Term ◽  
Volatility Spillover Effect

In this study, the volatility spillover effects in stock markets of various countries are examined. Volatility spillover effect occurs in two forms as heat wave and meteor shower in literature. From this point to these two effects were investigated in stock markets of Turkey, Italy, Russia and Greece. In the research, cointegration, ARCH-LM, VAR, and finally VAR-MGARCH analyzes were used. According to the results of the analysis, it was concluded that the volatility spillover effect is effective in all stock markets. Also, it was determined that more meteor shower hypothesis is more effective when the time was extended, although heat wave hypothesis is effective in the short term.                         

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 Return and Volatility Spillover among Commodity Futures, Stock Market and Exchange Rate: Evidence from India

2018 ◽  
Vol 20 (1) ◽  
pp. 214-237 ◽  
Author(s):  
Debasish Maitra ◽  
Varun Dawar
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Spillover Effects ◽  
Asset Market ◽  
Volatility Spillover ◽  
Stock Indices ◽  
Volatility Model ◽  
Exchange Rate Markets ◽  
Multivariate Volatility ◽  
Auto Regression

This article aims to investigate return and volatility spillover among commodity, stock and exchange rate markets. The article further looks into whether there is any change in return and volatility spillover during the crisis and post-crisis periods and whether there is any in the behaviour of spillover changes between agro and non-agro based commodities. The study uses Vector Auto Regression followed along with by Granger causality are to understand the causality of returns. We have performed multivariate volatility model to study the volatility co-movement of different assets. Unidirectional return spillover from the Multi Commodity Exchange (non-agro commodity) to stock indices and exchange rates is found. Stock indices are found to influence exchange rates to return; whereas the only dollar explains the return in stock indices. Equity markets have been found to have a return spillover on NCDEX (agro commodity) during the post-crisis period. However, each asset market is found to have volatility spillover effects on the other asset market. Commodity indices have more spillover effects on stocks.

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