The spillover effects and connectedness among green commodities, Bitcoins, and US stock markets: Evidence from the quantile VAR network

2022 ◽  
Vol 306 ◽  
pp. 114493
Author(s):  
Rabeh Khalfaoui ◽  
Sami Ben Jabeur ◽  
Buhari Dogan
Keyword(s):  
Stock Markets ◽  
Spillover Effects

China’s growing influence and risk in Asia–Pacific stock markets: evidence from spillover effects and market integration

2020 ◽  
Vol 22 (4) ◽  
pp. 338-361
Author(s):  
Xiaomeng Ma ◽  
Dong Zou ◽  
Chuanchao Huang ◽  
Shuliang Lv
Keyword(s):  
Stock Markets ◽  
Market Integration ◽  
Spillover Effects ◽  
Asia Pacific

scholarly journals The Effects from The U.S. and Japan to Emerging Stock Markets in Asia and Vietnam

2021 ◽  
Author(s):  
SDAG Lab
Keyword(s):  
Emerging Markets ◽  
Stock Prices ◽  
Stock Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
The Philippines ◽  
Volatility Spillovers ◽  
Return Effect ◽  
Asian Emerging Markets ◽  
The U.S

The subprime mortgage crisis in the U.S. in mid-2008 suggests that stock prices volatility do spillover from one market to another after international stock markets downturn. The purpose of this paper is to examine the magnitude of return and volatility spillovers from developed markets (the U.S. and Japan) to eight emerging equity markets (India, China, Indonesia, Korea, Malaysia, the Philippines, Taiwan, Thailand) and Vietnam. Employing a mean and volatility spillover model that deals with the U.S. and Japan shocks and day effects as exogenous variables in ARMA(1,1), GARCH(1,1) for Asian emerging markets, the study finds some interesting findings. Firstly, the day effect is present on six out of nine studied markets, except for the Indian, Taiwanese and Philippine. Secondly, the results of return spillover confirm significant spillover effects across the markets with different magnitudes. Specifically, the U.S. exerts a stronger influence on the Malaysian, Philippine and Vietnamese market compared with Japan. In contrast, Japan has a higher spillover effect on the Chinese, Indian, Korea, and Thailand than the U.S. For the Indonesian market, the the return effect is equal. Finally, there is no evidence of a volatility effect of the U.S. and Japanese markets on the Asian emerging markets in this study.

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.

COMPARING THE IMPACTS OF OIL PRICE SHOCKS ACROSS STOCK MARKETS

2015 ◽  
Vol 77 (20) ◽  
Author(s):  
Siok Kun Sek ◽  
Zhan Jian Ng ◽  
Wai Mun Har
Keyword(s):  
Stock Returns ◽  
Stock Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Oil Price ◽  
Multivariate Garch ◽  
Oil Price Shocks ◽  
Price Shocks ◽  
Long Run ◽  
Short Run

We conduct empirical analyses on comparing the spillover effects of oil price shocks on the volatility of stock returns between oil importing and oil exporting countries. In particular, we seek to study how the nature of oil price shocks differs due to the oil dependency factor and how the stock markets react to such shocks. Applying the multivariate GARCH-BEKK(1,1) model, our results detect spillover effects between crude oil price and stock returns for all countries. The short run persistencies of shocks are smaller but the persistencies of shocks are very high in the long run. The results hold for both groups of countries. The results imply larger spillover effect from oil price shock into stock market in the oil importing countries.

scholarly journals Volatility Similarity and Spillover Effects in G20 Stock Market Comovements: An ICA-Based ARMA-APARCH-M Approach

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Shanglei Chai ◽  
Zhen Zhang ◽  
Mo Du ◽  
Lei Jiang
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Financial Markets ◽  
Stock Markets ◽  
Time Series Data ◽  
Multivariate Time Series ◽  
Spillover Effects ◽  
Series Data ◽  
Dominant Source ◽  
Financial Internationalization

Financial internationalization leads to similar fluctuations and spillover effects in financial markets around the world, resulting in cross-border financial risks. This study examines comovements across G20 international stock markets while considering the volatility similarity and spillover effects. We provide a new approach using an ICA- (independent component analysis-) based ARMA-APARCH-M model to shed light on whether there are spillover effects among G20 stock markets with similar dynamics. Specifically, we first identify which G20 stock markets have similar volatility features using a fuzzy C-means time series clustering method and then investigate the dominant source of volatility spillovers using the ICA-based ARMA-APARCH-M model. The evidence has shown that the ICA method can more accurately capture market comovements with nonnormal distributions of the financial time series data by transforming the multivariate time series into statistically independent components (ICs). Our findings indicate that the G20 stock markets are clustered into three categories according to volatility similarity. There are spillover effects in stock market comovements of each group and the dominant source can be identified. This study has important implications for investors in international financial markets and for policymakers in G20 countries.

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