Measurement of Systemic Risk in Global Financial Markets and Its Application in Forecasting Trading Decisions

Liu, Jianxu; Song, Quanrui; Yang, Qi; Rahman, Sanzidur; Sriboonchitta, Songsak

doi:10.3390/su12104000

Cited by 11 publications

(5 citation statements)

References 49 publications

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“…There are other studies that have used stock markets for systemic risk analysis. For example, Liu et al (2020) analyse stock market indices of 43 countries to represent global financial markets, while Zhao et al (2019) analyse the systemic risk of the Chinese stock market and Eratalay and Vladimirov (2020) focused on the Russian stock market.…”

Section: Systemic Riskmentioning

confidence: 99%

The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms

Eratalay

Ángel

2022

JRFM

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There are diverging results in the literature on whether engaging in ESG related activities increases or decreases the financial and systemic risks of firms. In this study, we explore whether maintaining higher ESG ratings reduces the systemic risks of firms in a stock market context. For this purpose we analyse the systemic risk indicators of the constituent stocks of S&P Europe 350 for the period of January 2016–September 2020, which also partly covers the COVID-19 period. We apply a VAR-MGARCH model to extract the volatilities and correlations of the return shocks of these stocks. Then, we obtain the systemic risk indicators by applying a principle components approach to the estimated volatilities and correlations. Our focus is on the impact of ESG ratings on systemic risk indicators, while we consider network centralities, volatilities and financial performance ratios as control variables. We use fixed effects and OLS methods for our regressions. Our results indicate that (1) the volatility of a stock’s returns and its centrality measures in the stock network are the main sources contributing to the systemic risk measure, (2) firms with higher ESG ratings face up to 7.3% less systemic risk contribution and exposure compared to firms with lower ESG ratings and (3) COVID-19 augmented the partial effects of volatility, centrality measures and some financial performance ratios. When considering only the COVID-19 period, we find that social and governance factors have statistically significant impacts on systemic risk.

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Section: Systemic Riskmentioning

confidence: 99%

The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms

Eratalay

Ángel

2022

JRFM

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“…COVID-19 periods and comparatively less correlated US-China EPU period. The results indicate that a superior level of risk presents in emerging markets during the crisis period than in the EPU period and post-crisis period [70]. This indicates that Asian markets are closely connected to the more developed US stock market.…”

Section: Plos Onementioning

confidence: 81%

“…The outcomes show that while the sample markets are segmented before the global financial crisis and US-China EPU periods, they have become highly correlated during the global financial crisis and COVID-19 periods and comparatively less correlated US-China EPU period. The results indicate that a superior level of risk presents in emerging markets during the crisis period than in the EPU period and post-crisis period [ 70 ]. This indicates that Asian markets are closely connected to the more developed US stock market.…”

Section: Discussionmentioning

confidence: 99%

Emerging stock market reactions to shocks during various crisis periods

Bhowmik

Debnath

et al. 2022

PLoS ONE

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This study investigates granger causal linkages among six Asian emerging stock markets and the US market over the period 2002–2020, taking into account several crisis periods. The pairwise Granger causality tests for investigating the short-run causality show significant bi- and uni-directional causal relationships in those markets and evidence that they have become more internationally integrated after every crisis period. An exception is Bangladesh with almost no significant short-term causal linkages with other markets. For understanding, how the financial linkages amplify volatility spillover effects, we apply the GARCH-M model and find that volatility and return spillovers act very inversely over time. However, market interface is weak before the crisis periods and becomes very strong during the financial crisis and US-China economic policy uncertainty periods. The US market plays a dominant role during the financial crisis and COVID-19 periods. Further analysis using the VAR model shows that a large proportion of the forecast variance of the Asian emerging stock markets is affected by the S&P 500 and that market shock starts to rise notably from the 1 to 10 period. The overall findings could provide important policy implications in the six countries under study regarding hedging, trading strategies, and financial market regulation.

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“…If the residuals are normally distributed, the Wald statistics is an asymptotic χ 2 distribution. However, financial data are not normally distributed, and there exist autoregressive conditional heteroskedasticity (ARCH) effects (Liu et al 2020). A bootstrap test is a better way than the standard test when the data are not normal and there is constant variance (Hatemi-J et al 2017).…”

Section: Asymmetric Causality Testmentioning

confidence: 99%

Comparison of the Asymmetric Relationship between Bitcoin and Gold, Crude Oil, and the U.S. Dollar before and after the COVID-19 Outbreak

Liu,

Naktnasukanjn,

Tamprasirt

et al. 2023

JRFM

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This paper aims to reveal the asymmetric co-integration relationship and asymmetric causality between Bitcoin and global financial assets, namely gold, crude oil and the US dollar, and make a comparison for their asymmetric relationship before and after the COVID-19 outbreak. Empirical results show that there is no linear co-integration relationship between Bitcoin and global financial assets, but there are nonlinear co-integration relationships. There is an asymmetric co-integration relationship between the rise in Bitcoin prices and the decline in the US Dollar Index (USDX), and there is a nonlinear co-integration relationship between the decline of Bitcoin and the rise and decline in the prices of the three financial assets. To be specific, there is a Granger causality between Bitcoin and crude oil, but not between Bitcoin and gold/US dollar. Before the outbreak of the COVID-19 pandemic, there was an Asymmetric Granger causality between the decline in gold prices and the rise in Bitcoin prices. After the outbreak of the pandemic, there is an asymmetric Granger causality between the decline in crude oil prices and the decline in Bitcoin prices. The COVID-19 epidemic has led to changes in the causality between Bitcoin and global financial assets. However, there is not a linear Granger causality between the US dollar and Bitcoin. Last, the practical implications of the findings are discussed here.

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Measurement of Systemic Risk in Global Financial Markets and Its Application in Forecasting Trading Decisions

Cited by 11 publications

References 49 publications

The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms

The Impact of ESG Ratings on the Systemic Risk of European Blue-Chip Firms

Emerging stock market reactions to shocks during various crisis periods

Comparison of the Asymmetric Relationship between Bitcoin and Gold, Crude Oil, and the U.S. Dollar before and after the COVID-19 Outbreak

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