Risk transmission between equity market of China and its trading partners: new evidence from various financial crises

PurposeThe authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).Design/methodology/approachThe authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.FindingsAccording to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.Originality/valueThe authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.

Dynamic Dependency between the Shariah and Traditional Stock Markets: Diversification Opportunities during the COVID-19 and Global Financial Crisis (GFC) Periods

The aim of the present research is to highlight whether there exist any diversification opportunities from investing in developed and developing countries' Shariah-compliant and non-Shariah-compliant stock markets during global financial crisis (GFC) and the COVID-19 pandemic periods. For this purpose, we employ daily data for both Shariah and non-Shariah indices from 29 October 2007 to 31 December 2021. The study uses multivariate GARCH-DCC and wavelet approaches to examine if there exist diversification opportunities in the selected markets. Evidence from this study shows that although the developing markets' stock returns experience high volatility of a similar degree, the conventional indices of Malaysia have the highest volatility among them. This shows that Shariah indices have less exposure to risk and higher possibilities of diversification compared to their conventional counterparts. Regarding developed markets, the Japanese conventional index and the U.S. Shariah indices are more volatile compared to other indices in the market. Moreover, the results of the wavelet power spectrum show significant and higher volatility during the COVID-19 pandemic rather than the GFC. Similarly, the Chinese conventional market experienced minimum variance during the GFC and COVID-19 pandemic period. On the other hand, the results of wavelet-coherence transform indicate that the Japanese Shariah-based market offered better portfolio opportunities for U.S. traders during the GFC and the COVID-19 pandemic periods. Hence, opportunities for investment in this selected market are basically close to zero. Therefore, investors should carefully choose which stocks they can include in their investment portfolio. © 2023 by the authors.

The Spillover Effects of US Unconventional Monetary Policy on Inflation and Non-Inflation Targeting Emerging Markets

This study employs the panel vector autoregressive (PVAR) model to examine the spillover effect of US unconventional monetary policy on inflation and non-inflation targeting emerging markets post credit crunch and during COVID-19 from 2000Q1 to 2020Q4. Unlike other analyses, this paper adds to the existing body of knowledge by employing a dummy variable to represent the United States' quantitative easing. Other included control variables are equity prices, the federal reserve rate, the exchange rate, central bank assets and the short-term interest rate. This paper estimated two-panel VARs, Model one and Model two, for inflation and non-inflation targeting emerging markets, respectively. Model one consists of eight inflation-targeting markets, and Model two consists of four non-inflation-targeting countries. Other included control variables are equity prices, the federal reserve rate, the nominal effective exchange rate, and the central bank policy rate. According to the empirical results, the US unconventional monetary policy induces a surge in the exchange rate and a decrease in the central bank policy rate for both inflation and non-inflation targeting emerging markets. However, there was no significant impact on the equity prices. The empirical results are statistically significant, robust, and consistent with previous studies except for the response of equity prices. Unconventional monetary policy is effective in steering macroeconomic variables in developed economies. The monetary policymakers in emerging markets must also use the currency reserve to stabilise the macroeconomic variables in response to US unconventional monetary policy shocks.

Combination forecast based on financial stress categories for global equity market volatility: the evidence during the COVID-19 and the global financial crisis periods

The 2008 global financial crisis and the COVID-19 pandemic both decrease economic growth and lead to high uncertainty in global stock markets, and financial stress information is closely linked to financial crises. To improve the predictability of the realized volatility of the global equity indices during crises, we examine the predictive role of the Global Financial Stress Index (GFSI) and its categories. We find that the combination predictions based on GFSI's five incorporated categories and three region-based categories outperform the predictions based on the raw GFSI for most indices. Specifically, the DMSPE combination model with a low discount factor has accurate forecasts for 5- and 22-day-ahead realized volatility, and it also performs better than the equal-weighted and the trimmed mean combination methods. In this study, we present a comprehensive analysis of the predictive role of financial stress information in stock market volatility during crises, and the empirical evidence provides a positive case against the ‘forecast combination puzzle'. Our findings are very instructive for policymakers and investors to make their own short-term and long-term plans in crisis. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Do cryptocurrencies integrate with the indices of equity, sustainability, clean energy, and crude oil? A wavelet coherency approach

The paper examines market co-movement between pairs of financial assets in the time-frequency domain. Recent finance literature confirms the integration of cryptocurrencies and financial assets, which may bring more investments with the possibility of surplus liquidity in the cryptocurrency segment, leading to financial instability. The novelty of this paper is examining the integration of cryptocurrencies and the indices of equity, sustainability, renewable energy, and crude oil for the daily observations from 2015 to 2021 by using the wavelet coherency method. The empirical results signify no integration in the short-term scales and grow stronger in the medium-term scales, especially during the COVID-19 period, and further exhibit weaker heterogeneous associations in the long-term scales. However, the sustainability, clean energy indices follow similar dynamics of the equity market and crypto pairs. In contrast, the global crude oil index showcases the minor integration with cryptocurrencies compared with other traditional asset classes. Hence, the cryptocurrency market fails to confirm the safe haven features, especially during the COVID-19 periods (Medium-term), which facilitate the domestic and international investors expecting to hedge their price risk in equity markets using cryptocurrencies may have to look for short-term. The lead-lag heterogeneous effects of the asset-pairs may pave arbitrage opportunities for investors.

COVID-19 Vaccines, Healthcare Policies and Stock Markets: Are There Winners and Losers?

Purpose: This paper focuses on the stock market performance of a set of biopharmaceutical companies listed in the US stock exchange in response to news about the unfolding of the COVID pandemic and the development of COVID-19 vaccines. Methods: We analyze the short-term impact of some episodes by means of event analysis. We consider two categories of events: news related to the expansion of the pandemic and information about the development of COVID-19 vaccines. Results: We find that the impact during the first months of the pandemic news impacted the returns of the pharmaceutical firms, but the effect was not large, in general. The only exceptions are two small biotechnological firms, Moderna and Novavax, are exceptions since they registered large positive abnormal returns, which vanished over time. Encouraging announcements about the success of Phase III results had a positive impact the share prices of Pfizer, Moderna and Novavax. Our results also suggest that the emergency authorization provided by the US regulatory agency to the Pfizer vaccine was anticipated several days in advance and welcomed by the market. The announcement of a deal to supply vaccines between Moderna and the European Commission have generated large positive returns for this company. Conclusion: Our findings have policy implications. First, financial markets have supported and reinforced government strategies to fight the pandemic, characterized by funding of promising projects, building diversified vaccine portfolios and expediting approvals by regulatory agencies. Second, our findings suggest that not all drug developers have automatically obtained large profits from the design and manufacturing of COVID-19 vaccines, according to the behaviour of stock prices. These results cast doubts over attempts to discredit the efficacy of COVID-19 vaccines with the argument that they are primarily a means to obtain large and quick profits by pharmaceuticals, or than vaccination campaigns are driven by economic goals rather than by public health considerations.

Can internet concern about COVID-19 help predict stock markets: new evidence from high-concern and low-concern periods

The unprecedented outbreak of Corona Virus Disease 2019 (COVID-19) has resulted in extreme volatility in stock markets. This study mainly examines the predictive ability of the Internet concern about COVID-19 on stock index returns, based on the framework of GARCH type models. Instead of using the whole sample period, we divide the Internet concern about COVID-19 into high-concern and low-concern periods by breakpoint test method and then examine its predictive ability for stock returns in different periods, respectively. Using stock indexes of 10 countries and abnormal Google search volume of 'coronavirus' as study samples, the results reveal that (1) the Internet concern about COVID-19 has a negative impact on the stock index returns in the whole and high-concern periods, while its influence in the low-concern period is mixed;(2) the Internet concern about COVID-19 improves the prediction accuracy of stock index returns in the high-concern period, while seems to lose its powerful predictive ability in the whole and low-concern periods.

Herding behavior and systemic risk in global stock markets

This paper provides new evidence of herding due to non- and fundamental information in global equity markets. Using quantile regressions applied to daily data for 33 countries, we investigate herding during the Eurozone crisis, China's market crash in 2015–2016, in the aftermath of the Brexit vote and during the Covid-19 Pandemic. We find significant evidence of herding driven by non-fundamental information in case of negative tail market conditions for most countries. This study also investigates the relationship between herding and systemic risk, suggesting that herding due to fundamentals increases when systemic risk increases more than when driven by non-fundamentals. Granger causality tests and Johansen's vector error-correction model provide solid empirical evidence of a strong interrelationship between herding and systemic risk, entailing that herding behavior may be an ex-ante aspect of systemic risk, with a more relevant role played by herding based on fundamental information in increasing systemic risk.

Dynamic spillovers among natural gas, liquid natural gas, trade policy uncertainty, and stock market

Given Qatar's economic structure and geographical features, we examine the likely spillovers among natural gas, liquid natural gas (LNG), trade policy uncertainty (TPU), and stock markets using the spillover index developed by Diebold and Yilmaz (2012). The results show considerable spillover among the aforementioned variables. Natural gas and LNG are the net receivers of spillovers, whereas TPU and the stock market are net spillover transmitters. TPU had the lowest sensitivity in the network system, whereas natural gas and LNG had the highest sensitivities. Moreover, the measure of spillovers varies over time and jumps during financial and COVID-19 crises. TPU and the stock market were the strongest driving forces of spillover. In addition, while the stock market has the highest transmission of natural gas and LNG, consistent with the energy-oriented structure of corporations in Qatar's stock market, it showed the highest sensitivity to LNG and natural gas. Both forms of energies—natural gas and LNG—indicate noticeable sensitivity to the stock market and TPU, respectively. Moreover, TPU is more sensitive to natural gas and LNG shocks. These results have significant implications for investors, policymakers, and governments.

Does US Infectious Disease Equity Market Volatility Index Predict G7 Stock Returns? Evidence Beyond Symmetry

During the COVID-19 pandemic, Baker et al. (2020) [The unprecedented stock market reaction to COVID-19. The Review of Asset Pricing Studies, 10, 742–758.] proposed the infectious disease equity market volatility (ID-EMV) index, which tracks US equity market volatility caused by infectious diseases. We extended the literature by using this newly developed ID-EMV index to examine its asymmetric effect on the share market returns of the G7 countries, which include the United Kingdom, Italy, Japan, Germany, France, Canada, and the United States of America. Moreover, we used novel techniques like the quantile-on-quantile regression test, quantile cointegration test, and quantile unit root test. The quantile cointegration test indicates that the infectious disease EMV index is cointegrated with G7 stock returns. Moreover, the quantile-on-quantile regression technique reveals that the infectious disease index positively affects stock returns during bullish states of the stock markets. In contrast, it negatively affects stock returns during bearish states of the stock market returns. The negative effect of the bearish states implies that investors may discourage investments during the downturns of the economy, whereas they need to boost their investments during economic booms.

A Novel Machine Learning-assisted Pairs Trading Approach for Trading Risk Reduction

The cryptocurrency market has been growing rapidly in recent years. The volume of transactions and the number of participants in the cryptocurrency market makes it huge enough that we cannot ignore it. At the same time, the global stock market has also reached a new height in the past two years. However, due to the COVID epidemic and other political and economic-related factors in the last two years, the uncertainty in the capital market remains high, and short-term large fluctuations occur frequently;thus, many investors have suffered substantial losses. Pairs trading, an advanced statistical arbitrage method, is believed to hedge the risk and profit off the market regardless of market condition. Amongst the vast literature on pairs trading, there have been investors trading a pair of cryptocurrencies or a pair of stocks using machine learning or empirical methods. This research probes the boundary of utilizing machine learning methods to do pairs trading with one stock asset and another cryptocurrency. Briefly, we built an assets pool with both stocks and cryptocurrencies to find the best trading pair. In addition, we applied mainstream machine learning models to the trading strategy. We finally evaluated the accuracy of the proposed method in prediction and compared their returns based on the actual U.S. Stock and Cryptocurrency Market data. The test results show that our method outperforms other state-of-the-art methods. © 2022 IEEE.

Stock Market Response to Covid-19 Pandemic Period In Asian Equity Markets: An Event Study

The purpose of the study was to evaluate the relationshi ps between factors and the variability of Asian Emerging Stock Markets for the time before, during, and following the COVID 19 Outbreak. Descriptive, ADF Test, GARCH (1.1) Model, and Pair-wise Granger Causality Test were used in the research. From the outcomes of empirical analysis, the study found that the information about the COVID 19 Pandemic played a major role in the movement of Asian emerging countries, stock markets. But the fear of a COVID 19 pandemi c exerci sed mi xed i mpact on t he count ry' s market performance. As a result, while investing in the stock markets, the i nvest or shoul d keep a keen wat ch on market movements. International stock market investors in particular, should watch numerous worldwide events, for a sound investment in the global stock markets. © Indian Institute of Finance.

Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors

By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.-China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literature. By considering that the stock volatility spillover may vary over distinct timescales, the spillovers are disclosed through innovatively constructing the multi-scale spillover networks, followed by connectedness computation, based on variational mode decomposition (VMD) and generalized vector autoregression (GVAR) process. Our empirical analysis first demonstrates the different levels of increases in the total sectoral volatility spillover and changes in the roles of the sectors in the system under the aforementioned crises. Besides, the increases in the sectoral spillover in the long-term are verified to negatively impact the macroeconomy and can thereby act as warning signals.

Volatility Spillovers between Stock and Energy Markets during Crises: A Comparative Assessment between the 2008 Global Financial Crisis and the Covid-19 Pandemic Crisis

This paper investigates volatility spillovers between energy and stock markets during periods of crises. Our main findings reveal that transmissions of volatilities among these markets during the Covid-19 pandemic crisis exceeded the ones recorded throughout the 2008 global financial crisis. All stock markets are net transmitters of volatility to energy markets during the 2008 global financial crisis while they show different patterns during the Covid-19 crisis. We also provide evidence of asymmetric volatility spillovers among stock and energy markets. Our results also indicate that on average natural gas provides better hedging effectiveness to the stock markets than crude oil.

Safe havens in Islamic financial markets: COVID-19 versus GFC

Using a bivariate dynamic conditional correlation (DCC) generalized autoregressive conditional heteroskedasticity (GARCH) model, this study compares the safe-haven properties of various assets against the major Gulf Cooperation Council (GCC) stock indexes during two periods of financial turmoil, the COVID-19 pandemic and the 2008 Global Financial Crisis (GFC). Sovereign bonds offered the highest hedging benefits under both crises. The traditional safe assets, gold and silver, which were reasonably productive under the GFC, have been less so during the pandemic. The Japanese yen emerged as a very safe choice for investors holding GCC stock indexes. Both sector indexes and stock indexes failed to safeguard investors most of the time during each crisis.

COVID-19 and connectedness between Sustainable and Islamic equity markets

Because of the increasing importance of and demand for ethical investment, this paper investigates the dynamics of connectedness between sustainable and Islamic investment in nineteen countries that represent developed and emerging financial markets worldwide. To this end, we apply models proposed by Diebold and Yilmaz and Barunik and Krehlik to explore the overall and frequency-based connectedness between selected ethical investments. Our results reveal evidence of a moderate to strong intra country-level connectedness between sustainable and Is-lamic investment and limited cross-country connectedness between ethical investments. The time-varying connectedness analysis suggests enhanced connectedness during periods of market-wide turmoil, such as the European debt crisis, the Chinese financial crisis, and the COVID-19 pandemic. Moreover, the COVID-19 subsample analysis shows an enhanced and idiosyncratic country-level and cross-country connectedness structure between ethical investments, indicating the evolving nature of the relationship between sustainable and Islamic investment. Copyright (c) 2022 Borsa Istanbul Anonim S,irketi . Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Machine learning sentiment analysis, COVID-19 news and stock market reactions.

The recent COVID-19 pandemic represents an unprecedented worldwide event to study the influence of related news on the financial markets, especially during the early stage of the pandemic when information on the new threat came rapidly and was complex for investors to process. In this paper, we investigate whether the flow of news on COVID-19 had an impact on forming market expectations. We analyze 203,886 online articles dealing with COVID-19 and published on three news platforms (MarketWatch.com, NYTimes.com, and Reuters.com) in the period from January to June 2020. Using machine learning techniques, we extract the news sentiment through a financial market-adapted BERT model that enables recognizing the context of each word in a given item. Our results show that there is a statistically significant and positive relationship between sentiment scores and S&P 500 market. Furthermore, we provide evidence that sentiment components and news categories on NYTimes.com were differently related to market returns.

The Ramadan effect on commodity and stock markets integration

Purpose: This study aims to investigate the dependence structure and volatility spillovers among two strategic commodities (crude oil and gold) and a set of Islamic and conventional regional stock market indices, while examining the Ramadan effect Design/methodology/approach: The empirical strategy consists of two complementary measures of dependence and connectedness. This study first uses copulas to examine the dependency between the markets considered, then spillovers compute the magnitude of the connectedness among them. Findings: The copulas analysis shows that Frank's copula appears to better capture the relationship between most asset returns and highlights the almost absence of extreme dependence and, therefore, the existence of diversification opportunities. Moreover, the connectedness analysis suggests that gold is a net volatility receiver and provides, thereby, greater diversification benefits compared to crude oil. In addition, the high levels of time-varying connectedness support strong integration among the financial markets studied, specifically during the COVID-19 crisis period. Furthermore, the connectedness among the markets studied increases during the Ramdan subperiods, supporting shift contagion among financial markets considered during this religious holiday. Practical implications: The results provide investors with a better understanding of the nature as well as the magnitude of the interdependences between commodity markets and a set of Islamic and conventional regional stock markets. Indeed, it is of paramount importance for investors to clearly understand how Islamic and conventional markets are segmented or integrated during stress and stress-free periods, as well as the effect of the month of Ramadan on the interdependence among markets, to better assess risks, diversify portfolios and implement more effective hedging strategies. Originality/value: While a considerable body of literature examines financial contagion and volatility transmission between financial markets, there is still much to be said regarding connectedness among commodity and stock markets, particularly when it comes to studying the effects of religious holidays on the interaction between conventional and Islamic assets. This paper fills in this gap by focusing on the dependence structure as well as the connectedness between Islamic stock indices, conventional stock indices, gold and crude oil for six different regions, while examining the Ramadan effect. © 2023, Emerald Publishing Limited.

The Impact of COVID-19 Pandemic on Emerging Country Stock Markets: Evidence of the Value Effect

We examine the impact of the COVID-19 pandemic on seven emerging stock markets by focusing on the value effect. Our results show that there are significant differences in the value premia before and during the pandemic. Furthermore, the traditional value proxies are no longer good predictors of future stock returns. To further capture the impact the pandemic's progress on stock returns, we estimate Fama-MacBeth regressions by introducing proxies of the pandemic. We uncover heterogeneous responses of emerging markets to the pandemic. These findings provide a wealth of insights on the presence and driving force relevant to the value effect.

Hedging effectiveness of bitcoin and gold: Evidence from G7 stock markets

Geopolitical uncertainty creates huge pressure on financial markets, forcing decision-makers and investors to analyze risks and manage their investment portfolios. Against this background, this study investigates the risk-hedging effects of Bitcoin and Gold in the stock markets of the G7 countries. The research focuses on the period from January 5, 2017 to June 30, 2022, covering a significant portion of the COVID-19 pandemic and the Russo-Ukrainian War. The study utilizes wavelet analysis to analyze the hedging effects in the time–frequency domain, allowing for a more in-depth analysis. The findings show that bitcoin provides stronger short-term risk hedging in the G7 stock markets compared to gold during the COVID-19 and Russo-Ukrainian War periods, making a valuable contribution to the limited existing literature on the topic. © 2023 Elsevier B.V.