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.     

Vulnerability of financial markets in India: The contagious effect of COVID-19

This study aims to examine the impact of COVID-19 on financial markets, using emerging market data. Specifically, panel data regression is applied on 3200 observations for daily market returns during lockdown in India. The event study methodology is adopted to show abnormal returns registered in the lockdown period. A contrasting breakdown effect of COVID-19 on various Indian industries has been observed through sectoral analysis. The study also provides empirical evidence for lockdown measures taken by the government on stock market returns and post lockdown impact of COVID-19 on daily market returns for over 6550 observations.     

Comparing COVID-19 with the GFC: A shockwave analysis of currency markets

I analyze the shockwave effect of the COVID-19 pandemic on currency markets, with a comparison to the global financial crisis (GFC), employing Kapetanios m-break unit root test, investigations of standalone risk measures—downside variance, upside risk, volatility skewness, Gaussian Value at Risk (VaR), historical VaR, modified VaR—and Diebold–Yilmaz volatility spillover analysis. Standalone risk analysis shows that the turmoil in the initial months of COVID-19 was not as severe as that in the GFC. However, examination of co-movements and volatility spillovers illustrates a different scenario. According to the results of the static connectedness measure of Diebold–Yilmaz, the shockwave of the COVID-19 pandemic in the total volatility spillover is about eight times greater than that of the GFC. Among standalone risk measures, the results closest to this finding are obtained from volatility skewness analysis. Additionally, of six foreign exchange rates, the Brazilian real and Turkish lira are the currencies experiencing the greatest increase in received volatility during the GFC and the COVID-19 pandemic, respectively. These findings suggest the severe effect of crises on emerging financial markets.     

Internal capital markets,corporate investment,and the COVID-19 pandemic: Evidence from Korean business groups

This paper examines whether the investment of Korean business group (“chaebol”) affiliated firms behaved differently from that of non-chaebol firms in response to the COVID-19 outbreak. I show that chaebol firms cut back investment to a lesser degree than similar non-chaebol firms. Chaebol firms with higher-than-industry-median market-to-book ratios invested more and experienced less decline in their stock prices, while I do not find such relationships for non-chaebol firms. This paper provides evidence that chaebol internal capital markets helped mitigate the negative effects of the pandemic on firm investment and value.     

Diversifying equity with cryptocurrencies during COVID-19

Literature suggests assets become more correlated during economic downturns. The COVID-19 crisis provides an unprecedented opportunity to investigate this considerably further. Further, whether cryptocurrencies provide a diversification for equities is still an unsettled issue. We employ several econometric procedures, including wavelet coherence, and neural network analyses to rigorously examine the role of COVID-19 on the paired co-movements of four cryptocurrencies, with seven equity indices (matching countries particularly impacted by COVID-19). Our period of study includes one year prior to the onset of COVID-19, and one year during the pandemic, extending deeper into the pandemic period (February 2021) than most previous studies. We find co-movements between cryptocurrencies and equity indices gradually increased as COVID-19 progressed. However, most of these co-movements are either modestly positively correlated, or minimal, suggesting cryptocurrencies in general do not provide a diversification benefit during either normal times or downturns. An exception, however, is the co-movement of tether. Tether co-moves negatively with equities to an economically significant degree, both pre COVID-19, and considerably more during COVID-19. Co-movements between tether and equity indices spiked sharply during identified waves of the pandemic. Tether appears to be an important safe haven during times of market turmoil, consistent with investors seeking USD liquidity during periods of volatility.     

From COVID-19 herd immunity to investor herding in international stock markets: The role of government and regulatory restrictions

We study if government response to the novel coronavirus COVID-19 pandemic can mitigate investor herding behaviour in international stock markets. Our empirical analysis is informed by daily stock market data from 72 countries from both developed and emerging economies in the first quarter of 2020. The government response to the COVID-19 outbreak is measured by means of the Oxford COVID-19 Government Response Tracker, where higher scores are associated with greater stringency. Three main findings are in order. First, results show evidence of investor herding in international stock markets. Second, we document that the Oxford Government Response Stringency Index mitigates investor herding behaviour, by way of reducing multidimensional uncertainty. Third, short-selling restrictions, temporarily imposed by the national and supranational regulatory authorities of the European Union, appear to exert a mitigating effect on herding. Finally, our results are robust to a range of model specifications.     

The financial impact of COVID-19: Evidence from an event study of global hospitality firms

This paper examines the daily abnormal stock price returns of a sample of 154 publicly-traded hospitality firms from 23 different countries representing over $400 billion in combined market capitalization around the time that COVID-19 was first viewed by stock market participants as a major—possibly even existential—threat. The findings of the study suggest that, financially, hotels performed better than restaurants, which themselves performed better than casinos. These findings are consistent with medical recommendations concerning the relative safety of various hospitality-related activities and, therefore, also with the tenets of financial market efficiency in the hospitality sector. Additional findings suggest that hospitality firms with strong balance sheets and income statements characterized by relatively low leverage ratios, high market value (consistent with a “too big to fail” mentality), and higher price/earnings ratios (implying higher relative profitability) all fared better than smaller, weaker firms. Although, in no case, did Bloomberg's proprietary environmental, social, and governance (ESG) variable possess any predictive power, variables reflecting cross-country cultural differences support Huynh’s (2020) finding that “individualism” was an important factor in explaining the economic impact of the COVID-19 pandemic on hospitality firms.     

COVID-19, government policy responses,and stock market liquidity around the world: A note

Unprecedented non-pharmaceutical interventions targeted to curb the spread of COVID-19 exerted a dramatic impact on the global economy and financial markets. This study is the first attempt to investigate the influence of these government policy responses on global stock market liquidity. To this end, we examine daily data from 49 countries for the period January-April 2020. We demonstrate that the impact of the interventions is limited in scale and scope. Workplace and school closures deteriorate liquidity in emerging markets, while information campaigns on the novel coronavirus facilitate trading activity.     

Return connectedness across asset classes around the COVID-19 outbreak

In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of return connectedness across various assets (gold, crude oil, world equities, currencies, and bonds) around the COVID-19 outbreak. Using the TVP-VAR connectedness approach, the results show that the dynamic total connectedness across the five assets was moderate and quite stable until early 2020. After that, the total connectedness spikes and the structure of the network of connectedness alters, which concurs with the COVID-19 outbreak. The equity and USD indices are the primary transmitters of shocks before the outbreak, whereas the bond index becomes the main transmitters of shocks during the COVID-19 outbreak. However, the USD index is a net receiver of shocks to other assets during the outbreak period. Furthermore, using a recently developed newspaper-based index of uncertainty in financial markets due to infectious diseases to capture the recent impact of COVID-19, we find that connectedness is positively related to this index, and increases at higher levels (conditional quantiles) of connectedness. Overall, our results reflect the speedy disturbing effects of the COVID-19 outbreak, which matters to the formulations of policies seeking to achieve financial stability. The results also indicate a possibility to threaten investors’ portfolios and fade the benefits of diversification.     

Corporate governance and stock performance: The case of COVID-19 crisis

This paper analyzes the impact of COVID-19 on firm-level stock behaviors (including stock price volatility, trading volume and stock returns). Using US data, this paper examines whether confirmed cases (and deaths) of COVID-19 or COVID-19-associated online searches affect stock behaviors. The results show that our five COVID-19 proxies are all positively associated with stock price volatility and trading volume and negatively associated with stock returns. This paper further investigates the mitigating effect of corporate governance (viz., board and ownership structures) in this COVID-19 crisis. Overall, the results suggest that good corporate governance can mitigate the impact of COVID-19 on stock price volatility and trading volume but may not help to enhance stock returns. This paper also considers key policies used to tackle the COVID-19 pandemic and finds that government intervention plays an important role in stabilizing stock markets in this COVID-19 crisis.     

COVID-19, government interventions and emerging capital markets performance

In this study, we explore the impact of government intervention to contain the spread of COVID-19 in emerging countries on the performance of their leading stock indices. We retrieved data on the performance of 25 international capital market indices included in the MSCI Emerging Markets Index and data about the closures, economic, and health measures imposed in each country examined. Overall, our findings show that government restrictions are associated with negative market returns, possibly due to the anticipated adverse effect to the economy. The adverse effect is more evident when closures are imposed. The market response to economic stimulus is mild but varies depending on the type of intervention imposed, much as with the health measures. Public campaigns may raise public awareness about COVID-19, but they can also increase the public’s fear of the pandemic, reflected in the negative response in capital markets. The results are essential for understanding the trends and fluctuations in emerging markets during this current crisis and for preparing for crises in the future.     

COVID-19, a blessing in disguise for the Tech sector: Evidence from stock price crash risk

In this paper we document that although COVID-19 has brought uncertainties to the overall economy, the Technology (tech) sector is the systematic beneficiary of the pandemic. Using a quasi-natural setup, we find a significant notion that the Stock Price Crash Risk (SPCR) of firms within the Tech sector decreases during the COVID-19 pandemic compared to the recent past and firms belonging to other sectors. Our analyses further reveal that firms in the Tech sector with stronger external monitoring and better information environment receive an even greater advantage from the pandemic. Overall, our study suggests that the higher systemic dependency on the Tech sector during the COVID-19 outbreak results in an economic benefit for this sector.     

COVID-19 and stock returns: Evidence from the Markov switching dependence approach

This paper aims to investigate the regime-switching and time-varying dependence between the COVID-19 pandemic and the US stock markets using a Markov-switching framework. It makes two contributions to the empirical literature by showing that: (a) the variations of the daily reported COVID-19 cases and cumulative COVID-19 deaths induced asymmetric lower (left) and upper (right) tail dependence with the stock markets, and its left and right tail dependence exhibited significant time-varying trends; and (b) the left and right tail dependence between the stock markets and the pandemic exhibited significant regime-switching behaviours, with its switching probabilities in the higher tail dependence stage all being greater than in the lower tail dependence stage after 1 December 2019. Moreover, given that there is concurrent but significant financial market reaction to any unexpected emergence of a transmittable respirational disease or a natural calamity, the outcomes have some vital implications to market players and policymakers.     

Tests of technical trading strategies in the emerging equity markets of Latin America and Asia

This study examines the potential profit of ten Variable Length Moving Average (VMA) technical trading rules in ten emerging equity markets in Latin America and Asia from January 1982 through April 1995. The average difference in buy − sell returns after trading costs for each rule and country are compared to a buy and hold strategy. Taiwan, Thailand and Mexico emerge as markets where technical trading strategies may be profitable. We find no strong evidence of profitability for the other markets. However, we find that 82 out of the 100 country–trading rule combinations tested in ten emerging markets, disregarding their statistical significance, correctly predict the direction of changes in the return series. These findings may provide investors with important asset allocation information.     

Impact of COVID-19 on stock market efficiency: Evidence from developed countries

This study investigates the impact of the novel coronavirus (COVID-19) pandemic on stock market efficiency for six hard-hit developed countries, namely, the United States (US), Spain, the United Kingdom (UK), Italy, France, and Germany. Applying the wild bootstrap automatic variance ratio test on daily stock market data from July 29, 2019 to January 25, 2021, it is found that all stock markets used in this study deviate from market efficiency during some periods of the pandemic. Deviations from market efficiency are seen more in the stock markets of the US and UK during the COVID-19 outbreak than in other stock markets. These results are strengthened when a different econometric method, the automatic portmanteau test, is used. The findings of this study indicate an increasing chance for stock price predictions and abnormal returns during the COVID-19 pandemic.     

The interrelatedness of global equity markets, money markets, and foreign exchange markets

This article investigates different aspects of global financial markets, specifically relationships among equity markets, money markets, and foreign exchange markets across countries. To represent the three major financial markets of the world, Japan is the proxy for Asia, Germany is the proxy for Europe, and the United States is the proxy for North America. Strong evidence exists that international money markets and international equity markets are becoming increasingly integrated over time. This article incorporates foreign exchange values as partial determinants of equity returns and money market returns and investigates the interactions among these three asset markets from a global perspective.     

COVID-19 and Inequalities*

This paper brings together evidence from various data sources and the most recent studies to describe what we know so far about the impacts of the COVID-19 crisis on inequalities across several key domains of life, including employment and ability to earn, family life and health. We show how these new fissures interact with existing inequalities along various key dimensions, including socio-economic status, education, age, gender, ethnicity and geography. We find that the deep underlying inequalities and policy challenges that we already had are crucial in understanding the complex impacts of the pandemic itself and our response to it, and that the crisis does in itself have the potential to exacerbate some of these pre-existing inequalities fairly directly. Moreover, it seems likely that the current crisis will leave legacies that will impact inequalities in the long term. These possibilities are not all disequalising, but many are.     

Risk contagion of COVID-19 in Japanese firms: A network approach

The novel coronavirus disease (COVID-19) is one of the worst pandemics in human history. Our research objective is to assess the contagion effect on Japanese firms and to evaluate the Japanese government's COVID-19 measures during the period from April 7, 2020, to May 25, 2020. We propose a susceptible-infected-recovered-dead model for COVID-19 and derive COVID-19 parameters for Japan. Subsequently, we analyze the effect of COVID-19 on Japanese firms through correlation-based network and credit risk analyses. The main findings are that the Tokyo Stock Price Index moved in the opposite direction of COVID-19 parameters and COVID-19 parameters are almost the only risk factors that impact a firm's credit risk during the period. Finally, we find that the interconnection analysis between the COVID-19 infection network and the financial networks contribute to the existing pandemic risk management knowledge.     

Quantile dependencies and connectedness between the gold and cryptocurrency markets: Effects of the COVID-19 crisis

This paper examines the quantile dependence, connectedness, and return spillovers between gold and the price returns of leading cryptocurrencies, using quantile cross-spectral, the return spillovers based the quantile VAR, and quantile connectedness approaches. The results show that the dependencies within cryptocurrencies are highly symmetric and sensitive to different quantile arrangements. Under normal market conditions, we find a high positive dependence within cryptocurrencies and a low positive dependence between cryptocurrencies and gold. The dependence is higher at long term than intermediate- and short- terms before the pandemic during bearish market conditions. In contrast, the degree of dependence decreases at the intermediate- and long-terms during COVID-19 period than before. Moreover, the magnitude of return spillovers is higher at lower quantile (bearish market) than upper quantile (bullish market). Gold serves as a safe haven and diversifier asset for cryptocurrencies during COVID-19 outbreak at both intermediate and long terms.     

The impact of COVID-19 on the stock market crash risk in China

This study investigates the impact of the COVID-19 pandemic on the stock market crash risk in China. For this purpose, we first estimated the conditional skewness of the return distribution from a GARCH with skewness (GARCH-S) model as the proxy for the equity market crash risk of the Shanghai Stock Exchange. We then constructed a fear index for COVID-19 using data from the Baidu Index. Based on the findings, conditional skewness reacts negatively to daily growth in total confirmed cases, indicating that the pandemic increases stock market crash risk. Moreover, the fear sentiment exacerbates such risk, especially with regard to the impact of COVID-19. In other words, when the fear sentiment is high, the stock market crash risk is more strongly affected by the pandemic. Our evidence is robust for the number of daily deaths and global cases.