On equity market inefficiency during the COVID-19 pandemic

We show that during the weeks following the initiation of the COVID-19 pandemic, the United States equity market was inefficient. This is demonstrated by showing that utility maximizing agents over the time period ranging from mid-February to late March 2020 can generate statistically significant profits by utilizing only historical price and virus related data to forecast future equity ETF returns. We generalize Merton’s optimal portfolio problem using a novel method based upon a likelihood ratio in order to construct a dynamic trading strategy for utility maximizing agents. These strategies are shown to have statistically significant profitability and strong risk and performance statistics during the COVID-19 time-frame.     

Evidence of oil market price clustering during the COVID-19 pandemic

We use hourly data on opening price, closing price, opening ask price, opening bid price, closing ask price and closing bid price to show that while oil prices are characterized by price clustering behavior, prices tend to cluster on numbers closer to zero than to one. Comparing the pre-COVID-19 sample with the COVID-19 sample, we find that evidence of price clustering is 8% more in the COVID-19 sample. We test the determinants of price clustering and find that as much as 30% of the price clustering behavior can be attributed to the COVID-19 pandemic. Finally, using a simple technical trading strategy, we do not find any evidence that the oil market is profitable in the COVID-19 period.     

Analysis of risk correlations among stock markets during the COVID-19 pandemic

The outbreak of the COVID-19 pandemic significantly negatively impacted the global economy and stock markets. This paper investigates the stock-market tail risks caused by the COVID-19 pandemic and how the pandemic affects the risk correlations among the stock markets worldwide. The conditional autoregressive value at risk (CAViaR) model is used to measure the tail risks of 28 selected stock markets. Furthermore, risk correlation networks are constructed to describe the risk correlations among stock markets during different periods. Through dynamic analysis of the risk correlations, the influence of the COVID-19 pandemic on stock markets worldwide is examined quantitatively. The results show the following: (i) The COVID-19 pandemic has caused significant tail risks in stock markets in most countries, while the stock markets of a few countries have been unaffected by the pandemic. (ii) The topology of risk correlation networks has become denser during the COVID-19 pandemic. The impact of the COVID-19 pandemic makes it easier for risk to transfer among stock markets. (iii) The increase in the closeness of the risk relationship between countries with lower economic correlation has become much higher than that between counties with higher economic correlation during the COVID-19 pandemic. For researchers and policy-makers, these findings reveal practical implications of the risk correlations among stock markets.     

Crude oil market and stock markets during the COVID-19 pandemic: Evidence from the US,Japan, and Germany

We analyzed the return and volatility spillover between the COVID-19 pandemic in 2020, the crude oil market, and the stock market by employing two empirical methods for connectedness: the time-domain approach developed by Diebold and Yilmaz (2012) and the method based on frequency dynamics developed by Barunik and Krehlik (2018). We find that the return spillover mainly occurs in the short term; however, the volatility spillover mainly occurs in the long term. From the moving window analysis results, the impact of COVID-19 created an unprecedented level of risk, such as plummeting oil prices and triggering the US stock market circuit breaker four times, which caused investors to suffer heavy losses in a short period. Furthermore, the impact of COVID-19 on the volatility of the oil and stock markets exceeds that caused by the 2008 global financial crisis, and continues to have an effect. The impact of the COVID-19 pandemic on financial markets is uncertain in both the short and long terms. Our research provides some urgent and prominent insights to help investors and policymakers avoid the risks in the crude oil and stock markets because of the COVID-19 pandemic and reestablish economic development policy strategies.     

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.     

Assessing the safe haven property of the gold market during COVID-19 pandemic

This study examines the safe haven prowess of gold against some exogenous shocks due to the COVID-19 pandemic. We further make a comparison of our findings with those obtained for the period before it. Our results confirm the potential of gold market to serve as a safe haven during the pandemic albeit with a higher effectiveness before the pandemic. Further results suggest that gold consistently offers better safe haven properties than the US stocks as well as other precious metals like Silver, Palladium and Platinum regardless of the period. Finally, we find that the predictive model that accounts for uncertainties outperforms the benchmark model that ignores the same both for the in- and out-of-sample forecast analyses.     

Information demand during the COVID-19 pandemic

We investigate the demand for financial information during the initial months of the COVID-19 pandemic. Using Google search data for individual stocks, we show that the Abnormal Google Search Volume Index declined significantly between March and June of 2020. We find a similar effect around earnings announcements dates, which confirms that the demand for financial information by retail investors declined during the pandemic. Our results are indicative of potentially important consequences for information diffusion, price discovery and market efficiency under extreme uncertainty. We discuss possible explanations for these results.     

Market sentiment to COVID-19 and the Chinese stock market

We classify the market sentiment to COVID-19 into expected and unexpected components and then examine their particular impacts on the stock market. We find that unexpected sentiment causes fluctuations in the stock market more than expected sentiment does. However, unexpected sentiment cannot affect stock market informativeness despite the remarkable informational effect of expected sentiment. Moreover, the relation between expected sentiment and stock market fluctuation or informativeness is one-way, whereas there exists a two-way interaction between unexpected sentiment and stock market fluctuation. This further confirms that expected sentiment is informational, whereas unexpected sentiment is quite noisy and informationally harmful.     

In search of COVID-19 and stock market behavior

The aim of this paper is two-fold. First, we investigate the nexus between investor attention to COVID-19 and daily returns in 59 countries. We use Google Search Volume Index to account for investor attention. Our empirical findings suggest that the search volume of the pandemic is negatively associated with daily returns. The effect was strong in the week that the World Health Organization declared it as pandemic and among advanced countries. Second, we explore the relationship between search volume and market volatility. The findings suggest that COVID-19 sentiment generated excess volatility in the market. Our findings remain robust with alternative specifications.     

Disaster response: The COVID-19 pandemic and insider trading around the world

This paper investigates how corporate insiders respond to the initial COVID-19 outbreaks. Using comprehensive insider transaction data from 25 countries, we document a consistent pattern of insider selling during the month after the first COVID-19 case is confirmed in a given country. Insider selling during these disease outbreaks is less pronounced in countries with higher information disclosure requirements, higher public enforcement index, a more efficient judiciary system, and stronger investor protection. Furthermore, cultural differences and the stringency levels of government responses to the COVID-19 outbreaks help moderate insider panic selling when health disasters strike. The findings suggest that a transparent, reliable business system contributes to rebuilding investor trust and corporate resilience during crises.     

Sovereign credit ratings during the COVID-19 pandemic

Using 603 sovereign rating actions by the three leading global rating agencies between January 2020 and March 2021, this paper shows that the severity of sovereign ratings actions is not directly affected by the intensity of the COVID-19 health crisis (proxied by case and mortality rates) but through a mechanism of its negative economic repercussions such as the economic outlook of a country and governments' response to the health crisis. Contrary to expectations, credit rating agencies pursued mostly a business-as-usual approach and reviewed sovereign ratings when they were due for regulatory purposes rather than in response to the rapid developments of the pandemic. Despite their limited reaction to the ongoing pandemic, sovereign rating news from S&P and Moody's still conveyed price-relevant information to the bond markets.     

Noise trading and stock market volatility

We investigate the relative effects of fundamental and noise trading on the formation of conditional volatility. We find significant positive (negative) effects of investor sentiments on stock returns (volatilities) for both individual and institutional investors. There are greater positive effects of rational sentiments on stock returns than irrational sentiments. Conversely, there are significant (insignificant) negative effects of irrational (rational) sentiments on volatility. Also, we find asymmetric (symmetric) spillover effects of irrational (rational) bullish and bearish sentiments on the stock market. Evidence in favor of irrational sentiments is consistent with the view that investor error is a significant determinant of stock volatilities.     

Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets

The COVID-19 has undoubtfully brought fierce shocks to the real economic activities, financial market and public lives. Under this special condition, this study explores whether the predictability of crude oil futures information has changed before and during the COVID-19 pandemic for 19 international stock markets. From an in-sample perspective, we find that the crude oil futures RV can significantly affect future stock volatility for each equity index except SSEC. Moreover, the out-of-sample results from statistic and economic perspective reveal that crude oil futures RV is a more efficient predictor during the COVID-19 pandemic compared with the pre-crisis period. Furthermore, we find that the predictability of crude oil futures information is stronger from March to May 2020, when the epidemic is seriously prevailing. The empirical results from alternative evaluation method, recursive window method, alternative realized measures, controlling VIX and the seasonal effect, asymmetric forecasting window and different testing windows are robust and consistent. Our findings could offer novel and significant policy and practical implications.     

Optimal informed trading in the foreign exchange market

We formulate a market microstructure model of exchange determination that we employ to investigate the impact of informed trading on exchange rates and on foreign exchange (FX) market conditions. With our formulation, we show how strategic informed agents influence exchange rates via both the portfolio-balance and information effects. We outline the connection which exists between the private value of information, market efficiency, liquidity and exchange rate volatility. Our model is also consistent with recent empirical research on the micro-structure of FX markets.     

Performance and informed trading. Comparing foreigners,institutions and individuals in an emerging stock market

Do local institutions, local individuals or foreigners perform better in a small emerging market? We seek answers to this question by examining the investment performance of each group of investors using two unique databases of Colombian stocks. Our analysis serves as an out-of-sample test of previous findings. We find that local institutions have better outcomes than foreigners and local individuals on all performance measures. Furthermore, local individuals perform better than foreigners on trading execution, while foreigners generate better long-term returns. Using a bid-ask spread decomposition, we provide additional evidence that the better performance of institutions is consistent with informational advantages. Our findings reconcile contradictory statements from previous studies.     

Geographic dispersion and corporate resilience during the COVID-19 pandemic

This study demonstrates the positive role of geographic dispersion in corporate resilience to the COVID-19 pandemic in the context of China. This association is more pronounced when firms are highly dependent on the domestic market, less likely to obtain enough financing, highly apply digital technology, and have low customer concentration. This association is attributable to the following three channels: a diversified portfolio, the maintenance of business relationships, and access to non-local resources. Overall, our findings provide a more nuanced picture of the potential impacts of corporate diversification on corporate resilience.     

Searching for safe-haven assets during the COVID-19 pandemic

The ongoing COVID-19 pandemic has shaken the global financial system and caused great turmoil. Facing unprecedented risks in the markets, people have increasing needs to find a safe haven for their investments. Given that the nature of this crisis is a combination of multiple problems, it is substantially different from all other financial crises known to us. It is therefore urgent to re-evaluate the safe-haven role of some traditional asset types, namely, gold, cryptocurrency, foreign exchange and commodities. This paper introduces a sequential monitoring procedure to detect changes in the left-quantiles of asset returns, and to assess whether a tail change in the equity index can be offset by introducing a safe-haven asset into a simple mean-variance portfolio. The sample studied covers a training period between August–December 2019 and a testing period of December 2019–March 2020. Furthermore, we calculate the cross-quantilogram between pair-wise asset returns and compare their directional predictability on left-quantiles in both normal market conditions and the COVID-19 period. The main results show that the role of safe haven becomes less effective for most of the assets considered in this paper, while gold and soybean commodity futures remain robust as safe-haven assets during this pandemic.     

Divergence of sentiment and stock market trading

This paper introduces the concept of divergence of sentiment to the behavioral finance literature. We measure the distance between people with positive and negative sentiment on a daily basis for 20 countries by using data from status updates on Facebook. The prediction is that a higher divergence of sentiment leads to more diverging views on prospects and risks, and thus to more diverging views on the value of a stock. In line with this prediction, divergence of sentiment is positively related to trading volume. We further predict and find a positive relation between divergence of sentiment and stock price volatility. The observed relations are stronger when individual investors are more likely to trade. We compare the effect of our country-specific measures to a global measure of divergence of sentiment. We find that the separate effects of country-specific and global divergence measures depend on a country's level of market integration.     

Exchange trading rules and stock market liquidity

We examine stock exchange trading rules for market manipulation, insider trading, and broker–agency conflict, across countries and over time, in 42 stock exchanges around the world. Some stock exchanges have extremely detailed rules that explicitly prohibit specific manipulative practices, but others use less precise and broadly framed rules. We create new indices for market manipulation, insider trading, and broker–agency conflict based on the specific provisions in the trading rules of each stock exchange. We show that differences in exchange trading rules, over time and across markets, significantly affect liquidity.     

Gold and US sectoral stocks during COVID-19 pandemic

In this study, we examine the hedging relationship between gold and US sectoral stocks during the COVID-19 pandemic. We employ a multivariate volatility framework, which accounts for salient features of the series in the computation of optimal weights and optimal hedging ratios. We find evidence of hedging effectiveness between gold and sectoral stocks, albeit with lower performance, during the pandemic. Overall, including gold in a stock portfolio could provide a valuable asset class that can improve the risk-adjusted performance of stocks during the COVID-19 pandemic. In addition, we find that the estimated portfolio weights and hedge ratios are sensitive to structural breaks, and ignoring the breaks can lead to overestimation of the hedging effectiveness of gold for US sectoral stocks. Since the analysis involves sectoral stock data, we believe that any investor in the US stock market that seeks to maximize risk-adjusted returns is likely to find the results useful when making investment decisions during the pandemic.