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.     

Linkages between DeFi assets and conventional currencies: Evidence from the COVID-19 pandemic

This paper examines the static and dynamic returns connectedness between four renowned DeFi assets, namely, Chainlink, Maker, Basic Attention Token, and Synthetix, and four internationally important conventional currencies, being they Chinese Yuan, Japanese Yen, Euro, and Pound Sterling. We use the time-varying parameter vector autoregressions framework combined with the connectedness approach based on the generalized forecast error variance decomposition. Our static connectedness analysis evidences a low connection of the DeFi markets with the conventional currency markets. The results of our dynamic analysis reveal that the return spillovers are time-varying, with an abrupt increase in connectedness between the DeFi and currency markets in early 2020, during the initial escalation of the pandemic. However, the spillover from the Chinese Yuan to the system does not exhibit any hike due to the COVID-19-triggered meltdown, highlighting a pandemic-caused decoupling of the Chinese financial system from the other centralized and decentralized markets. We observe unprecedentedly high spillovers from the system to the DeFi markets at the beginning of the pandemic. However, we still find that the DeFi markets act predominantly as net innovation transmitters during the first COVID-19 year. Moreover, we detect the existence of a pairwise-like relationship between the net return spillover profiles and report on inversely symmetric profiles for the Maker - Euro, Basic Attention Token - Japanese Yen, and the Chainlink - Pound Sterling pairs. Given the time-varying transmission-reception patterns for all markets, investors and policymakers can make use of our spillover analysis to improve portfolio allocation and regulatory decisions.     

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.     

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.     

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.     

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.     

Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach

The economic onslaught of the COVID-19 pandemic has compromised the risk management of financial institutions. The consequences related to such an unprecedented situation are difficult to foresee with certainty using traditional methods. The regulatory credit loss attached to defaulted mortgages, so-called expected loss best estimate (ELBE), is forecasted using a machine learning technique. The projection of two ELBEs for 2022 and their comparison are presented. One accounts for the outbreak's impact, and the other presumes the nonexistence of the pandemic. Then, it is concluded that the referred crisis surely adversely affects said high-risk portfolios. The proposed method has excellent performance and may serve to estimate future expected and unexpected losses amidst any event of extraordinary magnitude.     

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.     

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.     

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.     

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.     

Tail risk contagion between international financial markets during COVID-19 pandemic

In this paper, we combine the time-varying financial network model and FARM-selection approach to analyze the tail risk contagion between international financial market during the COVID-19 epidemic. Since the tail risk acts as a global transmission channel, we use the sample of 19 international financial markets to explore the contagion of tail risk during the epidemic. We find that the COVID-19 epidemic increases the number of contagion channels in the international financial system. The clustering level of the financial system has a significant growth during the COVID-19 pandemic, and the number of risk drivers is also larger than risk takers. The key financial market of each international financial network is related to the epidemic country. We also consider the tail risk contagion in local financial markets and find that the COVID-19 pandemic has an important influence on the tail risk contagions in local network systems     

Estimating the COVID-19 cash crunch: Global evidence and policy

In this paper, we investigate how the COVID-19 health crisis could affect the liquidity of listed firms across 26 countries. We stress-test three liquidity ratios for each firm with full and partial operating flexibility in two simulated distress scenarios corresponding to drops in sales of 50% and 75%, respectively. In the most adverse scenario, the average firm with partial operating flexibility would exhaust its cash holdings in about two years. At that point, its current liabilities would increase, on average, by eight times, suggesting that the average firm would have to resort to the debt market to prevent a liquidity crunch. Moreover, about 1/10th of all sample firms would become illiquid within six months. Finally, we study two different fiscal policies, tax deferrals and bridge loans, that governments could implement to mitigate the liquidity risk. Our analysis suggests bridge loans are more cost-effective to prevent a massive cash crunch.     

Multinational corporations and tax havens: evidence from country-by-country reporting

International Tax and Public Finance - A growing body of economics literature shows that multinational corporations (MNCs) shift their profits to tax havens. We contribute to this evidence by...     

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.     

COVID-19 pandemic,oil prices,stock market,geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach

In this paper, we analyze the connectedness between the recent spread of COVID-19, oil price volatility shock, the stock market, geopolitical risk and economic policy uncertainty in the US within a time-frequency framework. The coherence wavelet method and the wavelet-based Granger causality tests applied to US recent daily data unveil the unprecedented impact of COVID-19 and oil price shocks on the geopolitical risk levels, economic policy uncertainty and stock market volatility over the low frequency bands. The effect of the COVID-19 on the geopolitical risk substantially higher than on the US economic uncertainty. The COVID-19 risk is perceived differently over the short and the long-run and may be firstly viewed as an economic crisis. Our study offers several urgent prominent implications and endorsements for policymakers and asset managers.     

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.     

The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect

In this paper, we test the role of news in the predictability of return volatility of digital currency market during the COVID-19 pandemic. We use hourly data for cryptocurrencies and daily data for the news indicator, thus, the GARCH MIDAS framework which allows for mixed data frequencies is adopted. We validate the presupposition that fear-induced news triggered by the COVID-19 pandemic increases the return volatilities of the cryptocurrencies compared with the period before the pandemic. We also establish that the predictive model that incorporates the news effects forecasts the return volatility better than the benchmark (historical average)model.     

Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic

This study aims to examine whether the prices and returns of two cryptocurrencies, Dogecoin and Ethereum, are affected by Twitter engagement following the COVID-19 pandemic. We use the autoregressive integrated moving average with explanatory variables model to integrate the effects of investor attention and engagement on Dogecoin and Ethereum returns using data from December 31, 2020, to May 12, 2021. The results provide evidence supporting the hypothesis of a strong effect of Twitter investor engagement on Dogecoin returns; however, no potential impact is identified for Ethereum. These findings add to the growing evidence regarding the effect of social media on the cryptocurrency market and have useful implications for investors and corporate investment managers concerning investment decisions and trading strategies.