In this study, we examine the efficiency of the US stock markets during the COVID-19 outbreak using a fundamental financial analysis approach, the constant growth model and a behavioral model including a Google-based Index. We juxtapose the released news and the performance of the US stock market during the COVID-19 outbreak and we show that during some periods the health risk was significantly underestimated and/or ignored. The Efficient Market Hypothesis (EMH) suggests that prices incorporate all the available information at any point in time, yet as we show a systemic factor, the health risk, was not always rationally incorporated in stock prices. The Runs-tests confirm our assumption that the market was not efficient during the examined period. The reason for this inefficiency could be that something is missing from traditional finance models, such as the impact of fear of COVID-19. For this reason we employ a Coronavirus Fear Index (CFI) based on Google searches and using Granger causality we provide empirical evidence that the fear drives the S&P500 performance, and using a GARCH model we show that the fear negatively influences the performance of the US stock market.

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In this note, we show that the stock markets do not always incorporate all the available information because in many cases they slowly evaluate the news. Using simple statistical analysis, we show that the response of the markets to the available information in certain time periods is irrational and inefficient. The COVID-19 outbreak gives financial economists an example of health risk underestimation, and of an unexpectedly slow response during a stress period; issues that should be examined in the future under a behavioral view.

Summary The purpose of this study is to examine the impact of the pandemic on the performance of stock markets, focusing on the behavioral influence of the fear due to COVID‐19. Using a data set of 10 developed countries during the period December 31, 2019, to September 30, 2020, we examine the impact of COVID‐19 on the performance of the stock markets. We incorporate the impact of the COVID‐19 pandemic using the following variables: (a) the number of new COVID‐19 cases, which was widely used as the main explanatory variable for market performance in early financial studies, and (b) a Google Search index, which collects the number of Google searches related to COVID‐19 and incorporates the health risk and the fear of COVID‐19 (the higher the number of searches for Covid terms, the higher the index value, and the higher the fear index). We employ our input into an EGARCH(1,1,1) model, and the findings show that the Google Search index enables us to draw statistically significant information regarding the impact of the COVID‐19 fear on the performance of the stock markets. On the other hand, the variable of the number of new COVID‐19 cases does not have any statistically significant influence on the performance of the stock markets. Google searches could be a useful tool for supporters of behavioral finance, scholars, and practitioners.

Purpose – This paper aims to examine the month and the trading month effects under changing financial trends. The Greek stock market was chosen to implement the authors' assumptions because during the period 2002-2012, there were clear and long-term periods of financial growth and recession. Thus, the authors examine whether the financial trends influence not only the Greek stock market’s returns, but also its anomalies. Design/methodology/approach – Daily financial data from the Athens Exchange General Index for the period 2002-2012 are used. The sample is separated into two sub-periods: the financial growth sub-period (2002-2007), and the financial recession sub-period (2008-2012). Several linear and non-linear models were applied to find which is the most appropriate, and the results suggested that the T-GARCH model better fits the sample. Findings – The empirical results show that changing economic and financial conditions influence the calendar effects. The trading month effect, especially, completely changes in each fortnight following the financial trend. Regarding the January effect, which is the most popular month effect, the results confirm its existence during the growth period, but during the recession period, we find that it fades. Therefore, by examining the aforementioned calendar effects in different periods, different conclusions may be reached, perhaps because the financial trends’ influence is ignored. Research limitations/implications – The empirical results confirm the authors' assumption that a possible explanation for the controversial empirical findings regarding the calendar anomalies may be the different financial trends. However, these are some primary results that are confirmed only for the Greek case. Further empirical research for deeper stock markets and/or a group of countries may be useful to reach conclusions regarding the financial trends’ influence on the calendar anomalies patterns. Practical implications – The findings are helpful to anyone who invests and deals with the Greek stock market. Moreover, they may pave the way for an alternative calendar anomalies research approach, proving useful for investors who take these anomalies into account when they plan their investment strategy. Originality/value – This paper contributes to the literature by presenting an alternative methodological approach regarding the calendar anomalies study and a new explanation for the calendar effects existence/fade through time by examining the calendar anomalies patterns under a changing economic environment and financial trends.