key: cord-0704421-9ein4v6m authors: Dong, Hang; Gil-Bazo, Javier; Ratiu, Raluca title: Information Demand during the COVID-19 Pandemic date: 2021-10-21 journal: Journal of Accounting and Public Policy DOI: 10.1016/j.jaccpubpol.2021.106917 sha: a20d5b211216037850636d2f75e26ee95b5d9002 doc_id: 704421 cord_uid: 9ein4v6m 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 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. The COVID-19 pandemic (henceforth, the pandemic) caused an array of changes in financial markets around the world. No individuals, companies or countries remained immune to the uncertainty created by the pandemic. Greater uncertainty about future company earnings was best reflected by the VIX index reaching in March 2020 its highest level in more than a decade. In this paper, we ask whether and how the pandemic impacted retail investors' demand for financial information in these times of extreme uncertainty. To answer this question, we use Google search data for individual stocks to explore the link between the pandemic, and more specifically its severity in the US, and the demand for financial information. The pandemic affected both the willingness and ability of retail investors to collect and process financial information. On the one hand, greater uncertainty provided investors with stronger incentives to gather information. Indeed, financial information can help investors identify which firms are more vulnerable to the pandemic, as well as which firms may benefit from the opportunities created by the new situation. This information includes exposure to the effects of lockdowns and travel restrictions, as well as the financial conditions that firms experienced prior to the pandemic. On the other hand, the pandemic had a profound and direct impact on individuals' personal lives. Adapting to the new circumstances (school closures, work-from-home, lockdowns, new health practices) imposed large demands on individuals' time and attention, which may have reduced their commitment to other, less essential, activities. Moreover, social isolation and uncertainty about the future resulted in increased levels of anxiety and depression, which are likely to alter individuals' ability to make important decisions (Brodeur et al., 2021) . Whether the net impact of the pandemic on the demand for financial information was positive or negative is ultimately an empirical question. To answer this question, we follow previous studies on information demand (Da et al., 2011; Drake et al., 2012 Drake et al., , 2017 , and use the Abnormal Google Search Volume Index (ASVI) as a proxy for financial information demand. In particular, we study how stock-specific ASVI changed during the initial months of the COVID-19 pandemic, i.e., March to June 2020. To proxy for the severity of the pandemic, we use four different variables: Number of confirmed cases; Stringency index; Infection Index; and the COVID-19 time dummy. We define these variables in section 2.2. In our empirical analysis, we first study how ASVI changes during the pandemic controlling for stock characteristics, and particularly characteristics related to the supply of information and trading activity. We find that ASVI decreases in the initial months of the pandemic: abnormal weekly searches of a given stock are 0.37 standard deviations lower in the pandemic months than in the pre-pandemic period. Second, we follow Drake et al. (2012) and compare ASVI around earnings announcements before and during the pandemic. We find that ASVI around earnings announcements decreases during the pandemic, consistent with a decline in the demand for financial information. We also test for potential heterogeneity in the evolution of searches across stocks. Finally, we discuss several possible explanations for our results in section 4. Based on previous literature and available empirical evidence, we argue that individuals shifted their search interests from financial information to information related to the pandemic and its direct effects on their personal lives. Our results are of special interest to regulators and policy makers. In particular, our results suggest that, despite the strong benefits of reducing asymmetric information in times of uncertainty, investors may not be able to collect and process financial information when extreme circumstances affect not only financial markets but also their personal lives. Regulators and policy makers should therefore acknowledge that investors' limitations are aggravated during such times and consider alternatives to the traditional ways of disseminating information aimed at overcoming investors' difficulties in using financial information when it is most needed. We obtain the Google Search Volume Index (SVI) from Google Trends following the procedure of Da et al. (2011) and Drake et al. (2012) . We focus on S&P 500 companies and use stock tickers as the search keywords. The original SVI data includes weekly SVI covering S&P 500 constituents, at the national level, spreading from July 2019 to June 2020. 1 We remove 32 tickers that potentially have alternative meanings. We also require all observations to appear in other data sources, i.e., Thomson Reuters' Refinitiv Eikon and I/B/E/S. The clearing data process leaves us with 16,268 observations covering 459 stocks and 48 weeks. Similar to other studies using Google search data, our variable of interest is the abnormal search volume (ASVI), that is, the increase in SVI relative to expected SVI. More specifically, we define ASVI for a given stock and week as the natural logarithm of SVI for that stock and week minus the natural logarithm of the average SVI in the previous 10 weeks. 2 That is, Where denotes the abnormal search volume for stock i in week w; is the raw , , Google Search Volume Index for stock i in week w, and is the average of the raw SVI , during the previous 10 weeks. Using the detrended ASVI measure instead of the raw SVI data allows us to disentangle the effect of the pandemic on searches from that of pre-pandemic trends. We use four variables to proxy for the severity of the pandemic in the US. We obtain the date of earnings announcements for all firms in our sample from Compustat. We define a dummy variable, , that equals one if stock i issues an earnings , announcement during week w, and zero, otherwise. Following Drake et al. (2012), we use several variables as controls. In particular, we include: , and the bid-ask spread ( We use the natural logarithm of one plus the variable for , ). , and . These data are obtained from Thomson , , , Reuters' Refinitiv Eikon. Descriptive statistics for the sample are available from the authors. Before proceeding with the analysis, we explore the evolution of ASVI around the pandemic. infections. Whereas the value of ASVI centers around 0.2 before the pandemic, it is close to zero in the period from April to June 2020. Therefore, a visual inspection of the data suggests that the demand for financial information, as captured by abnormal searches for stocks, did not increase with the uncertainty surrounding the pandemic and in fact, it decreased fast as the disease spread. In the following subsections, we formally test for changes in ASVI following the pandemic, while controlling for variation in stock fundamentals that determine the demand for information as well as information supply. To study the link between the pandemic and stock searches, we estimate the following regression equation: , As argued by Drake et al (2012) , Google searches are best identified with demand for financial information when a corporate event takes place. Therefore, we explore how ASVI changes around earnings announcements in the pandemic. For the sake of brevity, we focus on the number of cases as a proxy for the severity of the pandemic. We regress ASVI on the , an earnings announcement dummy, and their interaction term: 5 , = + 1 + 2 , + + 3 (3) × , + + + , , + there is an earnings announcement for stock i in week w+p. We consider three different values for p: -1, (one week before the announcement), 0 (the week when the announcement is released), and 1 (one week after the announcement). We also define another variable, , that equals one if there is an earnings announcement for stock i from week w-, -1/ + 1 1 to week w+1, and zero otherwise. Our results suggest that abnormal searches for stocks declined on average with the pandemic. However, one could expect that abnormal searches evolved differently for different firms since the potential impact of the pandemic was also heterogeneous across stocks. In particular, while some firms were more vulnerable to the pandemic, others actually benefitted from it. To explore this possibility, we rank stocks based on their return between March 13 and June 30 and sort them into 5 quintile groups (5 = highest and 1 = lowest). We then estimate again regression equation (1) augmented with interaction variables between the search variable, ASVI, and dummy variables for each group (the bottom decile dummy is omitted). Table 3 reports the results. The estimated coefficients of the interaction terms are all statistically insignificant. Therefore, the decline in overall abnormal searches for stock information appears to have been similar for pandemic winners, losers, as well as stocks less affected by the pandemic. Following Drake et al., (2012) , we have chosen a 10-week moving average as a benchmark for search volume. As explained above, by detrending searches, we reduce the risk that our results are driven by a possible pre-trend in Google searches. However, it is a priori unclear what the optimal length of the rolling window should be. As a robustness test, we repeat the analysis for various additional lengths ranging from 15 to 25 weeks. The results (available upon request) are qualitatively similar, although weaker for the longest horizons. Another potential concern is whether our results are explained by an overall decrease in In this section, we discuss different explanations for our results. As argued in the introduction, the pandemic and its associated lockdowns may have changed individuals' ability and willingness to engage in the process of collecting and processing financial information. Indeed, the pandemic imposed new demands on individuals' time and attention. Also, lockdowns and social distancing may have had important negative effects on individuals' well-being. However, we also consider two alternative hypotheses. First, it could be that investors consciously chose to avoid risky, potentially negative information about the stock market. This is the "ostrich effect," which has been shown to affect investor behavior and price formation (Galai & Sade, 2006; Karlsson et al., 2009 (Russo et al., 2021) . However, individuals did not respond to the challenges of the new situation by avoiding negative information. To the contrary, the evidence suggests that people actively sought information on the new disease, its evolution, and its consequences, as evidenced by the fact that the number of visitors to the website of the Center for Disease Control and Prevention jumped to over 49 million in March 2020 from only 5 million in December 2019. 9 Moreover, an inspection of top Google searches during 2020 reveals that the terms "Coronavirus," "Coronavirus updates," and "Coronavirus symptoms" were among the five most searched terms during 2020. 10 Other popular searches suggest that people learned new skills that helped them stay safe (e.g., "How to make hand sanitizer," "How to make a mask with fabric"). Taken together, the evidence seems to support the hypothesis that the pandemic challenged individuals' lives in fundamental ways, changing their priorities and concerns. The evidence, however, does not seem consistent with the ostrich effect. As for the hypothesis that historical financial information became less relevant during the pandemic, Ding et al., (2021) document that firm characteristics before 2020 strongly explain differences in stock returns during the January-May 2020 period. More specifically, the authors find that firms with better financial conditions and more CSR activities experienced better stock returns while those more exposed to COVID-19 through supply chains and customers underperformed. This evidence does not appear to support the hypothesis that financial information became disconnected from financial performance during the COVID-19 crisis. In sum, searches for stocks declined during the pandemic despite an increase in overall searches. The evidence is not consistent with the ostrich effect (investors avoiding negative information) or with a decrease in the predictive ability of account information. Instead, we believe that many investors have spent more (non-leisure) time and effort in other activities such as childcare, housework, keeping themselves and their families healthy, staying informed, or learning new skills, at the expense of non-essential activities. users to show that these investors trade on the information provided by the app itself or by the media The Unprecedented Stock Market Impact of COVID-19 Attention Induced Trading and Returns: Evidence from Robinhood Users What Explains Differences in Finance Research Productivity During the Pandemic? COVID-19, lockdowns and well-being: Evidence from Google Trends Search of Attention COVID-19 Disruptions Disproportionately Affect Female Academics Corporate Immunity to the COVID-19 pandemic The Comovement of Investor Attention Investor Information Demand: Evidence from Google Searches around Earnings Announcements The "Ostrich Effect" and the Relationship Between the Liquidity and the Yields of Financial Assets A Global Panel Database of Pandemic Policies The Ostrich Effect: Selective Attention to Information Flattening the Illiquidity Curve: Retail Trading During the COVID-19 Lockdown Predictors of Wellbeing and Productivity Among Software Professionals during the COVID-19 Pandemic -A longitudinal Study