COVID-19 and investor behavior

The novel coronavirus has led to unprecedented repercussions on daily life and the economy. The efforts to contain the virus have led to a temporary lockdown of almost all major economies worldwide. While the aggregate effect of the pandemic on the stock market and the spending behavior of households have been documented, little is known about the behavior of retail investors during such a turbulent time. It is, however, important to investigate the behavior of investors in these unprecedented conditions at the micro-level to allow for a better understanding of aggregate market outcomes. In this paper, the scientists explore how retail investors respond to the outbreak of COVID-19 and investigate how a pandemic influences trading patterns and financial risk-taking based on a large sample of trading records of retail investors.

For this, they use three arguments to express contrasting expectations about investor behavior during the COVID-19 outbreak:

• the outbreak of the pandemic is in many regards comparable to terrorist attacks: it is an exogenous shock, that has drastic consequences on everyday life, raises public fear, and causes great (economic) uncertainty. Investor behavior in the aftermath of terrorist activity is associated with more risk averse choices, such as a reduced trading intensity and a reduced flow to risky assets.

The research group use transactional-level brokerage data from a UK-based discount broker that offers an online trading platform to retail investors. The broker allows its clients to trade stocks (stocks) and contracts for difference (CFD) on stock market indizes (index), cryptocurrencies (crypto), commodities (gold), foreign exchange rates, and single name stocks (CFD_stock). The data sample contains all trades that the investors executed with the broker between August 1, 2019 and April 17, 2020. The majority of transactions in our data is based on indizes (∼24%), followed by cryptocurrencies (∼20%), CFDs on single name stocks (∼19%), and single name stocks (∼15%). The data contain the exact time- stamp and instrument of the trade, an indicator for long or short positions, the executed rate, the leverage, and the investment. The dataset quotes all trades in USD irrespective of the currency in which the underlying instrument trades and comprises net returns of closed positions after adjusting for stock splits, dividends, and transaction costs. In total, the dataset contains 45,003,637 transactions executed by 456,365 investors.

Additionally, the dataset includes the deposits to and withdrawals from the brokerage accounts that investors initiate. The data also contain information on push notifications that the broker sends to investors to alert them of volatility events (see Arnold et al., 2019). Lastly, the dataset comprises basic demographic information, such as age and gender.

Data on the number of cases and deaths due to COVID-19 from the European Centre for Disease Prevention and Control is obtained. In addition, they hand collect information on lockdowns and other restrictions on public life.

Formally, the researchers study the relation between the outbreak of COVID-19 and investors’ trading activities using an OLS regression analysis and use several variables to proxy investors’ trading activities.