Even though earnings announcements are anticipated events in most cases, multiple academic papers find the evidence that they still affect stock prices and therefore create a potentially profitable trading opportunity. For instance, one of the recent works shows that the short-term reversal is much stronger around the days of earnings announcement than in other, randomly chosen periods. More precisely, the LOW-HIGH (buying past losers and selling past winners) strategy yielded an average 3-day return (the window of t-1, t, and t+1, where t is the day of earnings announcement) of 1.45% during the 1996-2011 sample period. In contrast, the average return during random pseudo-announcement periods was only 0.22% (therefore more than a six-fold difference). The phenomenon, as suggested by the authors, is related to market makers‘ decisions regarding liquidity provision (see fundamental reason). The strategy further described is carried out on the subsample of big stocks due to better liquidity.
In general, a reversal in the price of an asset occurs due to investors’ overreaction to asset-related news and the subsequent price correction. In this case, the most probable reason for the phenomenon, according to the authors, is the market makers’ aversion to inventory risks that tend to increase dramatically in the pre-announcement period. Consequently, the market makers demand higher compensation for providing liquidity due to higher risk and therefore raise prices, which are expected to reverse after the earnings announcement.
Backtest period from source paper
Confidence in anomaly's validity
Notes to Confidence in Anomaly's Validity
OOS back-test shows slightly negative performance. It looks, that strategy’s alpha is deteriorating in the out-of-sample period.
Notes to Indicative Performance
per annum, annualized (arithmetically, assuming 10 rebalances per quarter) average 3-day return of high-size stocks (Q5 SIZE quintile), data from table 5
Period of Rebalancing
Notes to Period of Rebalancing
Notes to Estimated Volatility
estimated from t-statistic, data from table 5
Number of Traded Instruments
Notes to Number of Traded Instruments
more or less, it depends on investor’s need for diversification
Notes to Maximum drawdown
Notes to Complexity Evaluation
Simple trading strategy
The investment universe consists of stocks listed at NYSE, AMEX, and NASDAQ, whose daily price data are available at the CRSP database. Earnings-announcement dates are collected from Compustat. Firstly, the investor sorts stocks into quintiles based on firm size. Then he further sorts the stocks in the top quintile (the biggest) into quintiles based on their average returns in the 3-day window between t-4 and t-2, where t is the day of the earnings announcement. The investor goes long on the bottom quintile (past losers) and short on the top quintile (past winners) and holds the stocks during the 3-day window between t-1, t, and t+1. Stocks in the portfolios are weighted equally.
Hedge for stocks during bear markets
Not known - Source and related research papers don’t offer insight into the correlation structure of the proposed trading strategy to equity market risk; therefore, we do not know if this strategy can be used as a hedge/diversification during the time of market crisis. The strategy is built as a long-short, but it can be split into two parts. The long leg of the strategy is surely strongly correlated to the equity market; however, the short-only leg might be used as a hedge during bad times. Rigorous backtest is, however, needed to determine return/risk characteristics and correlation.
Out-of-sample strategy's implementation/validation in QuantConnect's framework