Reversal in Post-Earnings Announcement Drift
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The post-earnings announcement drift (the tendency of stocks to drift in the direction of earnings announcement surprise during next quarter) is a well-known effect many times analyzed in academic literature. However, recent research speculates that maybe it is known too much.
Arbitrageurs started to exploit this anomaly, and it seems that the effect reversed in most liquid stocks. Research paper by Milian shows that stocks which had the worst return during past earning announcement deliver substantially better return during the days around the next earnings announcement. Classical PEAD (post-earnings announcement drift) literature examines mainly quarterly returns; therefore, it is probable that PEAD still holds. However, Milian's work shows a way how to profit from traders' over-reaction to a classical anomaly.
Fundamental reason
The academic paper speculates that it seems that due to their well-documented history of apparently underreacting to earnings news, investors are now overreacting to earnings announcement news. However, classical PEAD (post-earnings announcement drift) literature examines mainly quarterly portfolio returns while this academic paper focuses on 2-days return; therefore, it is probable that PEAD still holds and both anomalies exist concurrently.
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Keywords
Market Factors
Confidence in Anomaly's Validity
Notes to Confidence in Anomaly's Validity
Period of Rebalancing
Number of Traded Instruments
Notes to Number of Traded Instruments
Complexity Evaluation
Financial instruments
Backtest period from source paper
Indicative Performance
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Simple trading strategy
The investment universe consists of all stocks from NYSE, AMEX, and NASDAQ with active options market (so mostly large-cap stocks). Each day investor selects stocks which would have earnings announcement during the next working day. He then checks the abnormal performance of these stocks during the previous earnings announcement. Investor goes long decile of stocks with the lowest abnormal past earnings announcement performance and goes short stocks with the highest abnormal past performance. Stocks are held for two days, and the portfolio is weighted equally.
Hedge for stocks during bear markets
Unknown – 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(chart, statistics & code)
Source paper
Miliian: Overreacting to a History of Underreaction?
Abstract: Prior research has documented a long history of positive autocorrelation in firms’ earnings announcement news. This is one of the main features of the post-earnings announcement drift phenomenon and is typically attributed to investors’ underreaction to earnings news. I document that this autocorrelation has become significantly negative for firms with active exchange-traded options. For these easy-to-arbitrage firms, the firms in the highest decile of prior earnings announcement abnormal return (prior earnings surprise), on average, underperform the firms in the lowest decile by 1.29% (0.73%) at their next earnings announcement. Additional analyses are consistent with investors learning about post-earnings announcement drift and overcompensating. It seems that due to their well-documented history of apparently underreacting to earnings news, investors are now overreacting to earnings announcement news. This paper shows that attempts to exploit a popular trading strategy based on relative valuation can significantly reverse the previously documented pattern.