Post Loss/Profit Announcement Drift

Abstract

a b s t r a c tWe document a market failure to fully respond to loss/profit quarterly announcements. The annualized post portfolio formation return spread between two portfolios formed on extreme losses and extreme profits is approximately 21 percent. This loss/profit anomaly is incremental to previously documented accounting-related anomalies, and is robust to alternative risk adjustments, distress risk, firm size, short sales constraints, transaction costs, and sample periods. In an effort to explain this finding, we show that this mispricing is related to differences between conditional and unconditional probabilities of losses/profits, as if stock prices do not fully reflect conditional probabilities in a timely fashion.

How well do investors understand loss persistence?

“…They partition profit and loss firms based on 10 current earnings (scaled by total assets) and find that firms with big profits earn significantly positive future returns, while firms with big losses earn significantly negative future returns. To some extent, results in this study and those in Balakrishnan et al (2010) complement each other because current earnings is an important predictor of forecast earnings. However, forecast earnings contain more information about loss persistence than current earnings.…”

“…The contemporaneous research by Balakrishnan et al (2010) examines post-profit and post-loss announcement drift using quarterly data. They partition profit and loss firms based on 10 current earnings (scaled by total assets) and find that firms with big profits earn significantly positive future returns, while firms with big losses earn significantly negative future returns.…”

“…In this chapter, I examine whether the predictive power of forecast earnings is correlated 40 and subsumed by other commonly known return predictors. These predictors include book-tomarket ratio (BTM t ) (Fama and French, 1992), accruals (ACC t ) (e.g., Sloan, 1996;Richardson et al, 2005), price momentum (MOM t ) (e.g., Jegadeesh and Titman, 1993;Chan et al, 1996;Lee and Swaminathan, 2000), return volatility (VOL t ) (Ang et al, 2006), standardized unexpected earnings (SUE t ) (e.g., Bernard and Thomas, 1990;Ball and Bartov, 1996;Rangan and Sloan, 1998;Narayanamoorthy, 2006), earnings-to-price ratio (ETP t ) (e.g., Basu, 1977;Basu, 1983;Lakonishok et al, 1994), and return on assets (EARN t ) (Balakrishnan et al, 2010). I use a regression framework to simultaneously control for the effects of all these return predictors: …”

Beyond Sorting: A More Powerful Test for Cross-Sectional Anomalies

“…Following Balakrishnan et al (2010), we measure return on assets (Roa) as income before extraordinary items (item ibq) divided by 1-quarter-lagged total assets (item atq).…”

Evidências internacionais dos efeitos da atuação de investidores institucionais na anomalia dos accruals

“…A PAD foi documentada por vários outros autores e em diversos mercados, inclusive no brasileiro (Balakrishnan, Bartov, & Faurel, 2010;Bartov, 1992;Bernard & Thomas, 1989;Foster, Olsen, & Shevlin, 1984;Martinez, 2004;Paulo, Sarlo, & Santos, 2012;Watts, 1978).…”