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Digesting Anomalies: An Investment Approach

01 Oct 2012-Research Papers in Economics (Ohio State University, Charles A. Dice Center for Research in Financial Economics)-
TL;DR: In this paper, the authors proposed a new factor model that consists of the market factor, a size factor, an investment factor, and a return-on-equity factor.
Abstract: Motivated from investment-based asset pricing, we propose a new factor model that consists of the market factor, a size factor, an investment factor, and a return-on-equity factor The new model [i] outperforms the Carhart (1997) four-factor model in pricing portfolios formed on earnings surprise, idiosyncratic volatility, financial distress, equity issues, as well as on investment and return-on-equity; [ii] performs similarly as the Carhart model in pricing portfolios on momentum as well as on size and book-to-market; but [iii] underperforms in pricing the total accrual deciles Our model's performance, combined with its clear economic intuition, suggests that it can serve as a new workhorse model for academic research and investment management practice
Citations
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Journal ArticleDOI
TL;DR: In this paper, a five-factor model that adds profitability (RMW) and investment (CMA) factors to the three factor model of Fama and French (1993) suggests a shared story for several average-return anomalies.
Abstract: A five-factor model that adds profitability (RMW) and investment (CMA) factors to the three-factor model of Fama and French (1993) suggests a shared story for several average-return anomalies. Specifically, positive exposures to RMW and CMA (returns that behave like those of the stocks of profitable firms that invest conservatively) capture the high average returns associated with low market β, share repurchases, and low stock return volatility. Conversely, negative RMW and CMA slopes (like those of relatively unprofitable firms that invest aggressively) help explain the low average stock returns associated with high β, large share issues, and highly volatile returns.

605 citations

Journal ArticleDOI
TL;DR: The authors take up the challenge to identify the firm characteristics that provide independent information about average U.S. monthly stock returns by simultaneously including 94 characteristics in Fama-MacBeth regressions that avoid overweighting microcaps and adjust for data snooping bias.
Abstract: We take up Cochrane’s (2011) challenge to identify the firm characteristics that provide independent information about average U.S. monthly stock returns by simultaneously including 94 characteristics in Fama-MacBeth regressions that avoid overweighting microcaps and adjust for data snooping bias. We find that while 12 characteristics are reliably independent determinants in non-microcap stocks during 1980-2014 as a whole, return predictability fell sharply in 2003 such that just two characteristics have been independent determinants since then. Outside of microcaps, the hedge returns to exploiting characteristics-based predictability have also been insignificantly different from zero since 2003.

284 citations

Journal ArticleDOI
TL;DR: In this paper, the authors propose an instrumented principal component analysis (IPCA) model that allows for latent factors and time-varying loadings by introducing observable characteristics that instrument for the unobservable dynamic loadings.

262 citations

Journal ArticleDOI
TL;DR: In this paper, a robust stochastic discount factor (SDF) summarizing the joint explanatory power of a large number of cross-sectional stock return predictors is proposed.

235 citations

References
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Journal ArticleDOI
TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.

24,874 citations


"Digesting Anomalies: An Investment ..." refers background or methods or result in this paper

  • ...675 [16:13 2/2/2015 RFS-hhu068.tex] Page: 676 650–705 to capture, as well as the 25 size and book-to-market portfolios, which are the key testing portfolios for Fama and French (1993, 1996).12 3.2.1 Earnings momentum (SUE-1) and price momentum (R6-6)....

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  • ...Following Fama and French (2008), at the end of June of year t , we measure net stock issues (NSI) as the natural log of the ratio of the split-adjusted shares outstanding at the fiscal year ending in calendar year t −1 to the split-adjusted shares outstanding at the fiscal year ending in t −2....

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  • ...Because of transaction costs and lack of liquidity, the portion of anomalies in microcaps is unlikely to be exploitable in practice.10 When constructing annually sorted testing portfolios, such as the book-tomarket deciles, we follow the Fama and French (1993) timing....

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  • ...This interpretation is weaker than the risk factors interpretation per Fama and French (1993, 1996)....

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  • ...As shown in Fama and French (2008), despite accounting for about 60% of the total number of stocks, microcaps are on average only about 3% of the market capitalization of the NYSE-Amex-NASDAQ universe....

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Journal ArticleDOI
TL;DR: In this article, the relationship between average return and risk for New York Stock Exchange common stocks was tested using a two-parameter portfolio model and models of market equilibrium derived from the two parameter portfolio model.
Abstract: This paper tests the relationship between average return and risk for New York Stock Exchange common stocks. The theoretical basis of the tests is the "two-parameter" portfolio model and models of market equilibrium derived from the two-parameter portfolio model. We cannot reject the hypothesis of these models that the pricing of common stocks reflects the attempts of risk-averse investors to hold portfolios that are "efficient" in terms of expected value and dispersion of return. Moreover, the observed "fair game" properties of the coefficients and residuals of the risk-return regressions are consistent with an "efficient capital market"--that is, a market where prices of securities

14,171 citations


"Digesting Anomalies: An Investment ..." refers background in this paper

  • ...Fisher (1930) and Fama and Miller (1972, Figure 2.4) show that the interest rate and investment are negatively correlated. As noted, Cochrane (1991) and Liu, Whited, and Zhang (2009) extend this insight into a dynamic world with uncertainty....

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  • ...Fisher (1930) and Fama and Miller (1972, Figure 2....

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Journal ArticleDOI
TL;DR: In this article, the authors show that strategies that buy stocks that have performed well in the past and sell stocks that had performed poorly in past years generate significant positive returns over 3- to 12-month holding periods.
Abstract: This paper documents that strategies which buy stocks that have performed well in the past and sell stocks that have performed poorly in the past generate significant positive returns over 3- to 12-month holding periods. We find that the profitability of these strategies are not due to their systematic risk or to delayed stock price reactions to common factors. However, part of the abnormal returns generated in the first year after portfolio formation dissipates in the following two years. A similar pattern of returns around the earnings announcements of past winners and losers is also documented

10,806 citations


"Digesting Anomalies: An Investment ..." refers background in this paper

  • ...1 See, for example, Ball and Brown (1968); Bernard and Thomas (1990); Ritter (1991); Jegadeesh and Titman (1993); Ikenberry, Lakonishok, and Vermaelen (1995); Loughran and Ritter (1995); © The Author 2014....

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  • ...…(6-month prior returns, R6-6 Price momentum (6-month prior returns, 1-month holding period), 6-month holding period), Jegadeesh and Titman (1993) Jegadeesh and Titman (1993) R11-1 Price momentum (11-month prior returns, I-Mom Industry momentum, 1-month holding period), Moskowitz and…...

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  • ...…(1996) R6-1 Price momentum (6-month prior returns, R6-6 Price momentum (6-month prior returns, 1-month holding period), 6-month holding period), Jegadeesh and Titman (1993) Jegadeesh and Titman (1993) R11-1 Price momentum (11-month prior returns, I-Mom Industry momentum, 1-month holding…...

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Journal ArticleDOI
TL;DR: In this article, a study of market efficiency investigates whether people tend to "overreact" to unexpected and dramatic news events and whether such behavior affects stock prices, based on CRSP monthly return data, is consistent with the overreaction hypothesis.
Abstract: Research in experimental psychology suggests that, in violation of Bayes' rule, most people tend to "overreact" to unexpected and dramatic news events. This study of market efficiency investigates whether such behavior affects stock prices. The empirical evidence, based on CRSP monthly return data, is consistent with the overreaction hypothesis. Substantial weak form market inefficiencies are discovered. The results also shed new light on the January returns earned by prior "winners" and "losers." Portfolios of losers experience exceptionally large January returns as late as five years after portfolio formation. As ECONOMISTS INTERESTED IN both market behavior and the psychology of individual decision making, we have been struck by the similarity of two sets of empirical findings. Both classes of behavior can be characterized as displaying overreaction. This study was undertaken to investigate the possibility that these phenomena are related by more than just appearance. We begin by describing briefly the individual and market behavior that piqued our interest. The term overreaction carries with it an implicit comparison to some degree of reaction that is considered to be appropriate. What is an appropriate reaction? One class,,of tasks which have a well-established norm are probability revision problems for which Bayes' rule prescribes the correct reaction to new information. It has now been well-established that Bayes' rule is not an apt characterization of how individuals actually respond to new data (Kahneman et al. [14]). In revising their beliefs, individuals tend to overweight recent information and underweight prior (or base rate) data. People seem to make predictions according to a simple matching rule: "The predicted value is selected so that the standing of the case in the distribution of outcomes matches its standing in the distribution of impressions" (Kahneman and Tversky [14, p. 416]). This rule-of-thumb, an instance of what Kahneman and Tversky call the representativeness heuristic, violates the basic statistical principal that the extremeness of predictions must be moderated by considerations of predictability. Grether [12] has replicated this finding under incentive compatible conditions. There is also considerable evidence that the actual expectations of professional security analysts and economic forecasters display the same overreaction bias (for a review, see De Bondt [7]). One of the earliest observations about overreaction in markets was made by J. M. Keynes:"... day-to-day fluctuations in the profits of existing investments,

7,032 citations


"Digesting Anomalies: An Investment ..." refers background or methods in this paper

  • ...As such, firms with high long-term prior returns should invest more and earn lower expected returns than firms with low long-term prior returns, meaning that the investment channel also helps interpret the De Bondt and Thaler (1985) long-term reversal effect....

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  • ...To capture the De Bondt and Thaler (1985) long-term reversal (Rev) effect, at the beginning of each month t, we use NYSE breakpoints to split stocks into deciles based on the prior returns from month t − 60 to t − 13....

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  • ...To be comprehensive, we cover all the major 663 [16:13 2/2/2015 RFS-hhu068.tex] Page: 664 650–705 Table 2 List of anomalies Panel A: Momentum SUE-1 Earnings surprise (1-month holding period), SUE-6 Earnings surprise (6-month holding period), Foster, Olsen, and Shevlin (1984) Foster, Olsen, and Shevlin (1984) Abr-1 Cumulative abnormal stock returns Abr-6 Cumulative abnormal stock returns around earnings announcements around earnings announcements (1-month holding period), (6-month holding period), Chan, Jegadeesh, and Lakonishok (1996) Chan, Jegadeesh, and Lakonishok (1996) RE-1 Revisions in analysts’ earnings forecasts RE-6 Revisions in analysts’ earnings forecasts (1-month holding period), (6-month holding period), Chan, Jegadeesh, and Lakonishok (1996) Chan, Jegadeesh, and Lakonishok (1996) R6-1 Price momentum (6-month prior returns, R6-6 Price momentum (6-month prior returns, 1-month holding period), 6-month holding period), Jegadeesh and Titman (1993) Jegadeesh and Titman (1993) R11-1 Price momentum (11-month prior returns, I-Mom Industry momentum, 1-month holding period), Moskowitz and Grinblatt (1999) Fama and French (1996) Panel B: Value-versus-growth B/M Book-to-market equity, A/ME Market leverage, Bhandari (1988) Rosenberg, Reid, and Lanstein (1985) Rev Reversal, De Bondt and Thaler (1985) E/P Earnings-to-price, Basu (1983) EF/P Analysts’ earnings forecasts-to-price, CF/P Cash flow-to-price, Elgers, Lo, and Pfeiffer (2001) Lakonishok, Shleifer, and Vishny (1994) D/P Dividend yield, O/P Payout yield, Litzenberger and Ramaswamy (1979) Boudoukh et al. (2007) NO/P Net payout yield, SG Sales growth, Boudoukh et al. (2007) Lakonishok, Shleifer, and Vishny (1994) LTG Long-term growth forecasts of analysts, Dur Equity duration, La Porta (1996) Dechow, Sloan, and Soliman (2004) Panel C: Investment ACI Abnormal corporate investment, I/A Investment-to-assets, Titman, Wei, and Xie (2004) Cooper, Gulen, and Schill (2008) NOA Net operating assets, PI/A Changes in property, plant, and equipment Hirshleifer et al. (2004) plus changes in inventory scaled by assets, Lyandres, Sun, and Zhang (2008) IG Investment growth, Xing (2008) NSI Net stock issues, Pontiff and Woodgate (2008) CEI Composite issuance, NXF Net external financing, Daniel and Titman (2006) Bradshaw, Richardson, and Sloan (2006) IvG Inventory growth, Belo and Lin (2011) IvC Inventory changes, Thomas and Zhang (2002) OA Operating accruals, Sloan (1996) TA Total accruals, Richardson et al. (2005) POA Percent operating accruals, PTA Percent total accruals, Hafzalla, Lundholm, and Van Winkle (2011) Hafzalla, Lundholm, and Van Winkle (2011) Panel D: Profitability ROE Return on equity, ROA Return on assets, Haugen and Baker (1996) Balakrishnan, Bartov, and Faurel (2010) RNA Return on net operating assets, PM Profit margin, Soliman (2008) Soliman (2008) ATO Asset turnover, Soliman (2008) CTO Capital turnover, Haugen and Baker (1996) GP/A Gross profits-to-assets, Novy-Marx (2013) F F -score, Piotroski (2000) TES Tax expense surprise, TI/BI Taxable income-to-book income, Thomas and Zhang (2011) Green, Hand, and Zhang (2013) RS Revenue surprise, NEI Number of consecutive quarters with earnings Jegadeesh and Livnat (2006) increases, Barth, Elliott, and Finn (1999) FP Failure probability, O O-score, Dichev (1998) Campbell, Hilscher, and Szilagyi (2008) (continued) 664 [16:13 2/2/2015 RFS-hhu068.tex] Page: 665 650–705 This table lists the anomalies that we study....

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  • ...As such, firms with high long-term prior returns should invest more and earn lower expected returns than firms with low longterm prior returns, meaning that the investment channel also helps interpret the De Bondt and Thaler (1985) long-term reversal effect....

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  • ...…B: Value-versus-growth B/M Book-to-market equity, A/ME Market leverage, Bhandari (1988) Rosenberg, Reid, and Lanstein (1985) Rev Reversal, De Bondt and Thaler (1985) E/P Earnings-to-price, Basu (1983) EF/P Analysts’ earnings forecasts-to-price, CF/P Cash flow-to-price, Elgers, Lo, and…...

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Journal ArticleDOI
TL;DR: In this article, the authors show that many of the CAPM average-return anomalies are related, and they are captured by the three-factor model in Fama and French (FF 1993).
Abstract: Previous work shows that average returns on common stocks are related to firm characteristics like size, earnings/price, cash flow/price, book-to-market equity, past sales growth, long-term past return, and short-term past return. Because these patterns in average returns apparently are not explained by the CAPM, they are called anomalies. We find that, except for the continuation of short-term returns, the anomalies largely disappear in a three-factor model. Our results are consistent with rational ICAPM or APT asset pricing, but we also consider irrational pricing and data problems as possible explanations. RESEARCHERS HAVE IDENTIFIED MANY patterns in average stock returns. For example, DeBondt and Thaler (1985) find a reversal in long-term returns; stocks with low long-term past returns tend to have higher future returns. In contrast, Jegadeesh and Titman (1993) find that short-term returns tend to continue; stocks with higher returns in the previous twelve months tend to have higher future returns. Others show that a firm's average stock return is related to its size (ME, stock price times number of shares), book-to-marketequity (BE/ME, the ratio of the book value of common equity to its market value), earnings/price (E/P), cash flow/price (C/P), and past sales growth. (Banz (1981), Basu (1983), Rosenberg, Reid, and Lanstein (1985), and Lakonishok, Shleifer and Vishny (1994).) Because these patterns in average stock returns are not explained by the capital asset pricing model (CAPM) of Sharpe (1964) and Lintner (1965), they are typically called anomalies. This paper argues that many of the CAPM average-return anomalies are related, and they are captured by the three-factor model in Fama and French (FF 1993). The model says that the expected return on a portfolio in excess of the risk-free rate [E(Ri) - Rf] is explained by the sensitivity of its return to three factors: (i) the excess return on a broad market portfolio (RM - Rf); (ii) the difference between the return on a portfolio of small stocks and the return on a portfolio of large stocks (SMB, small minus big); and (iii) the difference between the return on a portfolio of high-book-to-market stocks and the return on a portfolio of low-book-to-market stocks (HML, high minus low). Specifically, the expected excess return on portfolio i is,

6,737 citations


"Digesting Anomalies: An Investment ..." refers background or methods or result in this paper

  • ...675 [16:13 2/2/2015 RFS-hhu068.tex] Page: 676 650–705 to capture, as well as the 25 size and book-to-market portfolios, which are the key testing portfolios for Fama and French (1993, 1996).12 3.2.1 Earnings momentum (SUE-1) and price momentum (R6-6)....

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  • ...This interpretation is weaker than the risk factors interpretation per Fama and French (1993, 1996)....

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  • ...Consistent with Fama and French (1993, 1996), our factor regressions provide direct evidence that the q-factors capture shared variation in returns across a wide array of anomaly portfolios....

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  • ...Following MacKinlay (1995), 13 The small-growth anomaly is notoriously difficult to capture (e.g., Fama and French 1993, 1996; Davis, Fama, and French 2000; and Campbell and Vuolteenaho 2004)....

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  • ...…and Titman (1993) R11-1 Price momentum (11-month prior returns, I-Mom Industry momentum, 1-month holding period), Moskowitz and Grinblatt (1999) Fama and French (1996) Panel B: Value-versus-growth B/M Book-to-market equity, A/ME Market leverage, Bhandari (1988) Rosenberg, Reid, and Lanstein…...

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