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Digesting Anomalies: An Investment Approach

TLDR
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

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Citations
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Journal ArticleDOI

Volatility-Managed Portfolios

TL;DR: In this paper, the authors show that taking less risk when volatility is high produces large alphas, substantially increase factor Sharpe ratios, and produce large utility gains for mean-variance investors.
ReportDOI

Dissecting Characteristics Nonparametrically

TL;DR: This paper proposed a nonparametric method to test which characteristics provide independent information for the cross-section of expected returns, and used the adaptive group LASSO to select characteristics and to estimate how they affect expected returns nonparametrically.
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Left-Tail Momentum: Underreaction to Bad News, Costly Arbitrage and Equity Returns

TL;DR: In this paper, the authors provide a behavioral explanation to the left-tail risk anomaly based on the idea that investors underestimate the persistence in left tail risk and overprice stocks with large recent losses, thus, low returns in the left tail of the distribution persist into the future causing left tail return momentum.
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Innovative Originality, Profitability, and Stock Returns

TL;DR: Hirshleifer et al. as mentioned in this paper found that firms' innovative originality strongly predicts higher, more persistent, and less volatile profitability and higher abnormal stock returns, findings that are robust to extensive controls.
References
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Common risk factors in the returns on stocks and bonds

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.
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Risk, Return, and Equilibrium: Empirical Tests

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.
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Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency

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.
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Does the Stock Market Overreact

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.
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Multifactor Explanations of Asset Pricing Anomalies

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).
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