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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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Who Cares about Purity of Factor Indexes? A Comment on “Evaluating the Efficiency of ‘Smart Beta’ Indexes”

TL;DR: In this paper, the authors pointed out several questions regarding the relevance of factor efficiency ratios and similar assessments of purity of factor indexes and concluded that the indexes analyzed were generally unable to provide desired factor exposures without taking on substantial unintended exposures and that indexes are not pure in their delivery of intended factor exposures.
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Momentum crashes and variations to market liquidity

TL;DR: This article showed that the variation in market liquidity is an important determinant of momentum crashes that is independent of other known explanations surfaced on this topic, driven by the asymmetric large return sensitivity of short-leg of momentum portfolio to changes in the market liquidity that flares the tail risk of momentum strategy in panic states.
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An Intertemporal Risk Factor Model

TL;DR: In this paper, the authors implement a tradable ICAPM to capture market and inter-temporal risk, and construct a long-short portfolios based on stock exposures to dividend yield and realized volatility, and show that they reflect mimicking portfolios for longterm expected returns and volatility.
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Anomalies in the Joint Cross Section of Equity and Corporate Bond Returns

TL;DR: This paper examined the cross-section of equity and corporate bond returns and found that the risk premia in one market should appear in the other, and their magnitudes should be consistent with each other.
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Asset Pricing and Machine Learning: A critical review

TL;DR: In this article , the authors review and critically assess the most recent and relevant contributions in the literature grouping them into five categories defined by the Machine Learning (ML) approach they employ: regularization, dimension reduction, regression trees/random forest (RF), neural networks (NNs), and comparative analyses.
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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