56 Pages Posted: 19 Nov 2014 Last revised: 5 Dec 2016
Date Written: November 16, 2016
I develop a method to extract only the priced factors from stock returns. First, I use multiple regression on anomaly characteristics to predict expected returns. Next, I form portfolios of stocks sorted by their expected returns. Then, I extract statistical factors from these sorts using principal components. The procedure isolates and emphasizes the comovement across assets that is related to expected returns as opposed to firm characteristics. The procedure produces level, slope and curve factors for stock returns. The factors perform better than the Fama and French (1993, 2014) three and five factor models and comparably to the four factor models of Carhart (1997), Novy-Marx (2013) and Hou, Xue, and Zhang (2012). Horse races show that other factors add little to the Level, Slope and Curve factors. The Level, Slope and Curve factors have macroeconomic interpretations. The factors capture strong variation in consumption growth across the sorted portfolios, and when embedded in an ICAPM, proxy for innovations to dividend yield, credit spread and stock volatility.
Keywords: Empirical Asset Pricing, Factor Models
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