Common risk factors in the returns on stocks and bonds

By Eugene F. Fama, Kenneth R. French. 1993

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Citations in the corpus

Deep Learning for Predicting Asset Returns (2018, background): “Predicting asset returns is important to empirical ﬁnance and factor models play a central role, for example, see Rosenberg et al. (1976) and Fama and French (1993).”
Improving stock market prediction via heterogeneous information fusion (2017, methodology): “Based on the previous studies [45, 12], we choose four common quantitative features, that is, the share turnover, the price-to-earning (P/E) ratio, the price-to-book (P/B) ratio and the price-to-cash-ﬂow (PCF) ratio.”
Tensor-Based Learning for Predicting Stock Movements (2015, unknown): “Recent studies show that news articles play an important role in short-term stock movements (Fama and French 1993; Li et al. 2014a).”
Investment Banking and Securities Issuance (2003, methodology): “…starting with Loughran and Ritter (1995), the long-run returns literature has commonly used 3-factor time-series regressions, introduced by Fama and French (1993), of the form rpt - rft = a + b(rmt - rft) + sSMBt + vVMGt + ept where rpt - rft is the excess return over the risk-free rate…”
Preserving Socioemotional Wealth in Family Firms: Asset or Liability? The Moderating Role of Business Context (2013, background): “The main objectives of these rules are objectivity, transparency of business operations, and independence between firm business activities and governance bodies (Fama & French, 1993; Villalonga & Amit, 2006).”
Downside risk and asset pricing (2004, background): “The celebrated Fama and French (1993) (1996) papers focus on this particularly anomalous sample period.”
Mutual fund ownership, firm specific information, and firm performance: evidence from China (2013, methodology): “This measure of performance reflects a firm’s growth opportunities (Fama and French, 1995). We use industry adjusted natural log transformed MTB as our performance measure. Cornett et al., (2007) argue that the measures of operating performance provide two incentives over measures of the market valu”
Once Burned, Twice Shy: How Naive Learning, Counterfactuals, and Regret Affect the Repurchase of Stocks Previously Sold (2011, unknown): “To determine if any observed abnormal returns can be explained by investment style— that is, by stock characteristics known to affect returns—we also employ a four-factor model that includes market, size, value, and momentum factors (Carhart 1997; Fama and French 1993).”
Do women managers keep firms out of trouble? Evidence from corporate litigation and policies (2019, methodology): “Where applicable we control for year fixed effects to account for any time-trend in lawsuits, and industry fixed effects using Fama and French (1993) 48 industries to account for differences in litigation risk across industries.”
Is the Abnormal Return Following Equity Issuances Anomalous (2000, unknown): “This notion follows the empirical observation of Jegadeesh and Titman (1993) that "rms having high returns in the previous year tend to continue to enjoy high returns in the next year. His factor, PR12, is formed by taking the return on high momentum stocks minus the return on low momentum stocks.4 ”
Mutual Fund Incubation (2010, methodology): “[Table IX Goes Here] Two different measures of monthly fund performance are used in the regression; 1-factor alpha (Jensen, 1968) and 4-factor alpha (Fama and French, 1993 and Carhart, 1997).”
What Determines Chinese Stock Returns? (2004, unknown): “Fama and French (1993) sorted stocks independently by size and by book to market.”
The Long-Term Performance of Corporate Bonds (and Stocks) Following Seasoned Equity Offerings (2002, methodology): “We follow the procedures explained in Fama and French (1993) for forming the SMB and HML factors.”
Monthly Measurement of Daily Timers (2000, unknown): “Also, our approach is similar to that advocated by Fama and French (1993); our two excess returns on bond indexes capture the term premium and the default premium.”