Fama French Factors
The Fama-French three-factor model (market, size, value), developed by Eugene Fama and Kenneth French, improves on the traditional CAPM model by explaining a larger fraction of long-term expected return variations. This data set also includes the momentum factor proposed by Mark Carhart.
Fama and French factors calculated over Swedish stocks from 1983 to 2019, aggregated by day, week and month.
- rm: market return (SIXRX index)
- rf: risk-free rate (1 month Swedish T-Bill)
- rm_rf: market return in excess of the risk-free rate
- SMB_ew: Small minus Big (equally weighted)
- HML_ew: High minus Low (equally weighted)
- MOM_ew: Winners minus Losers (equally weighted)
- SMB_vw: Small minus Big (value weighted)
- HML_vw: High minus Low (value weighted)
- MOM_vw: Winners minus Losers (value weighted)
Huseyin Aytug, Yao Fu and Paolo Sodini
This document explains the construction of the four-factor model using stock price and accounting data of Swedish listed companies following the Fama and French (1993) and the Carhart (1997) four-factor model. It uses data from the Finbas dataset collected and distributed by the SHoF National Data Center Website from 1983 to 2019. The variables used to construct stock portfolios and risk factors are defined and explained in detail.
"The Fama-French Carhart model is used to explain the cross-section of stock returns and improves dramatically on the CAPM model. It is not only used in many areas of research, such as fund performance evaluation, but also is the center of research investigation itself. We do not know yet if the FF-factors have a rational or behavioral explanation", says Paolo Sodini.