Risk Versus Mispricing in the Fama–French Three-Factor Model
Summary
The document introduces the Fama–French three-factor return model, in which market exposure is supplemented by size and value factors. It asks whether the significance and persistence of the size and value premiums show that small-cap and value stocks carry additional risk, or instead reflect pricing errors that the model captures. The discussion frames these as competing interpretations rather than resolving the question.
The answer notes that persistent returns alone do not establish that a factor is compensation for risk. It summarizes research arguing that stock characteristics may explain returns better than factor-based risk accounts, while also mentioning theoretical explanations involving investors’ human capital and hedging needs. It cites evidence that the factors appear across periods and markets, but gives no study designs, quantitative estimates, or definitive conclusion. The material is therefore a short map of the debate, not a systematic review of the evidence or a test of either explanation.
Key ideas
- The model adds size and value exposures to market exposure when explaining returns.
- Significant factor loadings do not by themselves establish that the factors represent priced risk.
- Persistent value returns can be interpreted as compensation for risk or as mispricing.
- Characteristics-based explanations and human-capital hedging arguments are among the perspectives mentioned.
- The discussion offers no definitive resolution or detailed quantitative comparison of the explanations.
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Full text
# Fama-French 3-factor model: factors implying risk
# Fama-French 3-factor model: factors implying risk
The Fama-French three-factor risk model is given by $$ r=R_f+\beta_m(K_m-R_f) + \beta_s\cdot\mathit{SMB}+\beta_v\cdot\mathit{HML}+\alpha $$ where $r$ is the return, $R_f$ is the risk-free rate, $K_m$ is the market return, $SMB$ is the Small Minus Big factor and $HML$ is the High Minus Low factor. $\alpha$ and the $\beta$'s are estimated from the data and $\alpha$ can be interpreted as excess return not explained by the model.
Both $\beta_s$ and $\beta_v$ are highly significant and thus the CAPM (where $\beta_s = \beta_v = 0$) does not hold. This result can be explained in the two ways: the first is that this is a stock pricing anomaly and $\alpha$ can be obtained. This does not seem to be the case as the anomaly has persisted.
The second is that investing in small cap or value stocks carries extra risk and that the FF 3-factor model just explains risk better than the CAPM does. This interpretation is in line with semi-strong EMH but does not satisfy me. Why should small cap or value stocks be more risky? Economists can come up with all kinds of interesting narratives but have these narratives been tested quantitatively? And what were the results?
## Answer by Slow Learner (score 10, accepted)
https://quant.stackexchange.com/a/9235
There is no definitive answer to this question and there are infinite papers out there. I personally think they are better explained as mispricings. Several points:
1) Persistence of HML does not imply it has to be a risk factor. If there are idiosyncratic mispricings in individual stocks, then by construction, the ones that look cheap are going to be actually cheap.
This is a related (though somewhat involved) criticism of the risk-factor interpretation: http://finance.wharton.upenn.edu/~rlwctr/papers/9315.PDF
2) Here is some nice evidence that those factors aren't risk-factors and are more likely mispricings. At least they seem better explained by characteristics than factors: http://ww.andreisimonov.com/Microstr_PhD/MSU_09/DanielTitman97.pdf
3) There are attempts to find theoretical explanations for those factors. For instance people hypothesized (if my memory works) that the value factor is correlated with human capital, and therefore despite value stocks have higher returns, growth stocks are better hedges for investors if you think they are optimizing overall (taking into account the variability of their human capital).
4) Aside: yes those factors work quite consistently across time and markets: http://www.master272.com/finance/longshort/ff_growthvalue.pdfShown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.