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In asset pricing and portfolio management the Fama–French three-factor model is a model designed by Eugene Fama and Kenneth French to describe stock returns. Fama and French were professors at the University of Chicago Booth School of Business, where Fama still resides. The traditional asset pricing model, known formally as the capital asset pricing model (CAPM) uses only one variable to describe the returns of a portfolio or stock with the returns of the market as a whole. In contrast, the Fama–French model uses three variables. Fama and French started with the observation that two classes of stocks have tended to do better than the market as a whole: (i) small caps and (ii) stocks with a low Price-to-Book ratio (P/B, customarily called value stocks, contrasted with growth stocks). They then added two factors to CAPM to reflect a portfolio's exposure to these two classes: : Here r is the portfolio's expected rate of return, ''R''''f'' is the risk-free return rate, and ''K''''m'' is the return of the market portfolio. The "three factor" ''β'' is analogous to the classical ''β'' but not equal to it, since there are now two additional factors to do some of the work. ''SMB'' stands for "Small (capitalization ) Minus Big" and ''HML'' for "High (ratio ) Minus Low"; they measure the historic excess returns of small caps over big caps and of value stocks over growth stocks. These factors are calculated with combinations of portfolios composed by ranked stocks (BtM ranking, Cap ranking) and available historical market data. Historical values may be accessed on (Kenneth French's web page ). Moreover, once SMB and HML are defined, the corresponding coefficients ''b''''s'' and ''b''''v'' are determined by linear regressions and can take negative values as well as positive values. The Fama–French three-factor model explains over 90% of the diversified portfolios returns, compared with the average 70% given by the CAPM (within sample). They find positive returns from small size as well as value factors, high book-to-market ratio and related ratios. Examining β and size, they find that higher returns, small size, and higher β are all correlated. They then test returns for β, controlling for size, and find no relationship. Assuming stocks are first partitioned by size the predictive power of β then disappears. They discuss whether β can be saved and the Sharpe-Lintner-Black model resuscitated by mistakes in their analysis, and find it unlikely. Griffin shows that the Fama and French factors are country specific (Canada, Japan, the U.K., and the U.S.) and concludes that the local factors provide a better explanation of time-series variation in stock returns than the global factors. Therefore, updated risk factors are available for other stock markets in the world, including the (United Kingdom ), (Germany ) and (Switzerland ). Eugene Fama and Kenneth French also analysed models with local and global risk factors for four developed market regions (North America, Europe, Japan and Asia Pacific) and conclude that local factors work better than global developed factors for regional portfolios. The global and local risk factors may also be accessed on (Kenneth French's web page ). Finally, recent studies confirm the developed market results also for emerging markets. A number of studies have reported that when the Fama–French model is applied to emerging markets the book-to-market factor retains its explanatory ability but the market value of equity factor performs poorly. In a recent paper, Foye, Mramor and Pahor (2013) propose an alternative three factor model that replaces the market value of equity component with a term that acts as a proxy for accounting manipulation. ==See also== * Returns-based style analysis, a model that uses style indices rather than market factors * Carhart four-factor model (1997) — extension of the Fama–French model, containing an additional momentum factor (MOM), which is long prior-month winners and short prior-month losers *Size premium 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Fama–French three-factor model」の詳細全文を読む スポンサード リンク
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