I've often seen 2-3 different ways factor models are constructed, but I don't understand when do you use one approach, the benefits. I do have some intuition but really looking for some industry context here Long-Short portfolio based on some ranking : Eg. Take P/B ratio sort all stocks and then create a ranking, go long the top quantile and short the bottom. You've a value factor portfolio. Do similar approach with other definitions of factors. One clear drawback factor portfolio's likely explain the same variance. Commercial Vendor (Barra) style factor models - which are used for risk attribution, take values some fundamental data, calibrate factor returns jointly so you don't double count the variance. But I think this is better to look-back and explain what happened, rather than use it for 'predicting' what can happen in the future. Fama MacBeth - I think this is more theory ? Want to understand if a factor actually pays the risk premia - run cross-sectional regression to test that hypothesis. People who manage actively use factors in their portfolio - how do they think about using factor models, while building their portfolio ?