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Implementing Fama-Macbeth 1973 & Fama-French 1992 Portfolios construction & Regressions


  1. I'm new to Quantopian API but already went through the tutorials & lecture series.
  2. I'm looking for references & suggestions how to implement Fama-Macbeth 1973 & Fama-French 1992, more specifically how to implement with Quantopian API the size and beta size portfolios etc. we all familiar with from the papers.
  3. Note - I'm intersting in FF1992 not the more popular 3 factor FF1993...


6 responses

Hello Michael,

You'll most likely find this lecture useful, it implements the original Fama-French factors in the pipeline API.


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Hi thanks I've already saw this. I'm more specifically interested on whats called Fama-Macbeth method with the construction of 100 portfolios etc. and just trying to figure out what is the best way to implement this procedure because it's little bit tricky. (Actually we are doing this as part of academic research and we found out it will be more easy to code with Quantopian rather than with the Financial Matlab toolbox).
By the way - Besides the above lecture, is there any other related resource I missed? Maybe from some event or something?
Thanks a lot!

I'm not aware of any resources that currently implement that precisely. I actually coordinate academic outreach at Quantopian so I'd be interested to know where you're doing the research if you don't mind me asking. It helps me keep track of who's working on what and what resources may be helpful. For instance if we produce a new lecture and it's related to what someone is working on, we'll do our best to notify them. If you send me an email at [email protected] that would be easiest.

Also, an implementation of Fama-Macbeth regression sounds like it might be a great addition to the lecture series. If you come up with an implementation of it please let us know. If the implementation is nicely written and we have the time, we'd be happy to add it to the lectures with full credit going to whoever wrote it.

Hi thanks - sent you email...

I'm also interested on this topic.

The notebook ( was useful but unclear on the portfolio construction part like where you get your sensitivities from, etc.

I learned more from this video:

From what I gather, we solve the linear regression with individual stock return against the FAMA French parameters to get the betas. Then solve the weights for the expected desired portfolio ( eg. small portfolio, high value).

Still trying to build it myself but there's so few reference material on this..

Michael - btw I came across fama-macbeth on Pandas. Not much doc around it.