Practical use about universal-portfolios HOT 4 CLOSED

Hey, this is solely a research project, it's not meant to run in "production". For that, you'll need to connect to a broker (like IB or something, there are tons of packages that can help you with that). OLMAR is such a simple algorithm that once you understand it, you can integrate it into your production code in like ~50 lines.

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Thanks for the quick reply. I already have a production algo and I have been researching strategies for a while now.
I recently came across online portfolio selection algorithms and your repo specifically. I would like to understand how your code works and how I can input it in my personnal backtester, and ultimatly run it live.

from universal-portfolios.

Understanding it is pretty easy, for instance OLMAR has just 70 lines. The step method returns portfolio weights for every time step from available inputs (last portfolio weights and historical prices). That's pretty easy to copy into any backtester.

from universal-portfolios.

Thank you for your answer.

Btw, I get the error, in OLMAR's update() :

RuntimeWarning: divide by zero encountered in double_scalars
  lam = max(0., (eps - np.dot(b, x)) / np.linalg.norm(x - x_mean)**2)

which is due to x = [1, 1, ..., 1] at the first step, therefore x-x_mean = 0 and np.linalg.norm(x - x_mean)**2 = 0, therefore the division by zero (at the first step only, the code works fine after that).

Would you know a workaround ?

Thanks !

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