Finance Lib with portfolio optimization method in python

一曲冷凌霜 提交于 2019-11-30 07:32:11
Binary Phile

If you know linear algebra, there is a simple function for solving the optimization problem which any library should support. Unfortunately, it's been so long since I researched it I can't tell you the formula nor a library that supports it, but a little research should reveal it. The main point is that any linear algebra library should do.

Update:

Here's a quote from a post I found.

Some research says that "mean variance portfolio optimization" can give good results. I discussed this in a message

To implement this approach, a needed input is the covariance matrix of returns, which requires historical stock prices, which one can obtain using "Python quote grabber" http://www.openvest.org/Databases/ovpyq .

For expected returns -- hmmm. One of the papers I cited found that assuming equal expected returns of all stocks can give reasonable results.

Then one needs a "quadratic programming" solver, which appears to be handled by the CVXOPT Python package.

If someone implements the approach in Python, I'd be happy to hear about it.

There is a "backtest" package in R (open source stats package callable from Python) http://cran.r-project.org/web/packages/backtest/index.html "for exploring portfolio-based hypotheses about financial instruments (stocks, bonds, swaps, options, et cetera)."

Maybe you could use this library (statlib) or this one (Mystic) to help you.

If you know how to define your objective function. You can use Numpy to solve almost any portfolio optimization problem.

Python implementations of some typical portfolio optimizations can be found at https://github.com/czielinski/portfolioopt. The corresponding quadratic programs are being solved using the CVXOPT library. (Disclaimer: this is my own GitHub repository.)

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