问题
I'm looking for a finance library in python which offers a method similar to the MATLAB's portalloc . It is used to optimize a portfolio.
回答1:
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)."
回答2:
Maybe you could use this library (statlib) or this one (Mystic) to help you.
回答3:
If you know how to define your objective function. You can use Numpy to solve almost any portfolio optimization problem.
回答4:
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.)
来源：https://stackoverflow.com/questions/4119054/finance-lib-with-portfolio-optimization-method-in-python