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A portfolio-optimizer using Markowitz(1952) mean-variance model

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PortOpt [Portfolio Optimizer] is a C++ program (with Python binding) implementing the Markowitz(1952) mean-variance model with agent's linear indifference curves toward risk in order to find the optimal assets portfolio under risk.

You have to provide PortOpt (in text files or - if you use the api - using your own code) the variance/covariance matrix of the assets, their average returns and the agent risk preference.

It returns the vector of assets' shares that composes the optimal portfolio.

In order to minimise the variance it internally uses QuadProg++, a library that implement the algorithm of Goldfarb and Idnani for the solution of a (convex) Quadratic Programming problem by means of an active-set dual method. This solution is very efficient as it allows to solve hundred of thousand of portfolio problems in seconds.

PortOpt runs as a text/console tool so it can be easily used in your own scripts.

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Intended Audience

Financial and Insurance Industry, Science/Research, Developers, Management

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