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PortOpt
A portfolio-optimizer using Markowitz(1952) mean-variance model
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. ... -
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Implementation of algorithm from paper 'Numerical Approximation of Option Premia in Displaced-Lognormal Heston Models' by A Dickinson. For code: click link under 'Develop' & checkout via svn or click link under Browse Code->SVN & download tarball
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