Portfolio Management Tool

Proprietary MATLAB library that contains a collection of landmark implementations regarding portfolio optimization, enabling portfolio managers to hit the ground running with the latest techniques in quantitative finance.

1. F-Line Optimization:
   This is a famous portfolio optimization algorithm that overcomes some limitations of Markowitz’s Mean-Variance Optimization approach. The most important trait of this method is that it provides the investor with an option to place lower and upper bounds on the weights of the assets.
2. Mean-Variance Optimization:
   A collection of classic Mean-Variance portfolios – Inverse Variance, Minimum Volatility, Quadratic Utility, Maximum Sharpe, Efficient Risk etc. It also provides users with ability to create custom portfolios with custom objectives and constraints.
3. Clustered Optimization:
   The algorithm estimates optimal weight allocation to either maximize the Sharpe ratio or minimize the variance of a portfolio. As evident by the name, it clusters the covariance matrix of asset returns to a reduced, denoised form and produce efficient weight allocations.