parma

The portfolio allocation and risk managament applications (parma) package contains a unique set of methods and models for the optimal allocation of capital in financial portfolios. It uniquely represents certain discontinuous problems using their smooth
approximation counterparts and implements fractional based programming for the direct
optimization of risk-to-reward ratios. In combination with the rmgarch package, it enables the confident solution to scenario based optimization problems using such risk and deviation measures as Mean Absolute Deviation (MAD), Variance (EV), Minimax, Conditional Value at Risk (CVaR), Conditional Drawdown at Risk (CDaR) and Lower Partial Moments (LPM). In addition, it implements moment based optimization for use with the quadratic EV problem, and a higher moment CARA utility expansion using the
coskewness and cokurtosis matrices generated from the GO-GARCH with affine GH or NIG distributions. Benchmark relative optimization (tracking error) is also implemented as are basic mixed integer cardinality constraints. Finally, for non-convex problem formulations such as the upper to lower partial moments function, global optimization methods using a penalty based method are available.

The package is available to download from CRAN.  Since June 2013 the package has been under joint development with Bernhard Pfaff and hosted on r-forge.