parmautility-methods {parma} | R Documentation |
Utility Based Optimization
Description
Utility based portfolio optimization using either Taylor series expansion of utility function with moments or scenario based.
Usage
parmautility(U = c("CARA", "Power"), method = c("moment", "scenario"),
scenario = NULL, M1 = NULL, M2 = NULL, M3 = NULL, M4 = NULL, RA = 1,
budget = 1, LB = rep(0, length(M1)), UB = rep(1, length(M1)))
Arguments
U |
The utility function (only CARA curretly implemented). |
method |
Whether to use moment or scenario based optimization (only moment currently implemented). |
scenario |
A n-by-m scenario matrix. |
M1 |
A vector (m) of forecasts. |
M2 |
An m-by-m positive definite covariance matrix. |
M3 |
An m-by-m^2 third co-moment matrix. |
M4 |
An m-by-m^3 fourth co-moment matrix. |
RA |
Risk Aversion Coefficient for CARA. |
budget |
The investment constraint. |
LB |
The lower bounds for the asset weights (positive). |
UB |
The upper bounds for the asset weights. |
Details
The function currently only implements the CARA moment based approach, but will be expanded in the future. The moment approach can take as inputs either M1 and M2 (2-moment approximation), or M1, M2, M3 and M4 (4-moment approximation). Not many models generate M3 and M4, but the “gogarch” model with manig or magh distribution will.
Value
A parmaPort
object containing details of the PARMA
optimized portfolio.
Author(s)
Alexios Galanos
References
Galanos, A. and Rossi, E. and Urga, G. 2012, Independent Factor Autoregressive
Conditional Density Model submitted-TBA