optim_portfolio: Optimal portfolio.
In veldanie/SuraInvestmentAnalytics: Investment Analytics

optim_portfolio

R Documentation

Optimal portfolio.

Description

Optimal Portfolio.

Usage

optim_portfolio(w_ini, fn, lb, ub, eqfun, eqB, w_bench = NULL,
  lb_act = NULL, ub_act = NULL, ineqfun = NULL, ineqLB = NULL,
  ineqUB = NULL, method = "RI", fixed = NULL, n.restarts = 10,
  n.sim = 20000, type = "absolute", itermax = 1000, NP = 100,
  max.time = 180)

Arguments

`w_ini`	Initial weights.
`fn`	Objective function or list of objective function. By default it corresponds to the mean-var utility.
`lb`	Lower bound.
`ub`	Upper bound.
`eqfun`	Equality constraint function returning vector.
`eqB`	Equality constraints.
`w_bench`	Benchmark weigths.
`lb_act`	Lower bound active weight per asset
`ub_act`	Upper bound active weight per asset
`ineqfun`	Inequality constraint function returning vector.
`ineqLB`	Inequality lower bound.
`ineqUB`	Inequality upper bound.
`method`	Gradient descent (GD), GD with random initialization (RI), differential evolution (DE), Genetic Opt. using Derivative (GE), Generalized Simulated Annealing (SA) or Memetic with local search (MALS).
`fixed`	Numeric index indicating parameters that stay fixed.
`n.sim`	Random parameters for every restart of the solver.
`type`	Type of objective function. absolute or relative.
`itermax`	Maximum iteration (population generation) allowed.
`NP`	Number of population members.
`max.time`	Max time in seconds. Applied to SA.
`n.restars`	Number of solver restarts.