group_constraint: constructor for group_constraint

Description

Group constraints specify the grouping of the assets, weights of the groups, and number of postions (i.e. non-zero weights) iof the groups. This function is called by add.constraint when type="group" is specified. see add.constraint

Usage

group_constraint(
  type = "group",
  assets,
  groups,
  group_labels = NULL,
  group_min,
  group_max,
  group_pos = NULL,
  enabled = TRUE,
  message = FALSE,
  ...
)

Value

an object of class 'group_constraint'

Arguments

type: character type of the constraint
assets: number of assets, or optionally a named vector of assets specifying initial weights
groups: list of vectors specifying the groups of the assets
group_labels: character vector to label the groups (e.g. size, asset class, style, etc.)
group_min: numeric or vector specifying minimum weight group constraints
group_max: numeric or vector specifying minimum weight group constraints
group_pos: vector specifying the number of non-zero weights per group
enabled: TRUE/FALSE
message: TRUE/FALSE. The default is message=FALSE. Display messages if TRUE.
...: any other passthru parameters to specify group constraints

Author

Ross Bennett

Examples

Run this code

data(edhec)
ret <- edhec[, 1:4]

pspec <- portfolio.spec(assets=colnames(ret))

# Assets 1 and 3 are groupA
# Assets 2 and 4 are groupB
pspec <- add.constraint(portfolio=pspec, 
                        type="group", 
                        groups=list(groupA=c(1, 3),
                                    groupB=c(2, 4)),
                        group_min=c(0.15, 0.25),
                        group_max=c(0.65, 0.55))

# 2 levels of grouping (e.g. by sector and geography)
pspec <- portfolio.spec(assets=5)
# Assets 1, 3, and 5 are Tech
# Assets 2 and 4 are Oil
# Assets 2, 4, and 5 are UK
# Assets 1 and are are US
group_list <- list(group1=c(1, 3, 5),
                   group2=c(2, 4),
                   groupA=c(2, 4, 5),
                   groupB=c(1, 3))

pspec <- add.constraint(portfolio=pspec, 
                        type="group", 
                        groups=group_list,
                        group_min=c(0.15, 0.25, 0.2, 0.1),
                        group_max=c(0.65, 0.55, 0.5, 0.4))