BacktestPORTFOLIOS: <BacktestPORTFOLIOS>

In rickycant90/BMLgarch: Econometric and Mathematic tools for market analysis and portfolio optimization.

Description

<Rolling window backtesting of optimized portfolios>

Usage

BacktestPORTFOLIOS(scenario.set, cor.matrices = list(), box = TRUE,
  active = FALSE, full = TRUE, poslim = TRUE, diversification = FALSE,
  turnover = FALSE, target.return = FALSE, div = 0.8, turn = 0.2,
  p = 0.05, ret.target = 0.05, shortsell = FALSE, max.weight = 1,
  maxrisk = 0.3, maxpos = 4, minbox = -0.2, maxbox = 0.2)

Arguments

scenario.set	A data.frame object containing all the assets in the market.
cor.matrices	A list of conditional correlation matrices.
box	logical, indicating whether to add or not a box constraint, minbox and maxbox are the quantities associated to that constraint.
active	logical, indicating whether to compose a dollar-neutral (0-sum) portfolio or not.
full	logical, indicating whether to add or not a full-investment constraint.
poslim	logical, indicating whether to add or not a position limit constraint, maxpos is the quantity associated to that constraint.
diversification	logical, indicating whether to add or not a diversification constraint, div is the percentage quantity associated to that constraint.
turnover	logical, indicating whether to add or not a turnover constraint, turn is the quantity associated to that constraint.
target.return	logical, indicating whether to add or not a target return constraint, ret.target is the quantity associated to that constraint.
shortsell	Logic, if TRUE negative proportions are allowed in the optimized portfolios.
max.weight	real number, total capital to invest
nroll	Integer, width of the rolling window.
q	real number, quantile for VaRc estimates.

rickycant90/BMLgarch documentation built on May 23, 2019, 10:36 p.m.