plotPerformanceVsParams: Plot performance of portfolio function vs choice of...

In portfolioBacktest: Automated Backtesting of Portfolios over Multiple Datasets

Plot performance of portfolio function vs choice of parameters

Description

Portfolio functions usually contain some parameters that can be tuned. After generating multiple versions of a portfolio function with randomly chosen parameters with the function genRandomFuns and doing the backtesting, this function can be used to plot the performance vs choice of parameters.

Usage

plotPerformanceVsParams(
  bt_all_portfolios,
  params_subset = NULL,
  name_performance = "Sharpe ratio",
  summary_fun = median
)

Arguments

bt_all_portfolios	Backtest results as produced by the function portfolioBacktest.
params_subset	List of named parameters with a subset of the values to be considered. By default all the possible values will be considered.
name_performance	String with the name of the performance measure to be used.
summary_fun	Summary function to be employed (e.g., median or mean). Defult is median.

Author(s)

Daniel P. Palomar and Rui Zhou

See Also

genRandomFuns

Examples

library(portfolioBacktest)

# define GMVP with parameters "delay", "lookback", and "regularize"
GMVP_portfolio_fun <- function(dataset, ...) {
  prices <- tail(lag(dataset$adjusted, delay), lookback)
  X <- diff(log(prices))[-1]
  Sigma <- cov(X)
  if (regularize)
    Sigma <- Sigma + 0.01*diag(ncol(Sigma))
  # design GMVP
  w <- solve(Sigma, rep(1, ncol(Sigma)))
  return(w/sum(w))
}

# generate the functions with random parameters
portfolio_list <- genRandomFuns(portfolio_fun = GMVP_portfolio_fun, 
                                params_grid = list(lookback = c(100, 120, 140, 160),
                                                   delay = c(0, 5, 10, 15, 20),
                                                   regularize = c(FALSE, TRUE)),
                                name = "GMVP", 
                                N_funs = 40)
                                
# backtest portfolios
bt <- portfolioBacktest(portfolio_list, dataset10)

# plot
plotPerformanceVsParams(bt)
plotPerformanceVsParams(bt, params_subset = list(regularize = TRUE))
plotPerformanceVsParams(bt, params_subset = list(delay = 5))
plotPerformanceVsParams(bt, params_subset = list(delay = 5, regularize = TRUE))

portfolioBacktest documentation built on April 22, 2022, 9:05 a.m.