Intermediate Portfolio Analysis in R
Ross Bennett
Instructor
Single period optimization with optimize.portfolio()
Optimization with periodic rebalancing (backtesting) with optimize.portfolio.rebalancing()
optimize.portfolio(R, portfolio = NULL,
optimize_method = c("DEoptim", "random", "ROI", ...),
search_size = 20000, trace = TRUE,
momentFUN = "set.portfolio.moments",
...)
optimize.portfolio.rebalancing(R, portfolio = NULL,
optimize_method = c("DEoptim", "random", "ROI", ...),
search_size = 20000, trace = TRUE,
rebalance_on = "quarters",
training_period,
rolling_window,
momentFUN = "set.portfolio.moments",
...)
The following optimization methods are supported:
Global Solvers:
DEoptim: Differential Evolution Optimization
random: Random Portfolios Optimization
GenSA: Generalized Simulated AnnealingAnalyze optimization results
pso: Particle Swarm Optimization
LP and QP Solvers:
data(edhec) ret <- edhec[,1:6]
# Portfolio p <- portfolio.spec(assets = colnames(ret)) p <- add.constraint(portfolio = p, type = "full_investment") p <- add.constraint(portfolio = p, type = "long_only") p <- add.objective(portfolio = p, type = "risk", name = "StdDev")
# Optimizations opt_single <- optimize.portfolio(R = ret, portfolio = p, optimize_method = "ROI")
opt_rebal <- optimize.portfolio.rebalancing(R = ret, portfolio = p, optimize_method = "ROI", rebalance_on = "years", training_period = 60, rolling_window = 60)
Intermediate Portfolio Analysis in R