Rで学ぶ中級ポートフォリオ分析
Ross Bennett
Instructor
optimize.portfolio() による単期間の最適化
optimize.portfolio.rebalancing() による定期リバランス(バックテスト)最適化
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",
...)
サポートされる最適化手法:
グローバルソルバー:
DEoptim: 差分進化法
random: ランダム・ポートフォリオ最適化
GenSA: 一般化焼きなまし法
pso: 粒子群最適化
LP/QP ソルバー:
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)
Rで学ぶ中級ポートフォリオ分析