Gevorderde portefeuilleanalyse in R
Ross Bennett
Instructor
Bouw voort op basisconcepten uit "Introduction to Portfolio Analysis in R"
Verken geavanceerde concepten in het portefeuille-optimalisatieproces
Gebruik het R-pakket PortfolioAnalytics om optimalisatieproblemen op te lossen die echte situaties nabootsen
De Moderne Portefeuilletheorie (MPT) werd in 1952 geïntroduceerd door Harry Markowitz.
MPT stelt dat een belegger het verwachte portefeuillerendement maximaliseert voor een gegeven risico.
Veelvoorkomende doelen:
Maximaliseer winst per eenheid risico
Minimaliseer risico
library(PortfolioAnalytics)
data(edhec)
data <- edhec[,1:8]
# Create the portfolio specification
port_spec <- portfolio.spec(colnames(data))
port_spec <- add.constraint(portfolio = port_spec, type = "full_investment")
port_spec <- add.constraint(portfolio = port_spec, type = "long_only")
port_spec <- add.objective(portfolio = port_spec, type = "return", name = "mean")
port_spec <- add.objective(portfolio = port_spec, type = "risk", name = "StdDev")
**************************************************
PortfolioAnalytics Portfolio Specification
**************************************************
Call:
portfolio.spec(assets = colnames(data))
Number of assets: 8
Asset Names
[1] "Convertible Arbitrage" "CTA Global" "Distressed Securities"
[4] "Emerging Markets" "Equity Market Neutral" "Event Driven"
[7] "Fixed Income Arbitrage" "Global Macro"
Constraints
Enabled constraint types
- full_investment
- long_only
Objectives:
Enabled objective names
- mean
- StdDev
# Run optimization and chart results in risk-reward space
opt <- optimize.portfolio(data,
portfolio = port_spec,
optimize_method = "random",
trace = TRUE)
chart.RiskReward(opt,
risk.col = "StdDev",
return.col = "mean",
chart.assets = TRUE)

Gevorderde portefeuilleanalyse in R