In MatthiasSpeicher/gryffindorrobo: Run calculations that are useful to start a roboadvisor.
knitr::opts_chunk$set(echo = TRUE)
Risk Classification
The risk simulation is based on research on the benefit of repeated sampling in understanding risk conducted by the University of Mannheim. See http://simulator.behavioral-finance.de/#!/ for further information. The portfolio is constructed according to the risk assessment conducted in the beginning of the App, where each risk class corresponds to a yearly standard deviation as a proxy for risk.
Investment Universe
The portfolio has been constructed in accordance with the country and industry preferences specified. Geographically, your portfolio includes securities listed in the following countries: r input$mymap_groups.
if (is.null(input$industry1)) {
cat("In terms of industries, you did not specify any restrictions,
i.e. all industries are used in the portfolio construction.")
} else {
cat("The industries that have been chosen to exclude are: ")
cat(input$industry1, sep = ", ")
cat(".")
}
Your Performance
if (input$rpref2 == 1 && input$inv_horizon <= 5) {
portfoliofinal <<- indexpf(as.data.frame(shortbond))
portfolioplot <- cbind(ovr$Date,portfoliofinal)
names(portfolioplot) <- c("Date","Portfolio")
portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y")
portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d"))
portfolioplot <- cbind(portfolioplot, benchmark)
plotfinal <- ggplot()+
geom_line(data = portfolioplot, aes(
Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) +
geom_line(data = portfolioplot, aes(
Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) +
labs(x = "Year", y = "Portfoliodevelopement",
title = "Short Bond Portfolio") +
scale_x_date(date_breaks = "2 years")+
scale_colour_manual("", values = c("Your Portfolio"="blue",
"MSCI World Benchmark"="grey"))+
theme(legend.position=c(.9,.1))
theme_minimal()
}
##### long bond only ###########################################################
if ((input$rpref2 == 2 && input$inv_horizon <= 5) ||
(input$rpref2 == 1 && input$inv_horizon > 5 &&
input$inv_horizon <= 10)) {
portfoliofinal <<- indexpf(as.data.frame(longbond))
equityinvestment <<- 0
portfolioplot <- cbind(ovr$Date,portfoliofinal)
names(portfolioplot) <- c("Date","Portfolio")
portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y")
portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d"))
portfolioplot <- cbind(portfolioplot, benchmark)
plotfinal <- ggplot()+
geom_line(data = portfolioplot, aes(
Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) +
geom_line(data = portfolioplot, aes(
Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) +
labs(x = "Year", y = "Portfoliodevelopement",
title = "Long Bond Portfolio") +
scale_x_date(date_breaks = "2 years")+
scale_colour_manual("", values = c("Your Portfolio"="blue",
"MSCI World Benchmark"="grey")) +
theme(legend.position=c(.9,.1))
theme_minimal()
}
##### minimum variance PF ######################################################
if ((input$rpref2 == 3 && input$inv_horizon <= 5) ||
#redundant but included so that the number of conitions = number of PFs
(input$rpref2 == 3 && input$inv_horizon > 5 &&
input$inv_horizon <= 10) ||
(input$rpref2 == 2 && input$inv_horizon > 10)) {
####### split the required input df into sub-df's to make them optimizable #####
finaldata <- datasplit(newData())
portfoliofinal <<- minvarpf(finaldata)
equityinvestment <<- 0
####### include the performance plot in Shiny ##################################
portfolioplot <- cbind(ovr$Date,portfoliofinal)
names(portfolioplot) <- c("Date","Portfolio")
portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y")
portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d"))
portfolioplot <- cbind(portfolioplot, benchmark)
plotfinal <- ggplot()+
geom_line(data = portfolioplot, aes(
Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) +
geom_line(data = portfolioplot, aes(
Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) +
labs(x = "Year", y = "Portfoliodevelopement",
title = "Minimum Variance Portfolio") +
scale_x_date(date_breaks = "2 years")+
scale_colour_manual("", values = c("Your Portfolio"="blue",
"MSCI World Benchmark"="grey")) +
theme(legend.position=c(.9,.1))
theme_minimal()
}
###### Equity + longbond overweight bond #######################################
if (input$rpref2 == 1 && input$inv_horizon > 10) {
finaldata <- datasplit(newData())
finalpf <- optimpf(finaldata)
longbondindexed <- indexpf(as.data.frame(longbond))
portfoliofinal <<- equityanddeptpf(finalpf, longbondindexed, 0.2)
portfolioplot <- cbind(ovr$Date,portfoliofinal)
names(portfolioplot) <- c("Date","Portfolio")
portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y")
portfolioplot <- cbind(portfolioplot, benchmark)
plotfinal <- ggplot()+
geom_line(data = portfolioplot, aes(
Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) +
geom_line(data = portfolioplot, aes(
Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) +
labs(x = "Year", y = "Portfoliodevelopement",
title = "Sharpe Ratio optimized Equity Portfolio with 80% Longterm Debt") +
scale_x_date(date_breaks = "2 years")+
scale_colour_manual("", values = c("Your Portfolio"="blue",
"MSCI World Benchmark"="grey")) +
theme(legend.position=c(.9,.1))
theme_minimal()
equityinvestment <<- 0.2
}
############################ risk parity #######################################
if ((input$rpref2 == 4 && input$inv_horizon <= 5) ||
(input$rpref2 == 5 && input$inv_horizon <= 5) ||
(input$rpref2 == 4 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 5 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 3 && input$inv_horizon > 10) ||
(input$rpref2 == 4 && input$inv_horizon > 10)) {
finaldata <- datasplit(newData())
finalpf <- optimpf(finaldata)
longbonddf <- as.data.frame(longbond)
commoditydf <- as.data.frame(commodities)
portfoliofinal <<- riskparitypf(finalpf, longbonddf, commoditydf)
equityinvestment <<- as.numeric(portfoliofinal[2])
portfoliofinal <<- as.data.frame(portfoliofinal[1])
portfolioplot <- cbind(ovr$Date, portfoliofinal)
names(portfolioplot) <- c("Date","Portfolio")
portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y")
portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d"))
portfolioplot <- cbind(portfolioplot, benchmark)
plotfinal <- ggplot()+
geom_line(data = portfolioplot, aes(
Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) +
geom_line(data = portfolioplot, aes(
Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) +
labs(x = "Year", y = "Portfoliodevelopement",
title = "Risk Parity Portfolio with Sharpe Ratio optimized Equity Part") +
scale_x_date(date_breaks = "2 years")+
scale_colour_manual("", values = c("Your Portfolio"="blue",
"MSCI World Benchmark"="grey")) +
theme(legend.position=c(.9,.1))
theme_minimal()
}
########################### equity + longbond overweight equity ################
if ((input$rpref2 == 6 && input$inv_horizon <= 5) ||
(input$rpref2 == 6 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 5 && input$inv_horizon > 10)) {
finaldata <- datasplit(newData())
finalpf <- optimpf(finaldata)
longbondindexed <- indexpf(as.data.frame(longbond))
portfoliofinal <<- equityanddeptpf(finalpf, longbondindexed, 0.8)
equityinvestment <<- 0.8
portfolioplot <- cbind(ovr$Date,portfoliofinal)
names(portfolioplot) <- c("Date","Portfolio")
portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y")
portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d"))
portfolioplot <- cbind(portfolioplot, benchmark)
plotfinal <- ggplot()+
geom_line(data = portfolioplot, aes(
Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) +
geom_line(data = portfolioplot, aes(
Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) +
labs(x = "Year", y = "Portfoliodevelopement",
title = "Sharpe Ratio optimized Equity Portfolio with 20% Longterm Debt") +
scale_x_date(date_breaks = "2 years")+
scale_colour_manual("", values = c("Your Portfolio"="blue",
"MSCI World Benchmark"="grey")) +
theme(legend.position=c(.9,.1))
theme_minimal()
}
################################ Pure Equity? ##################################
if ((input$rpref2 == 6 && input$inv_horizon > 10) ||
(input$rpref2 == 7 && input$inv_horizon <= 5) ||
(input$rpref2 == 7 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 7 && input$inv_horizon > 10)) {
finaldata <- datasplit(newData())
portfoliofinal <<- optimpf(finaldata)
equityinvestment <<- 1
portfolioplot <- cbind(ovr$Date,portfoliofinal)
names(portfolioplot) <- c("Date","Portfolio")
portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y")
portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d"))
portfolioplot <- cbind(portfolioplot,benchmark)
plotfinal <- ggplot()+
geom_line(data = portfolioplot, aes(
Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) +
geom_line(data = portfolioplot, aes(
Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size = 1) +
labs(x = "Year", y = "Portfoliodevelopement",
title = "Sharpe Ratio optimized 100% Equity Portfolio") +
scale_x_date(date_breaks = "2 years")+
scale_colour_manual("", values = c("Your Portfolio"="blue",
"MSCI World Benchmark"="grey")) +
theme(legend.position=c(.9,.1))
theme_minimal()
}
plotfinal
if (input$rpref2 == 1 && input$inv_horizon <= 5) {
cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these
specifications we have identified a pure bond investment as the most
suitable for you.")
}
##### long bond only ###########################################################
if ((input$rpref2 == 2 && input$inv_horizon <= 5) ||
(input$rpref2 == 1 && input$inv_horizon > 5 &&
input$inv_horizon <= 10)) {
cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these
specifications we have identified a pure bond investment as the most
suitable for you.")
}
##### minimum variance PF ######################################################
if ((input$rpref2 == 3 && input$inv_horizon <= 5) ||
#redundant but included so that the number of conitions = number of PFs
(input$rpref2 == 3 && input$inv_horizon > 5 &&
input$inv_horizon <= 10) ||
(input$rpref2 == 2 && input$inv_horizon > 10)) {
####### split the required input df into sub-df's to make them optimizable #####
cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these
specifications we have identified a minimum variacne investment as the most
suitable for you.")
}
###### Equity + longbond overweight bond #######################################
if (input$rpref2 == 1 && input$inv_horizon > 10) {
cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these
specifications we have identified an equity and long bond investment as the most
suitable for you, where bond are overweighted.")
}
############################ risk parity #######################################
if ((input$rpref2 == 4 && input$inv_horizon <= 5) ||
(input$rpref2 == 5 && input$inv_horizon <= 5) ||
(input$rpref2 == 4 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 5 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 3 && input$inv_horizon > 10) ||
(input$rpref2 == 4 && input$inv_horizon > 10)) {
cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these
specifications we have identified a risk parity investment strategy as the most
suitable for you.")
}
########################### equity + longbond overweight equity ################
if ((input$rpref2 == 6 && input$inv_horizon <= 5) ||
(input$rpref2 == 6 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 5 && input$inv_horizon > 10)) {
cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these
specifications we have identified an equity and long bond investment as the most
suitable for you, where equity is overweighted.")
}
################################ Pure Equity? ##################################
if ((input$rpref2 == 6 && input$inv_horizon > 10) ||
(input$rpref2 == 7 && input$inv_horizon <= 5) ||
(input$rpref2 == 7 && input$inv_horizon > 5 && input$inv_horizon <= 10) ||
(input$rpref2 == 7 && input$inv_horizon > 10)) {
cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these
specifications we have identified a pure equity investment as the most
suitable for you.")
}
Performance Metrics. Historically, the portfolio that has been construceted
for you has had an average return of r paste0(round((averagereturn(portfoliofinal) * 100)), "%")
and a yearly standard derviation of r paste0(round((yearlystd(portfoliofinal) * 100)), "%").
This means that after r input$inv_horizon years, i.e. the investment horizon that you have
specified, you can expect a terminal wealth of r as.character(round(((1+(averagereturn(portfoliofinal)))^input$inv_horizon)*input$initial_wealth)).
Regarding downside risk, the portfolio has experienced a maximum drawdown of r paste0(round((maxdrawdown(portfoliofinal) * 100)), "%"), indicating the maximum
loss that has historically occured. Finally, the portfolio has a sharpe ratio of
r round((averagereturn(portfoliofinal)/yearlystd(portfoliofinal)), 2), which shows
the magnitude of the compensation for each unit of risk taken in terms of return
in excess of the risk free rate.
MatthiasSpeicher/gryffindorrobo documentation built on Dec. 27, 2019, 2:15 a.m.
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knitr::opts_chunk$set(echo = TRUE)
Risk Classification
The risk simulation is based on research on the benefit of repeated sampling in understanding risk conducted by the University of Mannheim. See http://simulator.behavioral-finance.de/#!/ for further information. The portfolio is constructed according to the risk assessment conducted in the beginning of the App, where each risk class corresponds to a yearly standard deviation as a proxy for risk.
Investment Universe
The portfolio has been constructed in accordance with the country and industry preferences specified. Geographically, your portfolio includes securities listed in the following countries: r input$mymap_groups.
if (is.null(input$industry1)) { cat("In terms of industries, you did not specify any restrictions, i.e. all industries are used in the portfolio construction.") } else { cat("The industries that have been chosen to exclude are: ") cat(input$industry1, sep = ", ") cat(".") }
Your Performance
if (input$rpref2 == 1 && input$inv_horizon <= 5) { portfoliofinal <<- indexpf(as.data.frame(shortbond)) portfolioplot <- cbind(ovr$Date,portfoliofinal) names(portfolioplot) <- c("Date","Portfolio") portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y") portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d")) portfolioplot <- cbind(portfolioplot, benchmark) plotfinal <- ggplot()+ geom_line(data = portfolioplot, aes( Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) + geom_line(data = portfolioplot, aes( Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) + labs(x = "Year", y = "Portfoliodevelopement", title = "Short Bond Portfolio") + scale_x_date(date_breaks = "2 years")+ scale_colour_manual("", values = c("Your Portfolio"="blue", "MSCI World Benchmark"="grey"))+ theme(legend.position=c(.9,.1)) theme_minimal() } ##### long bond only ########################################################### if ((input$rpref2 == 2 && input$inv_horizon <= 5) || (input$rpref2 == 1 && input$inv_horizon > 5 && input$inv_horizon <= 10)) { portfoliofinal <<- indexpf(as.data.frame(longbond)) equityinvestment <<- 0 portfolioplot <- cbind(ovr$Date,portfoliofinal) names(portfolioplot) <- c("Date","Portfolio") portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y") portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d")) portfolioplot <- cbind(portfolioplot, benchmark) plotfinal <- ggplot()+ geom_line(data = portfolioplot, aes( Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) + geom_line(data = portfolioplot, aes( Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) + labs(x = "Year", y = "Portfoliodevelopement", title = "Long Bond Portfolio") + scale_x_date(date_breaks = "2 years")+ scale_colour_manual("", values = c("Your Portfolio"="blue", "MSCI World Benchmark"="grey")) + theme(legend.position=c(.9,.1)) theme_minimal() } ##### minimum variance PF ###################################################### if ((input$rpref2 == 3 && input$inv_horizon <= 5) || #redundant but included so that the number of conitions = number of PFs (input$rpref2 == 3 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 2 && input$inv_horizon > 10)) { ####### split the required input df into sub-df's to make them optimizable ##### finaldata <- datasplit(newData()) portfoliofinal <<- minvarpf(finaldata) equityinvestment <<- 0 ####### include the performance plot in Shiny ################################## portfolioplot <- cbind(ovr$Date,portfoliofinal) names(portfolioplot) <- c("Date","Portfolio") portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y") portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d")) portfolioplot <- cbind(portfolioplot, benchmark) plotfinal <- ggplot()+ geom_line(data = portfolioplot, aes( Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) + geom_line(data = portfolioplot, aes( Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) + labs(x = "Year", y = "Portfoliodevelopement", title = "Minimum Variance Portfolio") + scale_x_date(date_breaks = "2 years")+ scale_colour_manual("", values = c("Your Portfolio"="blue", "MSCI World Benchmark"="grey")) + theme(legend.position=c(.9,.1)) theme_minimal() } ###### Equity + longbond overweight bond ####################################### if (input$rpref2 == 1 && input$inv_horizon > 10) { finaldata <- datasplit(newData()) finalpf <- optimpf(finaldata) longbondindexed <- indexpf(as.data.frame(longbond)) portfoliofinal <<- equityanddeptpf(finalpf, longbondindexed, 0.2) portfolioplot <- cbind(ovr$Date,portfoliofinal) names(portfolioplot) <- c("Date","Portfolio") portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y") portfolioplot <- cbind(portfolioplot, benchmark) plotfinal <- ggplot()+ geom_line(data = portfolioplot, aes( Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) + geom_line(data = portfolioplot, aes( Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) + labs(x = "Year", y = "Portfoliodevelopement", title = "Sharpe Ratio optimized Equity Portfolio with 80% Longterm Debt") + scale_x_date(date_breaks = "2 years")+ scale_colour_manual("", values = c("Your Portfolio"="blue", "MSCI World Benchmark"="grey")) + theme(legend.position=c(.9,.1)) theme_minimal() equityinvestment <<- 0.2 } ############################ risk parity ####################################### if ((input$rpref2 == 4 && input$inv_horizon <= 5) || (input$rpref2 == 5 && input$inv_horizon <= 5) || (input$rpref2 == 4 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 5 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 3 && input$inv_horizon > 10) || (input$rpref2 == 4 && input$inv_horizon > 10)) { finaldata <- datasplit(newData()) finalpf <- optimpf(finaldata) longbonddf <- as.data.frame(longbond) commoditydf <- as.data.frame(commodities) portfoliofinal <<- riskparitypf(finalpf, longbonddf, commoditydf) equityinvestment <<- as.numeric(portfoliofinal[2]) portfoliofinal <<- as.data.frame(portfoliofinal[1]) portfolioplot <- cbind(ovr$Date, portfoliofinal) names(portfolioplot) <- c("Date","Portfolio") portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y") portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d")) portfolioplot <- cbind(portfolioplot, benchmark) plotfinal <- ggplot()+ geom_line(data = portfolioplot, aes( Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) + geom_line(data = portfolioplot, aes( Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) + labs(x = "Year", y = "Portfoliodevelopement", title = "Risk Parity Portfolio with Sharpe Ratio optimized Equity Part") + scale_x_date(date_breaks = "2 years")+ scale_colour_manual("", values = c("Your Portfolio"="blue", "MSCI World Benchmark"="grey")) + theme(legend.position=c(.9,.1)) theme_minimal() } ########################### equity + longbond overweight equity ################ if ((input$rpref2 == 6 && input$inv_horizon <= 5) || (input$rpref2 == 6 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 5 && input$inv_horizon > 10)) { finaldata <- datasplit(newData()) finalpf <- optimpf(finaldata) longbondindexed <- indexpf(as.data.frame(longbond)) portfoliofinal <<- equityanddeptpf(finalpf, longbondindexed, 0.8) equityinvestment <<- 0.8 portfolioplot <- cbind(ovr$Date,portfoliofinal) names(portfolioplot) <- c("Date","Portfolio") portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y") portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d")) portfolioplot <- cbind(portfolioplot, benchmark) plotfinal <- ggplot()+ geom_line(data = portfolioplot, aes( Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) + geom_line(data = portfolioplot, aes( Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size =1) + labs(x = "Year", y = "Portfoliodevelopement", title = "Sharpe Ratio optimized Equity Portfolio with 20% Longterm Debt") + scale_x_date(date_breaks = "2 years")+ scale_colour_manual("", values = c("Your Portfolio"="blue", "MSCI World Benchmark"="grey")) + theme(legend.position=c(.9,.1)) theme_minimal() } ################################ Pure Equity? ################################## if ((input$rpref2 == 6 && input$inv_horizon > 10) || (input$rpref2 == 7 && input$inv_horizon <= 5) || (input$rpref2 == 7 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 7 && input$inv_horizon > 10)) { finaldata <- datasplit(newData()) portfoliofinal <<- optimpf(finaldata) equityinvestment <<- 1 portfolioplot <- cbind(ovr$Date,portfoliofinal) names(portfolioplot) <- c("Date","Portfolio") portfolioplot$Date <- strptime(as.character(portfolioplot$Date), "%d/%m/%Y") portfolioplot$Date <- as.Date(format(portfolioplot$Date, "%Y-%m-%d")) portfolioplot <- cbind(portfolioplot,benchmark) plotfinal <- ggplot()+ geom_line(data = portfolioplot, aes( Date, Portfolio, group = 1, colour = "Your Portfolio"), size = 1) + geom_line(data = portfolioplot, aes( Date, benchmark, group = 1, colour = "MSCI World Benchmark"), size = 1) + labs(x = "Year", y = "Portfoliodevelopement", title = "Sharpe Ratio optimized 100% Equity Portfolio") + scale_x_date(date_breaks = "2 years")+ scale_colour_manual("", values = c("Your Portfolio"="blue", "MSCI World Benchmark"="grey")) + theme(legend.position=c(.9,.1)) theme_minimal() } plotfinal
if (input$rpref2 == 1 && input$inv_horizon <= 5) { cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these specifications we have identified a pure bond investment as the most suitable for you.") } ##### long bond only ########################################################### if ((input$rpref2 == 2 && input$inv_horizon <= 5) || (input$rpref2 == 1 && input$inv_horizon > 5 && input$inv_horizon <= 10)) { cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these specifications we have identified a pure bond investment as the most suitable for you.") } ##### minimum variance PF ###################################################### if ((input$rpref2 == 3 && input$inv_horizon <= 5) || #redundant but included so that the number of conitions = number of PFs (input$rpref2 == 3 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 2 && input$inv_horizon > 10)) { ####### split the required input df into sub-df's to make them optimizable ##### cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these specifications we have identified a minimum variacne investment as the most suitable for you.") } ###### Equity + longbond overweight bond ####################################### if (input$rpref2 == 1 && input$inv_horizon > 10) { cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these specifications we have identified an equity and long bond investment as the most suitable for you, where bond are overweighted.") } ############################ risk parity ####################################### if ((input$rpref2 == 4 && input$inv_horizon <= 5) || (input$rpref2 == 5 && input$inv_horizon <= 5) || (input$rpref2 == 4 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 5 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 3 && input$inv_horizon > 10) || (input$rpref2 == 4 && input$inv_horizon > 10)) { cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these specifications we have identified a risk parity investment strategy as the most suitable for you.") } ########################### equity + longbond overweight equity ################ if ((input$rpref2 == 6 && input$inv_horizon <= 5) || (input$rpref2 == 6 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 5 && input$inv_horizon > 10)) { cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these specifications we have identified an equity and long bond investment as the most suitable for you, where equity is overweighted.") } ################################ Pure Equity? ################################## if ((input$rpref2 == 6 && input$inv_horizon > 10) || (input$rpref2 == 7 && input$inv_horizon <= 5) || (input$rpref2 == 7 && input$inv_horizon > 5 && input$inv_horizon <= 10) || (input$rpref2 == 7 && input$inv_horizon > 10)) { cat("You have chosen a risk preference of level", input$rpref2, ", and an investment horizon of", input$inv_horizon, "years. According to these specifications we have identified a pure equity investment as the most suitable for you.") }
Performance Metrics. Historically, the portfolio that has been construceted
for you has had an average return of r paste0(round((averagereturn(portfoliofinal) * 100)), "%")
and a yearly standard derviation of r paste0(round((yearlystd(portfoliofinal) * 100)), "%").
This means that after r input$inv_horizon years, i.e. the investment horizon that you have
specified, you can expect a terminal wealth of r as.character(round(((1+(averagereturn(portfoliofinal)))^input$inv_horizon)*input$initial_wealth)).
Regarding downside risk, the portfolio has experienced a maximum drawdown of r paste0(round((maxdrawdown(portfoliofinal) * 100)), "%"), indicating the maximum
loss that has historically occured. Finally, the portfolio has a sharpe ratio of
r round((averagereturn(portfoliofinal)/yearlystd(portfoliofinal)), 2), which shows
the magnitude of the compensation for each unit of risk taken in terms of return
in excess of the risk free rate.
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