hello I need help with this finance assignment that is coding in R programming languageProject 2 –...

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hello I need help with this finance assignment that is coding in R programming languageProject 2 – Portfolio Returns Step 1: Take the programs from Regenstein Chapters 2 and 3, and create your own portfolio.  Graph asset and portfolio returns.  Apply the shiny app.  Try modifying the start and end dates of your data and repeat the process. Step 2: Calculate and graph the rolling standard deviation of your portfolio.  Repeat using different rolling windows and start/end dates.  Apply the shiny app. Step 3:  Use the rolling skewness and kurtosis shiny app to analyze your portfolio.  Does your portfolio follow a normal distribution? Step 4: Write a short summary of your analysis in Microsoft Word, and incorporate graphs using the snipping tool. 2   Returns in XTS Returns in XTS and Tidyverse The Process Call libraries Quantmod – retrieves data from various sources Purrr – used for iteration PerformanceAnalytics – performs statistics, used frequently with xts Highcharter – a “wrapper” package for the Highcharts Javascript library Select securities (ETFs in our examples) SPY:  State Street S&P 500 Index ETF EFA:  iShares Non-U.S. Equity Index ETF IJS:  iShares S&P Small-Cap 600 Index ETF EEM:  iShares MSCI Emerging Markets Index ETF AGG:  iShares BBG Barclays U.S. Aggregate Index Bond ETF Retrieving Data from Yahoo! Finance Load daily price data from Yahoo! Finance into xts object “price”  getSymbols – from package quantmod, retrieves data from various sources  symbols – vector of stock symbols  src – from Yahoo! Finance (other data sources are available – see documentation)  from =, to =  - select dates  auto.assign = TRUE – assigns an R-legal name from the ticker symbol  map(~Ad(get(.))) – from package purrr, applies a function to each element of a vector (an elegant for loop).   Keeping only the adjusted prices for each ticker (vector).  reduce(merge) – merges the five price vectors into a single xts object  `colnames

Sanchi · Accepted Answer

AS21/.RDataAS21/.RData
AS21/.Rhistorylibrary(quantmod)
#
# Package quantmod helps us to retrieve data from various sources, in this case, Yahoo! Finance.
# Also note that it calls the package xts.
#
library(purrr)
#
# As a side note, package purrr is part of the tidyverse. We use it here for convenience.
#
#
# The following packages are used in the xts universe.
# Package PerformanceAnalytics performs several useful calculations.
# Package highcharter is actually a "wrapper" function for the Javascript 'Highcharts' library,
# including shortcut functions to plot R objects. 'Highcharts'
# offers numerous chart types with a simple configuration syntax.
#
library(PerformanceAnalytics)
#
# As a side note, package purrr is part of the tidyverse. We use it here for convenience.
#
#
# The following packages are used in the xts universe.
# Package PerformanceAnalytics performs several useful calculations.
# Package highcharter is actually a "wrapper" function for the Javascript 'Highcharts' library,
# including shortcut functions to plot R objects. 'Highcharts'
# offers numerous chart types with a simple configuration syntax.
install.packages("PerformanceAnalytics")
library(PerformanceAnalytics)
library(highcharter)
install.packages("highcharter")
library(highcharter)
#
# Select stocks (ETFs)
# SPY: State Street S&P 500 Index ETF
# EFA: iShares Non-U.S. Equity Index ETF
# IJS: iShares S&P Small-Cap 600 Value ETF
# EEM: iShares MSCI Emerging Markets Index ETF
# AGG: iShares BBG Barclays U.S. Aggregate Index Bond ETF
#
symbols <- c("SPY", "EFA", "IJS", "EEM", "AGG")
# We use the map function from package purrr to apply Ad(get(.)) to the imported prices.
# The map function is an elegant, easily understandable way to do looping (e.g., for loop).
# The call to Ad(get(.)) gets the split and dividend adjusted prices for each security.
# The result is the daily price series' for each security.
# Since we would like the data in a single xts object, we will use the reduce(merge) command.
# The reduce(merge) combines the 5 lists into a single xts object.
# We also add the variable names, which correspond to the names of the individual securities.
# Also note that we are piping (%>%) commands together. You can think of %<% as, "and now then
# we do this....
#
prices <-
getSymbols(symbols,
src = 'yahoo',
from = "2012-12-31",
to = "2017-12-31",
auto.assign = TRUE,
warnings = FALSE) %>%
map(~Ad(get(.))) %>%
reduce(merge) %>%
`colnames<-` (symbols)
View(AGG)
View(prices)
prices_monthly <- to.monthly(prices,
indexAt = "lastof",
OHLC = FALSE)
View(prices_monthly)
View(prices_monthly)
#
# Head is a convenient function to print out the first few lines of a file. It's in base R,
# but an improved version is contained in the tidyverse function dplyr.
#
head(prices_monthly)
asset_returns_xts <-
Return.calculate(prices_monthly,
method = "log") %>%
na.omit()
head(asset_returns_xts)
highchart(type = "stock") %>%
hc_title(text = "Monthly Log Returns") %>%
hc_add_series(asset_returns_xts[, symbols[1]],
name = symbols[1]) %>%
hc_add_series(asset_returns_xts[, symbols[2]],
name = symbols[2]) %>%
hc_add_series(asset_returns_xts[, symbols[3]],
name = symbols[3]) %>%
hc_add_series(asset_returns_xts[, symbols[4]],
name = symbols[4]) %>%
hc_add_series(asset_returns_xts[, symbols[5]],
name = symbols[5]) %>%
hc_add_theme(hc_theme_flat()) %>%
hc_navigator(enabled = FALSE) %>%
hc_scrollbar(enabled = FALSE) %>%
hc_exporting(enabled = TRUE) %>%
hc_legend(enabled = TRUE)
hc_hist_fun <- function(n = 1, object, color) {
hc_hist <- hist(object[, symbols[n]],
breaks = 50,
plot = FALSE)
hchart(hc_hist, color = color) %>%
hc_title(text =
paste(symbols[n],
"Log Returns Distribution",
sep = " ")) %>%
hc_add_theme(hc_theme_flat()) %>%
hc_exporting(enabled = TRUE) %>%
hc_legend(enabled = FALSE)
}
hc_hist_fun(1, asset_returns_xts, "cornflowerblue")
hc_hist_fun(2, asset_returns_xts, "green")
hc_hist_fun(3, asset_returns_xts, "pink")
hc_hist_fun(4, asset_returns_xts, "purple")
hc_hist_fun(5, asset_returns_xts, "yellow")
# Weights
w <- c(0.25, 0.25, 0.20, 0.20, 0.10)
portfolio_returns_xts_rebalanced_monthly <-
Return.portfolio(asset_returns_xts,
weights = w,
rebalance_on = "months") %>%
`colnames<-`("returns")
head(portfolio_returns_xts_rebalanced_monthly)
highchart(type = "stock") %>%
hc_title(text = "Portfolio Monthly Returns") %>%
hc_add_series(portfolio_returns_xts_rebalanced_monthly$returns,
name = "Rebalanced Monthly",
color = "cornflowerblue") %>%
hc_add_theme(hc_theme_flat()) %>%
hc_navigator(enabled = FALSE) %>%
hc_scrollbar(enabled = FALSE) %>%
hc_legend(enabled = TRUE) %>%
hc_exporting(enabled = TRUE)
hc_portfolio <-
hist(portfolio_returns_xts_rebalanced_monthly$returns,
breaks = 50,
plot = FALSE)
hchart(hc_portfolio,
color = "cornflowerblue",
name = "Portfolio") %>%
hc_title(text = "Monthly Returns Distribution") %>%
hc_add_theme(hc_theme_flat()) %>%
hc_exporting(enabled = TRUE)
---
title: "Returns Distribution"
runtime: shiny
output:
flexdashboard::flex_dashboard:
orientation: rows
source_code: embed
---
library(tidyverse)
library('tidyverse')
library(highcharter)
library('tidyverse')
library(highcharter)
library(tidyquant)
install.packages("tidyquant")
install.packages("tidyquant")
library(tidyquant)
library(timetk)
fluidRow(
column(6,
textInput("stock1", "Stock 1", "SPY")),
column(5,
numericInput("w1", "Portf. %", 25, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock2", "Stock 2", "EFA")),
column(5,
numericInput("w2", "Portf. %", 25, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock3", "Stock 3", "IJS")),
column(5,
numericInput("w3", "Portf. %", 20, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock4", "Stock 4", "EEM")),
column(5,
numericInput("w4", "Portf. %", 20, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock5", "Stock 5", "AGG")),
column(5,
numericInput("w5", "Portf. %", 10, min = 1, max = 100))
)
fluidRow(
column(7,
dateInput("date", "Starting Date", "2013-01-01", format = "yyyy-mm-dd"))
)
fluidRow(
column(7,
selectInput("rebalance", "rebalance freq",
c("Yearly" = "years",
"Monthly" = "months",
"Weekly" = "weeks"))
)
)
actionButton("go", "Submit")
portfolio_returns_byhand <- eventReactive(input$go, {
symbols <- c(input$stock1, input$stock2, input$stock3, input$stock4, input$stock5)
prices <- getSymbols(symbols, src = 'yahoo', from = input$date,
auto.assign = TRUE, warnings = FALSE) %>%
map(~Ad(get(.))) %>%
reduce(merge) %>%
`colnames<-`(symbols)
w <- c(input$w1/100, input$w2/100,
input$w3/100, input$w4/100, input$w5/100)
asset_returns_long <-
prices %>%
to.monthly(indexAt = "last", OHLC = FALSE) %>%
tk_tbl(preserve_index = TRUE, rename_index = "date") %>%
gather(asset, returns, -date) %>%
group_by(asset) %>%
mutate(returns = (log(returns) - log(lag(returns))))
portfolio_returns_byhand <-
asset_returns_long %>%
tq_portfolio(assets_col = asset,
returns_col = returns,
weights = w,
col_rename = "returns")
})
library('tidyverse')
library(highcharter)
install.packages("tidyquant")
library(tidyquant)
library(timetk)
fluidRow(
column(6,
textInput("stock1", "Stock 1", "SPY")),
column(5,
numericInput("w1", "Portf. %", 25, min = 1, max = 100))
)
devtools::install_github("shiny", "rstudio")
install.packages("shiny")
library(shiny)```
library("shiny")```
library(shiny)
library('tidyverse')
library(highcharter)
install.packages("tidyquant")
library(tidyquant)
library(timetk)
install.packages("shiny")
library(shiny)
fluidRow(
column(6,
textInput("stock1", "Stock 1", "SPY")),
column(5,
numericInput("w1", "Portf. %", 25, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock2", "Stock 2", "EFA")),
column(5,
numericInput("w2", "Portf. %", 25, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock3", "Stock 3", "IJS")),
column(5,
numericInput("w3", "Portf. %", 20, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock4", "Stock 4", "EEM")),
column(5,
numericInput("w4", "Portf. %", 20, min = 1, max = 100))
)
fluidRow(
column(6,
textInput("stock5", "Stock 5", "AGG")),
column(5,
numericInput("w5", "Portf. %", 10, min = 1, max = 100))
)
fluidRow(
column(7,
dateInput("date", "Starting Date", "2013-01-01", format = "yyyy-mm-dd"))
)
fluidRow(
column(7,
selectInput("rebalance", "rebalance freq",
c("Yearly" = "years",
"Monthly" = "months",
"Weekly" = "weeks"))
)
)
actionButton("go", "Submit")
portfolio_returns_byhand <- eventReactive(input$go, {
symbols <- c(input$stock1, input$stock2, input$stock3, input$stock4, input$stock5)
prices <- getSymbols(symbols, src = 'yahoo', from = input$date,
auto.assign = TRUE, warnings = FALSE) %>%
map(~Ad(get(.))) %>%
reduce(merge) %>%
`colnames<-`(symbols)
w <- c(input$w1/100, input$w2/100,
input$w3/100, input$w4/100, input$w5/100)
asset_returns_long <-
prices %>%
to.monthly(indexAt = "last", OHLC = FALSE) %>%
tk_tbl(preserve_index = TRUE, rename_index = "date") %>%
gather(asset, returns, -date) %>%
group_by(asset) %>%
mutate(returns = (log(returns) - log(lag(returns))))
portfolio_returns_byhand <-
asset_returns_long %>%
tq_portfolio(assets_col = asset,
returns_col = returns,
weights = w,
col_rename = "returns")
})
renderPlot({
portfolio_returns_byhand() %>%
ggplot(aes(x = returns)) +
geom_histogram(alpha = 0.25, binwidth = .01, fill = "cornflowerblue")
})
renderPlot({
portfolio_returns_byhand() %>%
ggplot(aes(x = returns)) +
geom_histogram(alpha = 0.25, binwidth = .01, fill = "cornflowerblue")
})
renderPlot({
portfolio_returns_byhand() %>%
ggplot(aes(x = returns)) +
geom_density(size = 1, color = "red")
})
renderPlot({
portfolio_returns_byhand() %>%
ggplot(aes(x = returns)) +
geom_histogram(alpha = 0.25, binwidth = .01, fill = "cornflowerblue") +
geom_density(geom = "line", size = 1, color = "red")
})
portfolio_returns_byhand() %>%
ggplot(aes(x = returns)) +
geom_histogram(alpha = 0.25, binwidth = .01, fill = "cornflowerblue") +
geom_density(geom = "line", size = 1, color = "red")
renderPlot({
portfolio_returns_byhand() %>%
ggplot(aes(x = returns)) +
geom_histogram(alpha = 0.25, binwidth = .01, fill = "cornflowerblue") +
geom_density(geom = "line", size = 1, color = "red")
})
renderPlot({
portfolio_returns_byhand() %>%
ggplot(aes(x = returns)) +
geom_histogram(alpha = 0.25, binwidth = .01, fill = "cornflowerblue") +
geom_density(geom = "line", size = 1, color = "red")
})
```{r}
AS21/Step1.r# Return calculations in xts
# December 11, 2019
library(quantmod)
#
# Package quantmod helps us to retrieve data from various sources, in this case, Yahoo! Finance.
# Also note that it calls the package xts.
#
library(purrr)
#
# As a side note, package purrr is part of the tidyverse. We use it here for convenience.
#
#
# The following packages are used in the xts universe.
# Package PerformanceAnalytics performs several useful calculations.
# Package highcharter is actually a "wrapper" function for the Javascript 'Highcharts' library,
# including shortcut functions to plot R objects. 'Highcharts'
# offers numerous chart types with a simple configuration syntax.
#install.packages("PerformanceAnalytics")
library(PerformanceAnalytics)
#install.packages("highcharter")
library(highcharter)
#
# Select stocks (ETFs)
# SPY: State Street S&P 500 Index ETF
# EFA: iShares Non-U.S. Equity Index ETF
# IJS: iShares S&P Small-Cap 600 Value ETF
# EEM: iShares MSCI Emerging Markets Index ETF
# AGG: iShares BBG Barclays U.S. Aggregate Index Bond ETF
#
symbols <- c("Open", "High", "Low", "Close", "Adj.Close","Volume")
#
# The function "getSymbols" which follows, is part of the quantmod package that allows you to retrieve data
# from various different data sources, in...

Project 2 – Portfolio Returns Step 1: Take the programs from Regenstein Chapters 2 and 3, and create your own portfolio. Graph asset and portfolio returns. Apply the shiny app. Try modifying the start...

Answer To: Project 2 – Portfolio Returns Step 1: Take the programs from Regenstein Chapters 2 and 3, and create...

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