In msperlin/afedR: Data and Functions for Book "Analyzing Financial and Economical Data with R"

library(BatchGetSymbols)
library(tidyverse)

df_sp500 <- GetSP500Stocks()

my_tickers <- df_sp500$Tickers

future::plan(future::multisession, 
             workers = floor(parallel::detectCores()/2))

first_date <- '2015-01-01'
df_prices <- BatchGetSymbols(tickers = my_tickers, 
                             first.date = first_date, 
                             last.date = Sys.Date(),
                             freq.data = 'yearly', 
                             do.parallel = TRUE)[[2]]

tab <- df_prices %>%
  na.omit() %>%
  group_by(ticker) %>%
  summarise(mean = mean(ret.adjusted.prices),
            sd = sd(ret.adjusted.prices))

p <- ggplot(tab, aes(x = sd, y = mean)) + 
  geom_point() + 
  xlim(0, 0.5) + ylim(-0.5, 0.5)

print(p)

# none
my_answers <- rep(0, 5)

Question

Use the BatchGetSymbols::GetSP500Stocks function to discover all tickers currently belonging to the SP500 index. Using BatchGetSymbols, download the annual return data for all stocks in the index, from r '2015-01-01' to the current day. After that, create the average/variance map by plotting the average annual return as the y axis and the standard deviation as the x axis. Tip: Use the parallel option in BatchGetSymbols to speed up the execution of the code. Also, you will find many outliers in the raw data. Make sure that the graph is visible limiting the x and y axes (see the ggplot2::xlim and ggplot2::ylim functions).

Solution

Meta-information

extype: string exsolution: r mchoice2string(c(TRUE, FALSE, FALSE, FALSE, FALSE), single = TRUE) exname: "function 01" exshuffle: TRUE

msperlin/afedR documentation built on Sept. 11, 2022, 9:49 a.m.