Generating a density plot

The density plot uses the kernel density estimation to generate the distribution. In this recipe, we will utilize the density() function to generate a plot. The density plots can be used to study the underlying distribution of the data.

Getting ready

We will use the quantmod package to download the stock prices for Microsoft and also calculate monthly returns:

install.packages("quantmod")
library(quantmod)

How to do it…

We will download the data in R using the getSymbols() function. Once we have the data, we can calculate the monthly returns using the monthlyReturns() function:

prices = c("MSFT")
getSymbols(prices)
msft_m = monthlyReturn(MSFT)

In order to generate a density plot, we will first estimate the kernel density using the density() function in R. Please note that we have plotted a density plot over the histogram and, hence, we need to use the lines() function. The lines() function will allow us to plot a density plot over the histogram:

msft_d = density(msft_m...