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Subperiod performance analysis and the function window

In the previous exercise, you computed the performance measure on each possible sample of a fixed size by rolling through time. Often investors are interested in the performance of a specific subwindow. You can create subsets of a time series in R using the function window(). The first argument is the return series that needs subsetting. The second argument is the starting date of the subset in the form "YYYY-MM-DD", and the third argument is the ending date in the same format.

In this exercise, you will be working with the daily S&P 500 returns, which is available as the object sp500_returns.

This exercise is part of the course

Introduction to Portfolio Analysis in R

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Exercise instructions

  • Fill in the missing arguments to the object sp500_2008 so that you have subsetted the entire year of 2008.
  • Define the object sp500_2014 as the S&P 500 portfolio returns for 2014.
  • Some plotting settings are added in the R console. Leave these as they are!
  • Plot histogram of returns in 2008 using the function chart.Histogram(). Set the argument methods = c("add.density", "add.normal") to visualize the non-parametric estimate of the density and the density under an assumed normal distribution.
  • Plot the same histogram, but for 2014.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Fill in window for 2008
sp500_2008 <- window(sp500_returns, start = "___", end = "___")

# Create window for 2014
sp500_2014 <-

# Plotting settings
par(mfrow = c(1, 2) , mar=c(3, 2, 2, 2))
names(sp500_2008) <- "sp500_2008"
names(sp500_2014) <- "sp500_2014"

# Plot histogram of 2008


# Plot histogram of 2014

Edit and Run Code