Commodities data
The plotting function pairs()
creates a pairwise scatterplot of the components of a multivariate time series with two or more dimensions. It is used on a zoo
object rather than an xts
object.
A roughly circular shape of a scatterplot indicates a low correlation between the log-returns of two different commodities. Generally speaking, low correlation is good in a portfolio as it implies that the assets are diversified. High correlation, on the other hand, represents a risk that must be properly modelled.
In this exercise, you will look at gold and oil prices over a 25 year period, calculate their daily and monthly log-returns, and plot them. The data gold
and oil
, containing the daily prices from 1990-2015 of gold and Brent crude oil, respectively, are available in your workspace.
This exercise is part of the course
Quantitative Risk Management in R
Exercise instructions
- Use
plot()
to plot thegold
andoil
time series separately. - Calculate the daily log-returns of each commodity and assign to
goldx
andoilx
, respectively. - Calculate the monthly log-returns of each commodity and assign to
goldx_m
andoilx_m
, respectively. - Use
merge()
to mergegoldx_m
andoilx_m
, in that order, intocoms
. - Plot
coms
, a multivariate series, with vertical bars. - Convert
coms
to azoo
object withas.zoo()
and then applypairs()
to create a pairwise scatterplot.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Plot gold and oil prices
___(___)
___(___)
# Calculate daily log-returns
goldx <- ___(___)
oilx <- ___(___)
# Calculate monthly log-returns
goldx_m <- ___(___)
oilx_m <- ___(___)
# Merge goldx_m and oilx_m into coms
coms <- ___(___, ___)
# Plot coms with vertical bars
___(___, ___)
# Make a pairwise scatterplot of coms
___(___)