Interpreting correlation

Now you will learn how to compute the correlation between bond returns and equity returns. Just like volatilities, these correlations are dynamic. Therefore you need to distinguish between a static analysis that calculates correlations over a complete sample and a dynamic analysis that calculates correlations over a rolling sample. This is a similar analysis as you did for the time-varying performance evaluation in terms of mean return and volatility.

In this exercise you will learn 3 new functions from the PerformanceAnalytics package: chart.Scatter(), chart.Correlation(), and chart.RollingCorrelation().

Diese Übung ist Teil des Kurses

Introduction to Portfolio Analysis in R

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Anleitung zur Übung

Plot the equity returns (returns_equities) against the bond returns (returns_bonds) using the function chart.Scatter() with the bond returns on the x-axis. Do you see a relation?
Compute the correlation between the variables returns_bonds and returns_equities using cor().
Merge returns_bonds, and returns_equities using merge(). Call this returns.
Compute and visualize the correlation again, using chart.Correlation() with returns as the argument.
Compute the rolling 24-month estimates of the bond-equity correlation using the function chart.RollingCorrelation().

Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Create a scatter plot
chart.Scatter(___, ___, xlab = "bond returns", ylab = "equity returns", main = "bond-equity returns")

# Find the correlation


# Merge returns_bonds and returns_equities 
returns <- merge(___, ___)

# Find and visualize the correlation using chart.Correlation


# Visualize the rolling estimates using chart.RollingCorrelation
chart.RollingCorrelation(___, ___, width = ___)

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