Correlation Risk Modelling and Management (2nd Edition)
First published:
ISBN: 978-1-78272-405-6
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Correlation Trading Strategies – Opportunities and Limitations
Introduction
Correlation Basics: Definitions, Applications and Terminology
Empirical Properties of Correlation: How do Correlations Behave in the Real World?
The Pearson Correlation Model – Work of the Devil?
Cointegration – A Superior Concept to Correlation?
Financial Correlation Modelling – Bottom-up Approaches
Valuing CDOs with the Gaussian Copula – What Went Wrong?
The One-Factor Gaussian Copula Model – Too Simplistic?
Financial Correlation Models – Top-Down Approaches
Stochastic Correlation Models
Quantifying Market Correlation Risk
Quantifying Credit Correlation Risk
Hedging Correlation Risk
Correlation Trading Strategies – Opportunities and Limitations
Credit Value at Risk under Basel III – Too Simplistic?
Basel III and XVAs
Fundamental Review of the Trading Book
The Future of Correlation Modelling
Answers to Questions and Problems in Correlation Risk Modelling and Management
"The best investment one can make is to invest in your own abilities."
– Warren Buffett
In this chapter, we give an overview and analyse the most popular correlation trading strategies in financial practice. Six correlation strategies are discussed: (1) empirical correlation trading; (2) pairs trading; (3) multi-asset options; (4) structured products; (5) correlation swaps; and (6) dispersion trading.
EMPIRICAL CORRELATION TRADING
Empirical correlation trading attempts to exploit historically significant correlations within or between financial markets. Numerous financial correlations can be investigated. One area of interest is the autocorrelation between stocks or between indices. Figure 13.1 shows the autocorrelation of the Dow Jones Industrial Index (Dow) from 1920 to 2017.
From Figure 13.1, we observe that autocorrelation since the start of World War Two in 1939 until the mid-1970s was mostly positive. However, since the mid-1970s, autocorrelation has been declining and has mostly been in range with a mean of zero until 2014. We also observe the high negative autocorrelation in bad economic times as in the Great Depression and the Great Recession. Altogether
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