Limits of Implied Credit Correlation Metrics Before and During the Crisis

Damiano Brigo, Andrea Pallavicini and Roberto Torresetti

Contents

Introduction to 'Lessons from the Financial Crisis'

1.

The Credit Crunch of 2007: What Went Wrong? Why? What Lessons Can be Learned?

2.

Underwriting versus Economy: A New Approach to Decomposing Mortgage Losses

3.

The Shadow Banking System and Hyman Minsky’s Economic Journey

4.

The Collapse of the Icelandic Banking System

5.

The Quant Crunch Experience and the Future of Quantitative Investing

6.

No Margin for Error: The Impact of the Credit Crisis on Derivatives Markets

7.

The Re-Emergence of Distressed Exchanges in Corporate Restructurings

8.

Modelling Systemic and Sovereign Risks

9.

Measuring and Managing Risk in Innovative Financial Instruments

10.

Forecasting Extreme Risk of Equity Portfolios with Fundamental Factors

11.

Limits of Implied Credit Correlation Metrics Before and During the Crisis

12.

Another view on the pricing of MBSs, CMOs and CDOs of ABS

13.

Pricing of Credit Derivatives with and without Counterparty and Collateral Adjustments

14.

A Practical Guide to Monte Carlo CVA

15.

The Endogenous Dynamics of Markets: Price Impact, Feedback Loops and Instabilities

16.

Market Panics: Correlation Dynamics, Dispersion and Tails

17.

Financial Complexity and Systemic Stability in Trading Markets

18.

The Martingale Theory of Bubbles: Implications for the Valuation of Derivatives and Detecting Bubbles

19.

Managing through a Crisis: Practical Insights and Lessons Learned for Quantitatively Managed Equity Portfolios

20.

Active Risk Management: A Credit Investor’s Perspective

21.

Investment Strategy Returns: Volatility, Asymmetry, Fat Tails and the Nature of Alpha

In this chapter we analyse the limits of popular models or pseudo-models (mostly quoting mechanisms) that in the past have been extensively used to mark-to-market and risk manage multi-name credit derivatives. This chapter presents a compendium of results we first published before the crisis, back in 2006, pointing out the dangers in the modelling paradigms used at the time in the market, and showing how the situation has even worsened subsequently by analysing more recent data. The analysis also points out that the current paradigm had been heavily criticised before the crisis, referring to works by us and other authors addressing the main limitations of the current market paradigm well before popular accounts such as Salmon (2009), Jones (2009) and Lohr (2009) appeared.

We will present a comparison of how a selected set of credit derivatives models fared before and during the crisis, pointing to the fact that the problems plaguing both compound and base implied correlation worsened with the advent of the credit crunch.

To develop the above comparison, we first introduce the Gaussian copula, which represents a common way to introduce dependence in credit derivatives modelling

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