PDF Ebook Estimating Implied Default Probabilities and Recovery Values
This paper develops a framework to estimate implied recovery values and risk-neutral default probability term-structures from sovereign bond prices. The model is applied to Greek bonds during the European debt crisis of 2010. In April and May 2010, the probability of a Greek default quickly rises from 5% to 40%. On Monday 10 May 2010, after EU finance ministers, the ECB and the IMF agree on a EUR 750 billion EU-wide rescue package, the default probability drops instantaneously below 10%. The implied recovery value remains between 40 and 60 cents on the euro and does not get revised materially during this period.
With the recent debt crisis in Southern Europe, interest in the valuation of sovereign debt has revived. Although there is a large literature on the pricing and modeling of corporate debt, there has beencomparably little attention for sovereign credit risk in the academic literature. This paper aims to fill this gap and develops a framework to simultaneously extract implied recovery values and the risk-neutral term-structure of default probabilities from sovereign bond prices. The reduced-form model employs a binomial lattice framework where the price of a bond is the probability-weighted average of promised cash-flows (if the obligor survives) and the recovery value (if the obligor defaults). By imposing a flexible parametric structure on the term-structure of default probabilities, it is possible to simultaneously extract default probabilities and the recovery value using the cross-section of outstanding bonds. The framework improves existing reduced-form credit models in two directions. First, the model allows for a term-structure of default risk. Second, the model also provides implicit market assumptions about the recovery value, which is valuable given that sovereign defaults are both rare and country-specific. Recasting market prices into default probabilities and recovery values provides market professionals and policy makers with information that is better to interpret than plain bond prices.
The model is applied to Greek bond prices during the period April-May 2010. Although painful for investors and European policy makers, the sample period provides a unique window to study the pricing of sovereign risks. The sample is characterized by a sharp re-pricing of Greek government debt, the announcement of severe austerity measures and great social unrest in both Greece and the rest of (Southern) Europe. The empirical section of this paper shows how the default probability term-structure and the recovery value implicit in Greek bonds evolved during the crisis. Model estimates show that the probability of a Greek credit event rises quickly from below 5% to more than 40% during this period. In the weekend of 8 and 9 May 2010, EU finance ministers, the ECB and the IMF announce a significant European rescue package. This leads to relief in sovereign bond prices and the probability of default falls to less than 10% over the weekend, somewhat elevated from “pre-stress” levels. The implicit recovery ratio gets hardly revised over this period and remains between 40 and 60 cents on the euro. This is close to the well-documented experience for corporate defaults and the scarce evidence from previous sovereign defaults.
The paper then studies the fit of the model by analyzing pricing errors for individual bonds and relates pricing errors to bond characteristics such as coupon, time-to-maturity and liquidity. This is the first paper to explicitly study the impact of additional variables on the pricing of sovereign bonds.1 Bondpricing errors (the difference between market prices and fitted prices) are relatively small and there is a strong association between changes in market prices and model prices. Pricing errors decrease with the amount outstanding (a proxy for liquidity).
By analyzing the price adjustments of the outstanding publicly-traded Greek debt, this paper provides an in-depth analysis of how market participants adjusted their assumptions during the European debt crisis of 2010. For policy makers, this information provides a useful basis to study how probabilitydefault term-structures and the recovery values evolve over time during stressful market circumstances. For professionals in financial markets, this information can be used to transform pricedata into meaningful information about implicit default probabilities and recovery values. Investors can use this information to identify investment opportunities. For risk management professionals, finally, the parameter estimates from the model can be used to manage the risk of a portfolio of risky assets. Speculative investments beyond a certain threshold are sometimes precluded from investor portfolios. Non-investment-grade bonds are a prime example. Given that ratings are both sticky and relatively slow to adjust to new information, the framework in this paper can be used to dynamically adjust portfolio holdings to comply with the risk management limits.
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PDF Ebook Estimating Implied Default Probabilities and Recovery Values
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