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Tous les séminaires

Jeudi 24 Novembre

16H30 Jean-Paul RENNE (University of Lausanne) "Affine Modelling of Credit Risk, Credit Event and Contagion"

17H30 Sébastien FRIES (CREST) "Mixed Causal and Noncausal Heavy-Tailed MAR (p,q) Processes and the Modelling of Speculative Bubbles"


De 16H15 à 18H15, Salle S016, INSEE-CREST, MK2, 15 Bd Gabriel Péri, 92245 Malakoff, Métro Malakoff Plateau de Vanves

 

Jean-Paul RENNE

AFFINE MODELLING OF CREDIT RISK, CREDIT EVENT AND CONTATION”

This paper proposes a general positive affine credit-risk pricing model for defaultable securities in a discrete-time framework. Building on the recently introduced non-negative Gamma-zero distribution entailing a point mass at zero, our model jointly allows for (i) the presence of systemic entities by breaking down the no-jump condition on the factors’ conditional distribution, (ii) contagion effects between defaultable entities, (iii) the pricing of credit events and (iv) the presence of stochastic recovery rates. The main advantage of our framework is its ability to relax simultaneously several restrictive assumptions made in the existing models while staying in the affine class, thus delivering explicit pricing formulas for default-sensitive securities like bonds and credit default swaps. A first application shows how this framework can be exploited to estimate sovereign credit risk premiums in an endowment-economy model. In a second application, we jointly model term structures of CDS denominated in different currencies and extract market-implied probabilities of depreciations at default. A third application illustrates the ability of the model to replicate the behavior of banks’ CDS spreads that was observed in the aftermaths of the Lehman bankruptcy.

Papier joint avec Alain Monfort, Guillaume Roussellet et Fulvio Pegoraro.

Sébastien FRIES

MIXED CAUSAL AND NONCAUSAL HEAVY-TAILED MAR(p,q) PROCESSES AND THE MODELLING OF SPECULATIVE BUBBLES

 

The adjunction of a noncausal component to standard causal linear autoregressive processes often yields a better fit to economic and financial time series. The general framework of mixed causal/noncausal MAR(p,q) processes with alpha-stable errors is investigated. The causal dynamics is derived and shown to display quadratic GARCH effects in direct time. The existence of a unit root in this causal dynamics is of particular interest as it allows to exhibit linear noncausal processes which are stationary, and even positive, martingales. Finally, under the broader assumption that the errors belong to the domain of attraction of a stable distribution, it is shown that contrary to the OLS estimator, the LAD estimator of the autoregressive parameters is able to identify causal and noncausal structures.

 

Papier joint avec Jean-Michel Zakoïan