Quadratic Models for Portfolio Credit Risk with Shot-Noise Effects

We propose a reduced form model for default that allows us to derive closed-form solutions to all the key ingredients in credit risk modeling: risk-free bond prices, defaultable bond prices (with and without stochastic recovery) and probabilities of survival. We show that all these quantities can be represented in general exponential quadratic forms, despite the fact that the intensity is allowed to jump producing shot-noise effects. In addition, we show how to price defaultable digital puts, CDSs and options on defaultable bonds. Further on, we study a model for portfolio credit risk where we consider both firm specific and systematic risks. The model generalizes the attempt from Duffie and Garleanu (2001). We find that the model produces realistic default correlation and clustering of defaults. Then, we show how to price first-to-default swaps, CDOs, and draw the link to currently proposed credit indices

Did Liquidity Providers Become Liquidity Seekers?

The misalignment between corporate bond and credit default swap (CDS) spreads (i.e., CDSbond basis) during the 2007-09 financial crisis is often attributed to corporate bond dealers shedding off their inventory, right when liquidity was scarce. This paper documents evidence against this widespread perception. In the months following Lehman's collapse, dealers, including proprietary trading desks in investment banks, provided liquidity in response to the large selling by clients. Corporate bond inventory of dealers rose sharply as a result. Although providing liquidity, limits to arbitrage, possibly in the form of limited capital, obstructed the convergence of the basis. We further show that the unwinding of precrisis 'basis trades' by hedge funds is the main driver of the large negative basis. Price drops following Lehman's collapse were concentrated among bonds with available CDS contracts and high activity in basis trades. Overall, our results indicate that hedge funds that serve as alternative liquidity providers at times, not dealers, caused the disruption in the credit market

Simulation-based Estimation Methods for Financial Time Series Models

Published in Handbook of computational finance, 2010, https://doi.org/10.1007/978-3-642-17254-0_15</p

Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance

Published in Handbook of financial time series, 2008, https://doi.org/10.1007/978-3-540-71297-8_22</p

Maximum likelihood and Gaussian estimation of continuous time models in finance

Ministry of Education, Singapore under its Academic Research Funding Tier