Abstract

The speaker introduces stochastic time change to default intensity models of credit risk as a parsimonious way to account for stochastic volatility in credit spreads. He derives two series of solutions for the survival probability function, and shows that both methods are applicable when the intensity follows the widely-used basic affine process. This leads to straightforward and efficient solutions to bond prices and CDS spreads. The speaker then estimates the time-changed model on panels of CDS spreads (across maturity and observation time) using Bayesian MCMC methods. He finds strong evidence of stochastic time change, both in-sample and in out-of-sample forecasting. This is joint work with Ovidiu Costin, Min Huang, and Pawel Szerszen.

About the speaker

Dr Michael Gordy received his BA degree in Mathematics & Philosophy from Yale University in 1985 and PhD degree in Economics from Massachusetts Institute of Technology in 1994. He held visiting positions at the Indian School of Business (2006) and Princeton University (2014). He joined the Board of Governors of the Federal Reserve System of the United States and is currently the Senior Economist.

Dr Gordy’s research interests are in Stochastic Volatility in Credit Spreads and Counterparty Credit Risk in OTC Markets. He is serving at the editorial board of several journals including Journal of Banking and Finance, International Journal of Central Banking, Journal of Credit Risk, and Global Credit Review. He received the award of Financial Risk Manager of the Year from Global Association of Risk Professionals in 2003 and the Quant of the Year from Risk Magazine in 2004.

The lecture is free and open to all. Seating is on a first-come, first-served basis.

HKUST Jockey Club Institute for Advanced Study
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