Stathis Tompaidis (UT Austin): Choosing Scenarios to Stress Test Financial Institutions

Stathis Tompaidis: Choosing Scenarios to Stress Test Financial Institutions

Abstract:
Since the 2008 Financial Crisis, stress tests have become a preferred method of assessing risk for large financial institutions, yet, in practice, scenario choice has largely been ad-hoc. Given a set of scenarios, we propose three methods designed to identify scenarios with large portfolio losses. The three methods correspond to: 1) a linear case, when the portfolio's profit or loss (P/L) depends linearly on risk factors with a known covariance matrix; 2) a robust case, where the P/L depends linearly on risk factors whose distribution is assumed to lie within an uncertainty set based on the Wasserstein distance; 3) a non-linear case, when the P/L is a non-linear function of the risk factors. We illustrate the performance of our methods in a numerical study based on the 2019 Commodity Futures Trading Commission stress test for central counterparties.

Bio:
Stathis Tompaidis is a professor at the Information, Risk and Operations Management department, and the department of Finance at the McCombs School of Business at The University of Texas at Austin. His research focuses on the development of quantitative methods for solving complex business problems, especially in the areas of risk management, derivative pricing, asset allocation, energy finance, real estate finance, and real options. His research has appeared in journals such as Journal of Finance, Journal of Financial Economics, Operations Research, and Management Science. He has collaborated with companies such as Schlumberger, Shell, and ElectroPeru. After finishing his undergraduate studies at Aristotle’s University of Thessaloniki in Greece, he received his Ph.D. in Physics from The University of Texas at Austin in 1994. He has also held positions at Université de Rennes I, and the University of Toronto, and visiting positions at Columbia University, Duke University, the Instituto Tecnologico Autonomo de Mexico (ITAM), and Northwestern University.