Stress-Testing with Fully Flexible Causal Inputs
ARPM - Advanced Risk and Portfolio Management
April 2, 2012
Risk, 25, 4, p. 61-65 (2012)
Propagating causal stress-tests or contagion on selected risk factors to all the risk drivers is a challenging task. We use Entropy Pooling by Meucci (2008) to address this issue. Our causal stress-tests comprise, but are not restricted to, stress-testing Bayesian networks. We detail the theory and we present a case study: stress-testing a market driven by swap curve, credit spreads, stock market return, stock market volatility, currency strength, inflation, and commodities. Fully commented code supporting the empirical analysis is available for download.
Number of Pages in PDF File: 13
Keywords: Contagion, Bayesian network, entropy pooling, non-Boolean variables, prior distribution, posterior distribution, linear programming, convex programming, dual optimization, 'Fully Flexible'
JEL Classification: C1, G11
Date posted: December 7, 2010 ; Last revised: October 11, 2012