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Stress-Testing with Fully Flexible Causal Inputs

Risk, 25, 4, p. 61-65 (2012)

13 Pages Posted: 7 Dec 2010 Last revised: 11 Oct 2012

Attilio Meucci

ARPM - Advanced Risk and Portfolio Management

Date Written: April 2, 2012

Abstract

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.

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

Suggested Citation

Meucci, Attilio, Stress-Testing with Fully Flexible Causal Inputs (April 2, 2012). Risk, 25, 4, p. 61-65 (2012). Available at SSRN: https://ssrn.com/abstract=1721302 or http://dx.doi.org/10.2139/ssrn.1721302

Attilio Meucci (Contact Author)

ARPM - Advanced Risk and Portfolio Management ( email )

HOME PAGE: http://www.arpm.co/

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