A Proximity Based Macro Stress Testing Framework

Waelchli, B. (2016). A proximity based macro stress testing framework. Dependence Modeling, 4(1), pp. -. Retrieved 18 Nov. 2016, from doi:10.1515/demo-2016-0015

Posted: 16 Sep 2015 Last revised: 19 Nov 2016

See all articles by Boris Waelchli

Boris Waelchli

University of Zurich - Department of Banking and Finance

Date Written: November 16, 2016

Abstract

In this a paper a non-linear macro stress testing methodology with focus on early warning is developed. The methodology builds on a variant of Random Forests and its proximity measures. It is embedded in a framework, in which naturally defined contagion and feedback effects transfer the impact of stressing a relatively small part of the observations on the whole dataset, allowing to estimate a stressed future state. It will be shown that contagion can be directly derived from the proximities while iterating the proximity based contagion leads to naturally defined feedback effects. Since the methodology is Random Forests based the framework can be estimated on large numbers of risk indicators up to big data dimensions, fostering the stability of the results while reducing inaccuracies in estimated stress scenarios by only stressing a small part of the observations. This procedure allows accurate forecasting of events under stress and the emergence of a potential macro crisis. The framework also estimates a set of the most influential economic indicators leading to the potential crisis, which can then be used as indications of remediation or prevention.

Keywords: Random Forests; Machine Learning; Stress Testing; Early Warning Indicators; Big Data

Suggested Citation

Waelchli, Boris, A Proximity Based Macro Stress Testing Framework (November 16, 2016). Waelchli, B. (2016). A proximity based macro stress testing framework. Dependence Modeling, 4(1), pp. -. Retrieved 18 Nov. 2016, from doi:10.1515/demo-2016-0015, Available at SSRN: https://ssrn.com/abstract=2660498 or http://dx.doi.org/10.2139/ssrn.2660498

Boris Waelchli (Contact Author)

University of Zurich - Department of Banking and Finance ( email )

Plattenstrasse 14
Z├╝rich, 8032
Switzerland

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