A new financial stress index model based on support vector regression and control chart |
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Authors: | Mohamed El Ghourabi Amira Dridi Mohamed Limam |
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Institution: | 1. Department of Economics and Quantitative Methods, ESSECT, University of Tunis, 4, Rue Abou Zakaria Hafsi, 1089, Montfleury, Tunis, Tunisia;2. LARODEC, University of Tunis, 41, Avenue de la Liberté, Cité Bouchoucha, Le Bardo 2000 – Tunis, Tunisia;3. Department of Management Information Systems, Dhofar University, Salalah, Oman |
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Abstract: | Financial stress index (FSI) is considered to be an important risk management tool to quantify financial vulnerabilities. This paper proposes a new framework based on a hybrid classifier model that integrates rough set theory (RST), FSI, support vector regression (SVR) and a control chart to identify stressed periods. First, the RST method is applied to select variables. The outputs are used as input data for FSI–SVR computation. Empirical analysis is conducted based on monthly FSI of the Federal Reserve Bank of Saint Louis from January 1992 to June 2011. A comparison study is performed between FSI based on the principal component analysis and FSI–SVR. A control chart based on FSI–SVR and extreme value theory is proposed to identify the extremely stressed periods. Our approach identified different stressed periods including internet bubble, subprime crisis and actual financial stress episodes, along with the calmest periods, agreeing with those given by Federal Reserve System reports. |
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Keywords: | rough set theory support vector regression financial stress index extreme value theory control chart |
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