An Optimal Design of Early Warning Systems: A Bayesian Quickest Change Detection Approach

Li, Haixi (2012): An Optimal Design of Early Warning Systems: A Bayesian Quickest Change Detection Approach.

Abstract

This paper proposed a new optimal design of Early Warning Systems (EWS) to detect early warning signals of an impending financial crisis. The problem of EWS was formulated from a policy maker's perspective. Hence the probability threshold was obtained by minimizing the policy maker's welfare loss. This paper employed the state-of-the-art Bayesian Quickest Change Detection (BQCD) as the methodology to detect the early warning signals as soon as possible. We showed that the BQCD method outperformed the Logit model used in traditional EWS models based on results of simulation exercise and the out-of-sample predictions of the 1997 Asian financial crises. We found that not only early warning signals were stronger prior to a crisis, but also stronger warning signals appeared more frequently. The BQCD method was sensitive to the increase in frequency, hence out-performed the traditional Logit-EWS model.

• Item Type: MPRA Paper
• Language: English
• Keywords: early warning system; financial crises; monetary policy; Bayesian quickest change detection; optimal stopping
• Subjects: F - International Economics > F3 - International Finance; E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit

References

Ball, Laurence, "Policy Rules for Open Economies," in John Taylor, ed., Monetary Policy Rules, The University of Chicago Press, 1999.

Berg, Andrew and Catherine Pattillo, "Predicting currency crises: The indicators approach and an alternative," Journal of International Money and Finance, 1999, 18 (4), 561-586.

Bussiere, Matthieu and Marcel Fratzscher, Low probability, high impact: Policy making and extreme events, Journal of Policy Modeling, 2008, 30 (1), 111-121.

Candelon, Bertrand, Elena-Ivona Dumitrescu, and Christophe Hurlin, Currency Crises Early Warning Systems: why they should be Dynamic, Research Memoranda 047,Maastricht : METEOR, Maastricht Research School of Economics of technology and Organization2010.

Candelon, Bertrand, Elena-Ivona Dumitrescu, and Christophe Hurlin, "How to evaluate an Early Warning System? Towards a United Statistical Framework for Assessing Financial Crises Forecasting Methods," Research Memoranda 046, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization 2010.

Davis, E. Philip and Dilruba Karim, Comparing early warning systems for banking crises, Journal of Financial Stability, June 2008, 4 (2), 89-120.

Gramlich, Dieter, Gavin L. Miller, Mikhail V. Oet, and Stephen J. Ong, Early Warning Systems for Systemic Banking Risk: Critical Review and Modeling Implications,Banks and Bank System, 2010, 5, 199-211.

IMF, The IMF-FSB Early Warning Exercise: Design and Methodological Toolkit, International Monetary Fund 2010.

Kaminsky, Graciela L. and Carmen M. Reinhart, The Twin Crises: The Causes of Banking and Balance-of-Payments Problems, American Economic Review, June 1999, 89 (3), 473-500.

Kaminsky, Graciela, Saul Lizondo, and Carmen M. Reinhart, Leading Indicators of Currency Crises, IMF Sta Papers, March 1998, 45 (1), 1-48.

Karatzas, Ioannis and Steven E. Shreve, Brownian motion and stochastic calculus, second ed., Vol. 113 of Graduate Texts in Mathematics, New York: Springer-Verlag, 1991.

Polunchenko, Aleksey S and Alexander G Tartakovsky, State-of-the-Art in Sequential Change-Point Detection, Sequential Analysis, 2011, 29 (2), 34.

Shewhart, W A, Economic Control of Quality of Manufactured Product, Vol. 27, D. Van Nostrand Company, Inc, 1931.

Shiryaev, A. N., On Optimum Methods in Quickest Detection Problems, Theory of Probability and its Applications, 1963, 8 (1), 22-46.

Shiryaev, Albert N., Optimal Stopping Rules, Springer-Verlag, 1978.