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CMARS and GAM & CQP—Modern optimization methods applied to international credit default prediction
Authors:Özge Sezgin Alp  Erkan Büyükbebeci  Fatma Yerlikaya Özkurt
Institution:
  • a Institute of Applied Mathematics, Middle East Technical University, 06531 Ankara, Turkey
  • b Faculty of Commercial Sciences, Ba?kent University, 06530 Ankara, Turkey
  • c Turkish Statistical Institute, 06100 Ankara, Turkey
  • d Department of Mathematics, Selçuk University, 42697 Konya, Turkey
  • e Department of Mathematics, Dicle University, 21280 Diyarbak?r, Turkey
  • Abstract:In this paper, we apply newly developed methods called GAM & CQP and CMARS for country defaults. These are techniques refined by us using Conic Quadratic Programming. Moreover, we compare these new methods with common and regularly used classification tools, applied on 33 emerging markets’ data in the period of 1980-2005. We conclude that GAM & CQP and CMARS provide an efficient alternative in predictions. The aim of this study is to develop a model for predicting the countries’ default possibilities with the help of modern techniques of continuous optimization, especially conic quadratic programming. We want to show that the continuous optimization techniques used in data mining are also very successful in financial theory and application. By this paper we contribute to further benefits from model-based methods of applied mathematics in the financial sector. Herewith, we aim to help build up our nations.
    Keywords:Financial mathematics  Sovereign defaults  Emerging markets  CART  GAM  Logistic regression  Regularization  MARS  CMARS  Continuous optimization  Conic quadratic programming
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