CMARS and GAM & CQP-Modern optimization methods applied to international credit default prediction
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Tarih
2011
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
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. (C) 2010 Elsevier B.V. All rights reserved.
Açıklama
14th International Congress on Computational and Applied Mathematics (ICCAM) -- SEP 29-OCT 02, 2009 -- Antalya, TURKEY
Anahtar Kelimeler
Financial Mathematics, Sovereign Defaults, Emerging Markets, Cart, Gam, Logistic Regression, Regularization, Mars, Cmars, Continuous Optimization, Conic Quadratic Programming
Kaynak
Journal of Computational and Applied Mathematics
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
235
Sayı
16
