CMARS and GAM & CQP-Modern optimization methods applied to international credit default prediction

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:235

Article; Proceedings Paper

Alp, Ozge Sezgin^1,2  Buyukbebeci, Erkan³  Cekic, Aysegul Iscanoglu^1,4  Ozkurt, Fatma Yerlikaya¹  Taylan, Pakize⁵  Weber, Gerhard-Wilhelm¹ 

[1] Middle E Tech Univ, Inst Appl Math, TR-06531 Ankara, Turkey

[2] Baskent Univ, Fac Commercial Sci, TR-06530 Ankara, Turkey

[3] Turkish Stat Inst, TR-06100 Ankara, Turkey

[4] Selcuk Univ, Dept Math, TR-42697 Konya, Turkey

[5] Dicle Univ, Dept Math, TR-21280 Diyarbakir, Turkey

关键词: Financial mathematics;    Sovereign defaults;    Emerging markets;    CART;    GAM;    Logistic regression;    Regularization;    MARS;    CMARS;    Continuous optimization;    Conic quadratic programming;   

DOI  :  10.1016/j.cam.2010.04.039

来源: Elsevier

【 摘 要 】

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.

【 授权许可】

Free