Credit scoring methods and accuray ratio

Download
2005
İşcanoğlu, Ayşegül
The credit scoring with the help of classification techniques provides to take easy and quick decisions in lending. However, no definite consensus has been reached with regard to the best method for credit scoring and in what conditions the methods performs best. Although a huge range of classification techniques has been used in this area, the logistic regression has been seen an important tool and used very widely in studies. This study aims to examine accuracy and bias properties in parameter estimation of the logistic regression by using Monte Carlo simulations in four aspect which are dimension of the sets, length, the included percentage defaults in data and effect of variables on estimation. Moreover, application of some important statistical and non-statistical methods on Turkish credit default data is provided and the method accuracies are compared for Turkish market. Finally, ratings on the results of best method is done by using receiver operating characteristic curve.

Suggestions

Credit default swap valuation: an application via stochastic intensity models
Namuslu, Merve; Danışoğlu, Seza; Ayaydın Hacıömeroğlu, Hande; Department of Financial Mathematics (2016)
The objective of this thesis is to study the pricing of a single-name credit default swap (CDS) contract via the discounted cash flow method with reduced-form survival probability functions depending on stochastic intensity. The ability of the model in predicting the market-observed spreads is tested as well by using bond and CDS data from the US market. In credit risk modeling, the CIR (Cox-Ingersoll-Ross) model is used. The main reason for using a reduced-form model in pricing the CDS contracts is the adv...
Credit Risk Market and the Recent Loan Profile in the Turkish Banking Sector
Özdemir, Özlem (2009-05-01)
Very little research has been done on the financial stability implications of credit risk transfer markets. In particular there is a paucity of work considering the interactions between the various credit risk transfer markets or instruments. Regarding credit derivatives, the small number of existing studies can be explained by a lack of quantitative data and by the brief history of the market" (Kiff et al., 2002, page 2). This paper tries to explain the development of credit risk transfer instruments and h...
Stochastic credit default swap pricing
Gökgöz, İsmail Hakkı; Uğur, Ömür; Yolcu Okur, Yeliz; Department of Financial Mathematics (2012)
Credit risk measurement and management has great importance in credit market. Credit derivative products are the major hedging instruments in this market and credit default swap contracts (CDSs) are the most common type of these instruments. As observed in credit crunch (credit crisis) that has started from the United States and expanded all over the world, especially crisis of Iceland, CDS premiums (prices) are better indicative of credit risk than credit ratings. Therefore, CDSs are important indicators f...
On the single name CDS price under structural modeling
GOKGOZ, I. H.; Uğur, Ömür; Okur, Y. Yolcu (2014-03-15)
Regulators, banks and other market participants realized that true assessment of the credit risk is more critical and complex than their ex-ante appraisals after the US Credit Crunch. They have turned their attention to complex credit risk models and credit instruments such as credit derivatives. Credit default swap contracts (CDSs) are the most common credit derivatives used for speculation and hedging purposes in the credit markets. Thus, in this paper we fundamentally study the pricing of a single name C...
Credit Risk Evaluation Using Clustering Based Fuzzy Classification Method
Koç, Oğuz; Başer, Furkan; Kestel, Sevtap Ayşe (2023-03-01)
Credit scoring is a crucial indicator for banks to determine the financial position and the eligibility of aclient for credit. In order to assign statistical odds or probabilities to predict the risk of nonpayment inrelation to many other factors, the scoring criterion becomes an important issue. The focus of thisstudy is to propose a clustering based fuzzy classification (CBFC) method for credit risk assessment. Weaim to illustrate the beneficial use of machine learning (ML) methods whose prediction power ...
Citation Formats
A. İşcanoğlu, “Credit scoring methods and accuray ratio,” M.S. - Master of Science, Middle East Technical University, 2005.