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توضیحات

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مشخصات این مقاله :

عنوان مقاله :

A zero-adjusted gamma model for mortgage loan loss given default

ترجمه فارسی عنوان :

بررسی تنظیمات مدل صفر گاما برای از دست دادن وام داده شده

سال انتشار : 2013

متعلق به مجله یا ژورنال : نشریه بین المللی پیش بینی – International Journal of Forecasting

فرمت: PDF

تعداد صفحات: 15

شماره پروژه: 5093


کلمات کلیدی :

Regression,Finance,Credit risk modelling,Mixture models,LGD,Basel II

رگرسیون، سرمایه گذاری، مدل سازی ریسک اعتباری، مدل های مخلوط، LGD ، بازل


چکیده  :

Abstract

The Internal Ratings Based (IRB) approach introduced in the Basel II Accord requires financial institutions to estimate not just the probability of default, but also the Loss Given Default (LGD), i.e., the proportion of the outstanding loan that will be lost in the event of a default. However, modelling LGD poses substantial challenges. One of the key problems in building regression models for estimating the loan-level LGD in retail portfolios such as mortgage loans relates to the difficulty of modelling their distributions, as they typically contain extensive numbers of zeroes. In this paper, an alternative approach is proposed where a mixed discrete-continuous model for the total loss amount incurred on a defaulted loan is developed. The model accommodates the probability of a zero loss and the loss amount given that a loss occurs simultaneously. The approach is applied to a large dataset of defaulted home mortgages from a UK bank and compared to two well-known industry approaches. Our zero-adjusted gamma model is shown to present an alternative and
competitive approach to LGD modelling.


مقدمه این مقاله :

 Introduction

The advanced Internal Ratings Based (IRB) approach outlined in the Basel II and Basel III Accords allows banks to calculate their own regulatory capital requirements based on internal credit risk model estimates (Basel Committee on Banking Supervision, 2005).It requires banks to develop suitable methods for estimating three key parameters for each segment of their loan portfolios: PD (probability of default in the next 12 months), LGD (loss given default, i.e., the proportion of the outstanding loan that will be lost in the event of a default)
and EAD (exposure at default).For consumer credit, probability of default modelling has been a main objective of credit scoring for several decades. However, the additional IRB requirement of having to model LGD has posed substantial challenges, partly because of the properties of its distribution. Datasets of defaulted loan observations for residential mortgage portfolios or other retail portfolios usually exhibit a large probability mass at zero where no losses have been incurred,either because the account has cured and returned to performing status, or, in the case of mortgage loans, because the property has subsequently been repossessed and the sale price covered the loan balance at default adequately (Leow & Mues, 2012; Loterman, Brown, Martens, Mues, & Baesens, 2012; Thomas, Matuszyk, & Moore, 2012). Also, whereas the actual LGD observations of some individual loan defaults may fall outside the (0, 1) range, as LGD is supposed to include all economic costs (e.g., additional collection costs) and recoveries (e.g., penalties paid),the model estimates themselves are expected to be constrained to this interval.


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توضیحات بیشتر در مورد پروژه :

در این مقاله خواهید خواند که چگونه اعتبار داخلی بر اساس IRB معرفی شده در بازل نیاز موسسات مالی را برطرف ساخت. تنظیم مدل صفر گاما به عنوان جایگزین رویکرد رقابتی مدل سازی LGD ارائه شده است.


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