Parameterizing Credit Risk Models with Rating Data
نویسندگان
چکیده
منابع مشابه
Credit Rating Dynamics and Markov Mixture Models∗
Despite mounting evidence to the contrary, credit migration matrices, used in many credit risk and pricing applications, are typically assumed to be generated by a simple Markov process. Based on empirical evidence we propose a parsimonious model that is a mixture of (two) Markov chains, where the mixing is on the speed of movement among credit ratings. We estimate this model using credit ratin...
متن کاملCorporate payments networks and credit risk rating
Understanding the structure of interactions between corporate firms is critical to identify risk concentration and the possible pathways of propagation of financial distress. In this paper we consider the interaction due to payments and, by investigating a large proprietary dataset of Italian firms, we characterize the topological properties of the payment network. We then focus on the relation...
متن کاملCorporate Credit Rating using Multiclass Classification Models with order Information
Corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has been one of the attractive research topics in the literature. In recent years, multiclass classification models such as artificial neural network (ANN) or multiclass support vector machine (MSVM) have become a very appealing machine learning approaches due to their good performance. However, mos...
متن کاملPredicting Credit Rating and Credit Rating Changes: A New Approach
In this paper, we propose a hazard rate model for studying credit rating and credit rating changes. Theoretically the hazard rate model is more appropriate than the previous static models. Yet it is difficult to estimate hazard rate model, especially when the covariates are time-varying. This paper extends the results of Shumway(2001) and shows that a multiple-state hazard rate model can be est...
متن کاملCredit Risk Scoring Models
Credit scoring models play a fundamental role in the risk management practice at most banks. They are used to quantify credit risk at counterparty or transaction level in the different phases of the credit cycle (e.g. application, behavioural, collection models). The credit score empowers users to make quick decisions or even to automate decisions and this is extremely desirable when banks are ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2001
ISSN: 1556-5068
DOI: 10.2139/ssrn.249294