Modeling Credit Aggregates PDF Download

Author: Sylvia Kaufmann
Publisher:
ISBN:
Category : Credit
Languages : en
Pages : 68

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Author: Leslie Milton
Publisher:
ISBN:
Category : Credit
Languages : en
Pages : 56

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Author: Spencer Dale
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
The paper presents a theoretical model of how banks and the non-bank private sector respond to changes in monetary policy. Unlike many textbook models in which banks play no active role, the banking sector is recognised here as playing a key part in transmitting changes in monetary policy to the real economy.In a conventional IS/LM model the impact of a change in monetary policy arises from the response of expenditure to changes in interest rates (the quot;monetaryquot; channel). If, however, bank and non-bank sources of credit are not perfect substitutes (for example because some borrowers have only limited access to capital markets) then changes in monetary policy could also have an effect through their impact on the availability or the relative price of bank credit (a quot;creditquot; channel). The paper sets out the conditions under which this credit channel reinforces or weakens the impact of changes in monetary policy on the behaviour of the non-bank private sector.One example of the case where the credit channel could weaken the impact of changes in monetary policy would be where banks do not pass on changes in official interest rates fully or immediately to some of their customers. In this context the paper acknowledges the results of the two Bank studies of bank lending to small businesses.

Author: Mr.Fabian Valencia
Publisher: International Monetary Fund
ISBN: 1475513933
Category : Business & Economics
Languages : en
Pages : 26

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Book Description
Recent studies show that uncertainty shocks have quantitatively important effects on the real economy. This paper examines one particular channel at work: the supply of credit. It presents a model in which a bank, even if managed by risk-neutral shareholders and subject to limited liability, can exhibit self-insurance, and thus loan supply contracts when uncertainty increases. This prediction is tested with the universe of U.S. commercial banks over the period 1984-2010. Identification of credit supply is achieved by looking at the differential response of banks according to their level of capitalization. Consistent with the theoretical predictions, increases in uncertainty reduce the supply of credit, more so for banks with lower levels of capitalization. These results are weaker for large banks, and are robust to controlling for the lending and capital channels of monetary policy, to different measures of uncertainty, and to breaking the dataset in subsamples. Quantitatively, uncertainty shocks are almost as important as monetary policy ones with regards to the effects on the supply of credit.

Author: Elizabeth Mays
Publisher: Global Professional Publishi
ISBN: 9781888998382
Category : Business & Economics
Languages : en
Pages : 280

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Covers: � Implementing an application scoring system � Behavior modeling to manage your portfolio � Incorporating economic factors � Statistical techniques for choosing the optimal credit risk model � How to set cutoffs and override rules � Modeling for the sub-prime market � How to evaluate and monitor credit risk models This is an indispensable guide for credit professionals and risk managers who want to understand and implement modeling techniques for increased profitability. In this one-of-a-kind text, experts in credit risk provide a step-by-step guide to building and implementing models both for evaluating applications and managing existing portfolios.

Author: Frédéric Vrins
Publisher: MDPI
ISBN: 3039287605
Category : Business & Economics
Languages : en
Pages : 190

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Book Description
Credit risk remains one of the major risks faced by most financial and credit institutions. It is deeply connected to the real economy due to the systemic nature of some banks, but also because well-managed lending facilities are key for wealth creation and technological innovation. This book is a collection of innovative papers in the field of credit risk management. Besides the probability of default (PD), the major driver of credit risk is the loss given default (LGD). In spite of its central importance, LGD modeling remains largely unexplored in the academic literature. This book proposes three contributions in the field. Ye & Bellotti exploit a large private dataset featuring non-performing loans to design a beta mixture model. Their model can be used to improve recovery rate forecasts and, therefore, to enhance capital requirement mechanisms. François uses instead the price of defaultable instruments to infer the determinants of market-implied recovery rates and finds that macroeconomic and long-term issuer specific factors are the main determinants of market-implied LGDs. Cheng & Cirillo address the problem of modeling the dependency between PD and LGD using an original, urn-based statistical model. Fadina & Schmidt propose an improvement of intensity-based default models by accounting for ambiguity around both the intensity process and the recovery rate. Another topic deserving more attention is trade credit, which consists of the supplier providing credit facilities to his customers. Whereas this is likely to stimulate exchanges in general, it also magnifies credit risk. This is a difficult problem that remains largely unexplored. Kanapickiene & Spicas propose a simple but yet practical model to assess trade credit risk associated with SMEs and microenterprises operating in Lithuania. Another topical area in credit risk is counterparty risk and all other adjustments (such as liquidity and capital adjustments), known as XVA. Chataignier & Crépey propose a genetic algorithm to compress CVA and to obtain affordable incremental figures. Anagnostou & Kandhai introduce a hidden Markov model to simulate exchange rate scenarios for counterparty risk. Eventually, Boursicot et al. analyzes CoCo bonds, and find that they reduce the total cost of debt, which is positive for shareholders. In a nutshell, all the featured papers contribute to shedding light on various aspects of credit risk management that have, so far, largely remained unexplored.

Author: Colin Chen
Publisher: Springer Nature
ISBN: 3031525426
Category :
Languages : en
Pages : 404

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Author: Julio R. Escandón
Publisher:
ISBN:
Category : Credit
Languages : en
Pages : 56

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Author: David B. White
Publisher:
ISBN:
Category : Business cycles
Languages : en
Pages : 64

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Book Description

Author: Christian Bluhm
Publisher: CRC Press
ISBN: 1584889934
Category : Business & Economics
Languages : en
Pages : 386

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Book Description
Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations. While continuing to focus on common mathematical approaches to model credit portfolios, Introduction to Credit Risk Modelin