Default probability

Topic 11A  Defaultadjusted bond return. After completing this topic, you should be able to: Use transition matrices to compute multiperiod default probabilities, understand the difference between a bond’s YTM and defaultadjusted expected return, compute defaultadjusted expected bond return given a transition matrix and recovery rate.
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In banking, especially in risk management, portfolio management, and structured ﬁnance, solid quantitative knowhow becomes more and more important. We had a twofold intention when writing this book: First, this book is designed to help mathematicians and physicists leaving the academic world and starting a profession as risk or portfolio managers to get quick access to the world of credit risk management. Second, our book is aimed at being helpful to risk managers looking for a more quantitative approach to credit risk. ...
285p vigro23 24082012 107 51 Download

n my "Word of Greeting" of the first edition of this book which was dedicated to Günter Dufey, I pointed out that I appreciate Günter Dufey as someone who builds bridges between Germany and the United States. Meanwhile, almost 5 years have gone by. Günter Dufey's significance as an academic intermediary between the continents has even increased since then. Due to his efforts, the cooperation between high ranked U.S. business schools and the WHU  Otto Beisheim Hochschule in Germany have been intensified. The joint summer MBA program on the WHU campus is attended by 45 U.S.
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Luận văn sử dụng phương pháp chọn mẫu ngẫu nhiên để thu thập cơ sở dữ liệu 258 khách hàng doanh nghiệp có quan hệ vay vốn tại Habubank trong khoảng thời gian từ năm 2008 đến năm 2010. Sau đó, sẽ áp dụng phương pháp phân tích thống kê mô tả để phân tích đặc điểm của mẫu, phương pháp so sánh, phương pháp Z score của tác giả Atltman có sự điều chỉnh phù hợp với môi trường của ngành ngân hàng Việt nam để ước lượng xác suất default của khách hàng....
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Forecasting credit portfolio risk poses a challenge for the banking industry. One important goal of modern credit portfolio models is the forecast of the future credit risk given the information which is available at the point of time the forecast is made. Thus, the discussion paper “Forecasting Credit Portfolio Risk“ proposes a dynamic concept for the forecast of the risk parameters default probabilities and default correlations.
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In the present paper we use a model to forecast default probabilities and estimate default correlations based on the threshold model described above. The default probability measures the probability of an obligor’s assets falling short of a threshold. In addition, asset correlations are modeled as a measure of comovement of the asset values of two obligors. Default correlations can then be derived analytically.
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The model allows default probabilities to be forecasted for individual borrowers and to estimate correlations between those borrowers simultaneously. We show that asset and default correlations depend on the point in time calibration of the default probabilities. In addition a simultaneous estimation eases the validation of default probabilities. Thus, default probabilities and correlations should never be derived separately from each other.
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We also model the contagion process in a relatively mechanical fashion, holding balance sheets and the size and structure of interbank linkages constant as default propagates through the system. Arguably, in normal times in developed nancial systems, banks are sufciently robust that very minor variations in their default probabilities do not affect the decision of whether or not to lend to them in interbank markets.
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The intuition underpinning these results is straightforward. In a highly connected system, the counterparty losses of a failing institution can be more widely dispersed to, and absorbed by, other entities. So increased connectivity and risk sharing may lower the probability of contagious default. But, conditional on the failure of one institution triggering contagious defaults, a high number of nancial linkages also increases the potential for contagion to spread more widely.
390p mebachano 01022013 18 4 Download

The pricing of creditsensitive bonds, that is, bonds which have a significant probability of default, is an issue of increasing academic and practical importance. The recent practice in financial markets has been to issue high yield corporate bonds that are a hybrid of equity and riskfree debt. Also, to an extent, most corporate bonds are creditsensitive instruments, simply because of the limited liability of the issuing enterprise. In this paper, we suggest and implement a model for the pricing of options on creditsensitive bonds.
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In the Basel II framework, external ratings are used for the purpose of enhancing the risk sensitivity of the framework, for example, by being incorporated into assessments of the credit quality of an exposure or creditworthiness of a counterparty – and thus the imposition of capital requirements. External ratings are primarily used under the standardised approach for credit risk, 10 but also to riskweight securitisations exposures.
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This article examines the pricing of catastrophe risk bonds. Catastrophe risk cannot be hedged by traditional securities. Therefore, the pricing of catastrophe risk bonds requires an incomplete markets setting, and this creates special difficulties in the pricing methodology. The authors briefly discuss the theory of equilibrium pricing and its relationship to the standard arbitragefree valuation framework. Equilibrium pricing theory is used to develop a pricing method based on a model of the term structure of interest rates and a probability structure for the catastrophe risk.
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THE credit standing of an applicant for a personal loan is investigated intensively because it indicates, within reason able limits, the likelihood of repayment. It should not be assumed, however, that a bank officer can foretell with cer tainty how faithfully a borrower will meet his obligations; few applicants have economic prospects so bad that there is not some small chance of repayment, and few are so well sit uated that there is not some possibility of delinquency or even default. The selection of borrowers must therefore rest on probabilities.
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This paper analyses the determinants of the probability of default (PD) of bank loans. We focus the discussion on a limited set of determinants (collateral, type of lender and bankborrower relationship) while controlling for the other explanatory variables such as the macroeconomic environment, characteristics of the borrower (industry and region) and of the loan (instrument, currency, maturity and size). We try to discern if riskier borrowers are asked to pledge more collateral or if, on the other hand, low risk borrowers are those who have collateralised loans1.
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Similarly, it might be possible that the relation between collateral and the probability of default was different depending on the type of lender. During the time period studied, savings banks have expanded their activities outside their traditional geographic markets and therefore it can be expected that they face a more severe adverse selection problem than banks which have grown mostly within their traditional markets. If this was the case among savings banks, collateral might be used to solve the problem raised by the hidden information situation.
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The intuition underpinning these results is as follows. In a highly connected system, the counterparty losses of a failing institution can be more widely dispersed to, and absorbed by, other entities. So increased connectivity and risk sharing may lower the probability of contagious default. But, conditional on the failure of one institution triggering contagious defaults, a high number of nancial linkages also increases the potential for contagion to spread more widely.
54p mebachano 01022013 17 2 Download

In what follows, we construct a simple nancial system involving entities with interlocking balance sheets and use these techniques to model the spread and probability of contagious default following an unexpected shock, analytically and numerically. Unlike the generic, undirected graph model of Watts (2002), our model provides an explicit characterisation of balance sheets, making clear the direction of claims and obligations linking nancial institutions. It also includes asset price interactions with balance sheets, allowing the effects of assetside contagion to be clearly delineated.
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