Thesis (doctoral)--Universitẗ Bern.

The master thesis deals with the advanced methods for estimating credit risk parameters from market prices: probability of default (PD) and loss given default (LGD). Precise evaluation of these parameters is important not only for banks to calculate their regulatory capital but also for investors to price risky bonds and credit derivatives. We provide forward looking reduced-form analytical method for calculation of PD and LGD of corporate defaultable bonds based on their quoted market prices, prices of equivalent risk-free bonds and quoted credit default swap spreads of the issuer of these bonds. This is reversed to most of the studies on credit risk modeling, as aim is not to price instruments based on estimated credit risk parameters, but to calculate these parameters based on the available market prices. Furthermore, compared to other studies, the LGD parameter is assumed to be endogenous and we provide the method for its simultaneous calculation with the probability of default. Finally, using developed methods, we estimate implied PD and LGD for five European banks assuming that the risk is priced correctly by other investors and the markets are efficient. JEL Classification: C02, C63, G13, G33 Keywords: credit risk, loss given default, probability of default, credit default swap Author's...

In the recent years, the banks pay more attention to the importance of the Credit Risk. Thus, more research institutions start to focus on the problem of the Credit Risk. And the KMV company is one of the most famous institutions. The paper uses Expected Default Frequency Model developed by KMV to value the expected default probability of Taiwan listed company, and compared two ways, Financial Statement Analysis and KMV Option Model, to value EDF, and try to understand the distribution of the EDF of Taiwan listed company.

債券信用風險的規避,一直以來是學者有興趣研究的課題,本篇研究以HJM模型去衡量信用風險, 透過市場資料的輸入,去衡量違約程度,並對信用風險相關之衍生性金融商品作出適當的評價,以求規避信用風險. / Abstract In this study, we combine credit valuation approaches developed by Jarrow＆Turnbull (1995)、Duffie＆Singleton (1999)、Schonbucher (2000) to execute a default pricing methodology under H.J.M default intensity structure. We can use market data such as defaultable yield rate and its volatility to measure credit risk, however, because of the close form in our model, the comparative static analysis for parameters can be done. At last, after introducing the survivor probability measure, we can extend to price default related derivatives.

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This thesis presents ways how investors can construct optimal portfolios on on-line peer-to-peer lending platforms. Thesis uses standard portfolio theory and unique dataset from Lending Club platform of over 886 thousand loans issued since 2008 till the end of 2015. Firstly, this thesis shows that there is a non- zero covariance between loans from different credit grades and it is necessary to include it in portfolio management optimization. Secondly, the thesis with the help of a logistic regression identifies loan default determinants. Using the default predictions, the portfolio performance can be improved significantly. Thirdly, the thesis simulates diversification benefits stemming from investing into multiple loans. Powered by TCPDF (www.tcpdf.org)

Microfinance can play an important role in the growth of an economy. Thus, we are interested in developing models that could simply estimate the probability of default of a customer and the probability of the microfinance being at risk based on probability of default of customers.

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Thesis (Ph. D.)--University of Chicago, Dept. of Economics, June 2001. / Includes bibliographical references. Also available on the Internet.

This thesis studies the impact of geographic mobility on the decision of a household to whether to buy or to rent a house, and sheds light on the efficiency of mortgage default prevention policies. The first chapter provides an introduction and an overview of the ongoing policy debates on homeownership and mortgage terms. In the second and third chapters, I study the housing tenure decision in the context of a life cycle model with uninsurable individual income risk, plausibly calibrated to match key features of the U.S. housing market. I find that the relatively low ownership rate of young households is mainly explained by their high geographic mobility. Downpayment constraints have minor quantitative implications on ownership rates, except for old households. I also find that idiosyncratic earnings uncertainty has a significant impact on ownership rates. Based on these results, I argue that the long term increase in ownership rates observed over the period 1993-2009 was not necessarily due to mortgage market innovations and the relaxation of downpayment requirements, as is often argued. Instead, it was simply an implication of U.S. demographic evolution, most notably the decline in interstate migration and, less importantly, population aging. Finally, in Chapter 4, I study the impact of the relaxation of downpayment requirement on homeownership and default risk. Given its quantitative success in matching the U.S. homeownership curve, my model represents a reasonable benchmark to asses the efficiency of mortgage default prevention policies. I find that both income and mobility are the main trigger factors for default decisions. In fact, households with a higher mobility (ie. young households) rate are more likely to default. According to the welfare analysis, I suggest that policymakers include a minimum downpayment requirement of 9.5% in the new definition of the Qualified Residential Mortgage. This number should, however, be viewed with some caution, since I focus on a steady state economy, in which house prices are constant. In fact, the house price represents an important factor influencing the default rate. Potentially, the optimal minimum downpayment requirement should be set at higher value than 9.5%. / Thesis (Ph.D, Economics) -- Queen's University, 2014-06-24 19:58:17.324