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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Defaulted retail mortgage loans as a percentage of retail mortgage loans and advances averaged 9 percent over 2010 as reported in the SARB Bank Supervision Annual report. Banks are in the business of risk taking and as a result need to constantly evaluate and review credit risk management to attain sustained profitability. In credit risk modelling, default risk is associated with client-specific factors particularly the client’s credit rating. However, Brent, Kelly, Lindsey-Taliefero, and Price (2011), have shown that variation in mortgage delinquencies reflect changes in general macroeconomic conditions. This study aims to provide evidence of whether macroeconomic factors such as the house price index, CPI, credit growth, debt to income ratio, prime interest rates, and unemployment, are key drivers of residential mortgage delinquencies and default in South Africa. In this study, data from an undisclosed bank is used to estimate three models that are supposed to capture the influence of several macroeconomic variables on 30 day, 60 day, and 90 day delinquency rates over the 2006-2010 period. In order to eliminate the potential bias introduced by those observations, a fourth model was estimated using aggregated banking industry published by the SARB. However, due to data constraints, only the severe mortgage delinquency state, that is the 90 day delinquency rate was modelled using this aggregate data. The SARB sample covers the period between 2008 and 2010. The choice of the date 2008 coincides with the introduction of the Basel 2 regulatory framework. Prior to 2008, the big four South African banks were governed by the Basel 1 framework, and measured their credit risk using the so-called Standardised Approach which has different loan categories and different default definitions compared to the Basel 2 Advanced Internal Ratings Approach adopted in 2008. The findings suggest that the two samples (i.e. the data from the individual bank and the SARB data) imply different explanatory macroeconomic factors. Prime interest rates were found to be the only important variable in determining 30 day and 60 day delinquency rates for the individual bank. The house price index, CPI, credit growth, and prime interest rates were found to be the main determinants of the 90 day delinquency rates for the undisclosed bank, while the house price index, CPI, and credit growth, determine the 90 day delinquency rates for the big four banks.

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.

Thesis advisor: Utku Unver / This dissertation consists of three essays in microeconomic theory: two focusing on insurance theory and one on matching theory. The first chapter is concerned with catastrophe insurance. Motivated by the aftermath of hurricane Katrina, it studies a strategic model of catastrophe insurance in which consumers know that they may not get reimbursed if too many other people file claims at the same time. The model predicts that the demand for catastrophe insurance can ``bend backwards'' to zero, resulting in multiple equilibria and especially in market failure, which is always an equilibrium. This shows that a catastrophe market can fail entirely due to demand-driven reasons, a result new to the literature. The model suggests that pricing is key for the credibility of catastrophe insurers: instead of increasing demand, price cuts may backfire and instead cause a ``race to the bottom.'' However, small amounts of extra liquidity can restore the system to stable equilibrium, highlighting the importance of a functioning reinsurance market for large risks. These results remain robust both for expected utility consumer preferences and for expected utility's most popular alternative, rank-dependent expected utility. The second chapter develops a model of quality differentiation in insurance markets, focusing on two of their specific features: the fact that costs are uncertain, and the fact that firms are averse to risk. Cornerstone models of price competition predict that firms specialize in products of different quality (differentiate their products) as a way of softening price competition. However, real-world insurance markets feature very little differentiation. This chapter offers an explanation to this phenomenon by showing that cost uncertainty fundamentally alters the nature of price competition among risk-averse firms by creating a drive against differentiation. This force becomes particularly pronounced when consumers are picky about quality, and is capable of reversing standard results, leading to minimum differentiation instead. The chapter concludes with a study of how the costs of quality affect differentiation by considering two benchmark cases: when quality is costless and when quality costs are convex (quadratic). The third chapter focuses on the theory of two-sided matching. Its main topic are inefficiencies that arise when agent preferences permit indifferences. It is well-known that two-sided matching under weak preferences can result in matchings that are stable, but not Pareto efficient, which creates bad incentives for inefficiently matched agents to stay together. In this chapter I show that in one-to-one matching with weak preferences, the fraction of inefficiently matched agents decreases with market size if agents are sufficiently diverse; in particular, the proportion of agents who can Pareto improve in a randomly chosen stable matching approaches zero when the number of agents goes to infinity. This result shows that the relative degree of the inefficiency vanishes in sufficiently large markets, but this does not provide a "cure-all'' solution in absolute terms, because inefficient individuals remain even when their fraction is vanishing. Agent diversity is represented by the diversity of each person's preferences, which are assumed randomly drawn, i.i.d. from the set of all possible weak preferences. To demonstrate its main result, the chapter relies on the combinatorial properties of random weak preferences. / Thesis (PhD) — Boston College, 2012. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

Today's mortgage industry is constantly changing, with adjustable rate mortgages (ARM), loans originated to the so-called "subprime" market, and volatile interest rates. Amid the changes and controversy, lenders continue to originate loans because the interest paid over the loan lifetime is profitable. Measuring the profitability of those loans, along with return on investment to the lender is assessed using Actuarial Present Value (APV), which incorporates the uncertainty that exists in the mortgage industry today, with many loans defaulting and prepaying. The hazard function, or instantaneous failure rate, is used as a measure of probability of failure to make a payment. Using a logit model, the default and prepayment risks are estimated as a function of interest rate. The "optimal" interest rate can be found where the profitability is maximized to the lender.

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Thesis (MTech (Cost and Management Accounting))--Cape Peninsula University of Technology, 2019 / The risk that borrowers may not fulfil borrowing obligation presents credit owners (lenders) with a default risk management opportunity to maximize risk-adjusted rate of return and maintain minimum exposure to default associated cost. This study investigated respondents' perception of the cost of credit default and examines requirements for default risk management (ORM) in the vehicle finance industry in South Africa. It is noted that with increased level of consumer indebtedness, an unstable economy, and high unemployment, vehicle financing faces a higher probability of default from borrowers. This descriptive investigation utilised both the quantitative and qualitative approaches using the survey method to collect data from 381 purposive, randomly selected respondents who are vehicle finance customers in South Africa; Cape Town specifically. Data collection took place in the Western Cape over a nine months period, utilising personal interview, and emails to administer open-ended questionnaires for credit managers and close-ended questionnaires, for the vehicle finances' customers, as data collection instrument. Responses received were codified and quantitative data was analysed using the Statistical Packages for Social Sciences (SPSS version 25) while qualitative data was analysed using the content analysis of percentage of word similarities. The study found mixed and variable respondents' perception of the cost of credit default. In conclusion, it is perceived that in South Africa the cost of credit would become more costly with credit default. It can be recommended that a default risk management intervention could be applied to mitigate the risk of credit default within the context of unified credit assessment policy of South Africa.

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