Following the recent financial crisis, financial regulators have placed a strong emphasis on reducing expectations of government support for banks, and on better managing and assessing risks in the banking system. This thesis considers three current topics in credit risk and the statistical problems that arise there. The first of these topics is expectations of government support in distressed banks. We utilize unique features of the European credit default swap market to find that market expectations of European government support for distressed banks have decreased -- an important development in the credibility of financial reforms. The second topic we treat is the estimation of covariance matrices from the perspective of market risk management. This problem arises, for example, in the central clearing of credit default swaps. We propose several specialized loss functions, and a simple but effective visualization tool to assess estimators. We find that proper regularization significantly improves the performance of dynamic covariance models in estimating portfolio variance. The third topic we consider is estimation risk in the pricing of financial products. When parameters are not known with certainty, a better informed counterparty may strategically pick mispriced products. We discuss how total estimation risk can be minimized approximately. We show how a premium for remaining estimation risk may be determined when one counterparty is better informed than the other, but a market collapse is to be avoided, using a simple example from loan pricing. We illustrate the approach with credit bureau data.

Liu, Weiyang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (p. 111-113). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction and Literature Review --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.1.1 --- Background and Motivating examples --- p.2 / Chapter 1.1.2 --- Basic Concepts --- p.4 / Chapter 1.1.3 --- Outline of the thesis --- p.6 / Chapter 1.2 --- Literature Review --- p.8 / Chapter 2 --- Multi-period Cooperative Re-investment Games: The Basic Model --- p.11 / Chapter 2.1 --- Basic settings and assumptions --- p.11 / Chapter 2.2 --- The problem --- p.13 / Chapter 3 --- Three sub-models and the allocation rule of Sub-Model III --- p.17 / Chapter 3.1 --- Three possible sub-models of the basic model --- p.17 / Chapter 3.1.1 --- Sub-model I --- p.17 / Chapter 3.1.2 --- Sub-model II --- p.18 / Chapter 3.1.3 --- Sub-model III --- p.19 / Chapter 3.2 --- The allocation rule of Sub-model III --- p.19 / Chapter 4 --- A two period example of the revised basic model --- p.25 / Chapter 4.1 --- The two period example with two projects --- p.25 / Chapter 4.2 --- The algorithm for the dual problem --- p.29 / Chapter 5 --- Extensions of the Basic Model --- p.35 / Chapter 5.1 --- The model with stochastic budgets --- p.36 / Chapter 5.2 --- The core of the model with stochastic budgets --- p.39 / Chapter 5.3 --- An example: the two-period case of models with stochastic bud- gets and an algorithm for the dual problem --- p.46 / Chapter 5.4 --- An interesting marginal effect --- p.52 / Chapter 5.5 --- "A Model with stochastic project prices, stochastic returns and stochastic budgets" --- p.54 / Chapter 6 --- Multi-period Re-investment Model with risks --- p.58 / Chapter 6.1 --- The Model with l1 risk measure --- p.58 / Chapter 6.2 --- The Model with risk measure --- p.66 / Chapter 7 --- Numerical Tests --- p.70 / Chapter 7.1 --- The affects from uncertainty changes --- p.71 / Chapter 7.2 --- The affects from budget changes --- p.71 / Chapter 7.3 --- The affects from the budget changes of only one group --- p.71 / Chapter 8 --- Conclusive Remarks --- p.77 / Chapter A --- Original Data and Analysis for Section 7.1 (Partial) --- p.79 / Chapter B --- Data Analysis for Section 7.2 (Partial) --- p.95 / Chapter C --- Data Analysis for Section 7.3 (Partial) --- p.98

Contingent Claim Pricing with Applications to Financial Risk Management By Hua Chen 2008 Committee Chair: Samuel H. Cox and Shaun Wang Major Academic Unit: Department of Risk Management and Insurance This is a multi-essay dissertation designed to explore the contingent claim pricing theory with non-tradable underlying assets, with emphasis on its applications to insurance and risk management. In the first essay, I apply the real option pricing theory and dynamic programming methods to address problems in the area of operational risk management. Particularly, I develop a two-stage model to help firms determine optimal switching triggers in the event of an influenza epidemic. In the second essay, I examine mortality securitization in an incomplete market framework. I build a jump-diffusion process into the original Lee-Carter model and explore alternative model with transitory versus permanent jump effects. I discuss pricing difficulties of the Swiss Re mortality bond (2003) and use the Wang transform to account for correlations of the mortality index over time. In the third essay, I study the valuation of the non-recourse provision in reverse mortgages. I model the various risks embedded in the HECM program and apply the conditional Esscher transform to price the non-recourse provision. I further examine the premium structure of HECM loans and investigate whether insurance premiums are adequate to cover expected claims.

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Financial risk tolerance, an investor’s appetite for financial risk, is an extremely important aspect that needs to be considered when constructing investment portfolios. Evidence as to how risk tolerance should be measured is mixed, with each method having its own strengths and weaknesses. It can be determined both objectively and subjectively, depending on the method used, and can be influenced by a variety of demographic characteristics. Debate as to how certain demographic factors influence risk tolerance is widespread, providing support for further study in this field, particularly from a South African perspective. The purpose of this study was to investigate to what extent demographic factors influenced an individual’s willingness to take on levels of financial risk. The study used an existing, but adapted, subjective questionnaire to determine the risk tolerance levels of a sample of respondents. Respondents were categorised at an aggregate level as either being below or above average risk tolerant. A Binary Logistic model was used to analyse the effect of the independent demographic variables on risk tolerance and it was found that age and gender were significantly related to risk tolerance, whilst there was mixed evidence as to the relationship between risk tolerance and race as well as income. The findings from the study provide new evidence from a wider South African sample and could be used by financial advisors to improve their understanding of risk tolerance and its demographic determinants, as well as companies wishing to align their employees’ risk profiles with the overall company risk profile, as examples. / Thesis (M.Com.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.

We propose a systematic framework for designing adaptive trading strategies that minimize both the mean and the variance of the execution costs. This is achieved by diversifying risk over sequential decisions in discrete time. By incorporating previous trading performance as a state variable, the framework can dynamically adjust the risk-aversion level for future trading. This incorporation also allows the framework to solve the mean-variance problems for different risk aversion factors all at once. After developing this framework, it is then applied to solve three algorithmic trading problems. The first two are trade scheduling problems, which address how to split a large order into sequential small orders in order to best approximate a target price – in our case, either the arrival price, or the Volume-Weighed-Average-Price (VWAP). The third problem is one of optimal execution of the resulting small orders by submitting market and limit orders. Unlike the tradition in both academia and industry of treating the scheduling and order placement problems separately, our approach treats them together and solves them simultaneously. In out-of-sample tests, this unified strategy consistently outperforms strategies that treat the two problems separately.

Hedge funds report performance information voluntarily. When they stop reporting they are transferred from the "live" pool of funds to the "defunct" pool. Consequently, liquidated funds constitute a subset of the defunct pool. I present models of hedge fund survival, attrition, and survivorship bias based on liquidation alone. This refines estimates of predictor variables in models of survival, leads to attrition rates of hedge funds to be roughly one half those previously thought, and produces larger estimates of survivorship bias. Survival models based on liquidated funds only, lead to an increase in survival time of 50 to 100 percent relative to survival based on all defunct funds. / In addition to refining estimates of survival time, it is useful to examine how the double fee structure of hedge funds and Commodity Trading Advisors (CTA) affects the incentives of their managers. Young CTAs are usually very small --- they hold few financial assets --- and may not meet their operating expenses with their management fee alone, so their incentive is to take on risk and post good returns. As they grow, their incentive to take on risk diminishes. CTAs in their fifth year diminish their volatility by 25 percent relative to their first year, and diminish returns by 70 percent. We find CTAs to behave more like indexers as they grow, concerned with more with capital preservation than asset management. / Operational risk is a major cause of hedge fund and CTA liquidation. In the banking industry, regulators have called upon institutions to develop models for measuring capital charge for operational losses, and to subject these models to stress testing. Losses are found to be inversely related to GDP growth, and positively related to unemployment. Since losses are thus cyclical, one way to stress test models is to calculate capital charge during good and bad economic regimes. We find loss distributions to have thicker tails during bad regimes. One implication is that banks will likely need to increase their capital charge when economic conditions deteriorate.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 95-101).

M.Phil. / The premise of this research study was to study the phenomenon of Enterprise Risk Management (ERM) in order to understand the processes and practices of risk management within First National Bank (FNB). Risk management became a favourite topic for discussion in the aftermath of the Global Financial Crisis (GFC). Some analysts, chief financial officers and observers have noted that risk management is to blame for the economic recession and myriad of bank failures that ensue. However, the intention of this research study was not to analyse the GFC or to devote itself entirely to defend risk management and risk managers.

M.Com. (Computer Auditing) / This dissertation aims to explore the entity characteristics associated with the implementation of the board-level stand-alone risk management committee (RMC) in South Africa. We developed a battery of econometric models based on triangulation of corporate governance theories which linked an entity’s decision to set up a separate risk management committee (RMC) in its board structures as a dependent variable and a host of entity-specific factors as independent variables. Data collected from audited annual reports of 181 JSE-listed non-financial entities was analysed using logistics regression estimation procedures. Our results show a strong positive relationship between the likelihood that an entity would establish a separate RMC, on the one hand, and board independence, board size, entity size, and industry type, on the other. Our study fails to find support for the hypothesis that an entity’s characteristics – such as the independence of the board chairman, the use of Big Four audit firms, financial reporting risks, and levels of financial leverage – do influence an entity’s decision to form a separate RMC. Our findings emphasize the role that information asymmetry between executive and non-executive directors, agency cost and potential damage to reputation capital of directors; diversity in background, expertise, and skills of directors; economies of scale in absorbing RMC costs; and industry-specific institutions and norms play in an entity’s decision to form a separate RMC. The implication of our findings is that policy-makers should consider the size and composition of boards and also take cognizance of entity size and industry-specific idiosyncrasies in setting recommended corporate governance practices.