Li Chin Pang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 64-66). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Structural Models of Credit Risk --- p.7 / Chapter 2.1 --- Barrier-Independent Models --- p.8 / Chapter 2.2 --- Barrier-Dependent Models --- p.9 / Chapter 2.3 --- Empirical Literature --- p.10 / Chapter 3 --- Jump-Diffusion Models --- p.13 / Chapter 3.1 --- Analytical Option Pricing Formula --- p.14 / Chapter 3.1.1 --- The Jump-Diffusion Model of Merton --- p.14 / Chapter 3.1.2 --- The Jump-Diffusion Model of Kou --- p.15 / Chapter 3.2 --- Simulation for Options --- p.19 / Chapter 3.2.1 --- Simulation for Barrier-Independent Options --- p.19 / Chapter 3.2.2 --- Brownian Bridge Simulation for DOC Option --- p.20 / Chapter 4 --- Likelihood Function for Equity Returns --- p.24 / Chapter 4.1 --- Likelihood Function on Equity Return --- p.26 / Chapter 4.2 --- Degeneracy Problem of Likelihood Function --- p.27 / Chapter 5 --- The Proposed Framework --- p.31 / Chapter 5.1 --- Penalized Likelihood Estimation --- p.31 / Chapter 5.2 --- Expectation-Maximization Algorithm --- p.36 / Chapter 5.3 --- The MJD Structural Model --- p.41 / Chapter 5.4 --- The K<JD Structural Model --- p.43 / Chapter 5.5 --- Computation of the E-step --- p.47 / Chapter 6 --- Performance of Estimation --- p.49 / Chapter 6.1 --- Simulation Checks --- p.49 / Chapter 6.2 --- Empirical Performance --- p.55 / Chapter 6.2.1 --- Bond Selection --- p.55 / Chapter 6.2.2 --- Empirical Results --- p.57 / Chapter 7 --- Conclusion --- p.62 / Bibliography --- p.64

Not available / text

This thesis studies the impacts of credit risk, or the risk of default, on the pricing of fixed income securities. It consists of three essays. The first essay extends the classical corporate debt pricing model in Merton (1974) to incorporate stochastic volatility (SV) in the underlying firm asset value and derive a closed-form solution for the price of corporate bond. Simulation results show that the SV specification for firm asset value greatly increases the resulting credit spread levels. Therefore, the SV model addresses one major deficiency of the Merton-type models: namely, at short maturities the Merton model is unable to generate credit spreads high enough to be compatible with those observed in the market. In the second essay, we develop a two-factor affine model for the credit spreads on corporate bonds. The first factor can be interpreted as the level of the spread, and the second factor is the volatility of the spread. Our empirical results show that the model is successful at fitting actual corporate bond credit spreads. In addition, key properties of actual credit spreads are better captured by the model. Finally, the third essay proposes a model of interest rate swap spreads. The model accommodates both the default risk inherent in swap contracts and the liquidity difference between the swap and Treasury markets. The default risk and liquidity components of swap spreads are found to behave very differently: first, the default risk component is positively related to the riskless interest rate, whereas the liquidity component is negatively correlated with the riskless interest rate; second, although default risk accounts for the largest share of the levels of swap spreads, the liquidity component is much more volatile; and finally, while the default risk component has been historically positive, the liquidity component was negative for much of the 1990s and has become positive since the financial market turmoil in 1998.

No description available.

published_or_final_version / Mathematics / Master / Master of Philosophy

Li Ka-leung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 85-88). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Structural models of credit risk --- p.9 / Chapter 2.1 --- The original Merton model --- p.10 / Chapter 2.2 --- The extended Merton model --- p.11 / Chapter 2.3 --- The Black and Cox model --- p.12 / Chapter 2.4 --- The LS model --- p.14 / Chapter 2.5 --- The CDG model --- p.16 / Chapter 2.6 --- Comments on structural models --- p.19 / Chapter 3 --- Proxies and their implications --- p.20 / Chapter 3.1 --- Reviews of the EHH's empirical studies --- p.20 / Chapter 3.2 --- The proxy for market values of firms --- p.23 / Chapter 3.2.1 --- Zero coupon bonds under the Merton model --- p.23 / Chapter 3.2.2 --- Coupon bearing bonds under the extended Merton model --- p.25 / Chapter 3.2.3 --- Zero coupon bonds under the LS model --- p.26 / Chapter 3.2.4 --- Coupon bearing bonds under the LS model --- p.28 / Chapter 3.3 --- Implications of other proxies --- p.29 / Chapter 4 --- Maximum Likelihood Estimation --- p.33 / Chapter 4.1 --- The MLE approach for the Merton model --- p.33 / Chapter 4.2 --- The MLE approach for the barrier dependent models --- p.35 / Chapter 4.3 --- Survivorship consideration --- p.36 / Chapter 4.4 --- Simulation tests --- p.37 / Chapter 4.5 --- Simulation results --- p.39 / Chapter 4.5.1 --- Simulation results for the Merton model --- p.39 / Chapter 4.5.2 --- Simulation results for the LS model --- p.42 / Chapter 5 --- Empirical test --- p.47 / Chapter 5.1 --- Criteria of bond selection --- p.47 / Chapter 5.2 --- Parameters of models --- p.51 / Chapter 5.2.1 --- Firm specific parameters --- p.51 / Chapter 5.2.2 --- Interest rate parameters --- p.54 / Chapter 5.2.3 --- Stationary leverage process parameters --- p.55 / Chapter 5.2.4 --- Bond specific parameters --- p.57 / Chapter 5.3 --- Empirical results --- p.58 / Chapter 5.3.1 --- Empirical results for the Merton model --- p.59 / Chapter 5.3.2 --- Empirical results for the LS model --- p.66 / Chapter 5.3.3 --- Empirical results for the CDG model --- p.71 / Chapter 6 --- Conclusion --- p.77 / Appendix --- p.80 / Chapter A.1 --- Appendix 1 --- p.80 / Chapter A.2 --- Appendix 2 --- p.82 / Chapter A.3 --- Appendix 3 --- p.84 / Bibliography --- p.85

The problem of credit rationing/borrowing constraint has recently received considerable attention. Individuals who are denied any credit by a financial institution, or who find it difficult to borrow against future incomes, are said to be credit rationed or borrowing constrained in the credit markets. This dissertation tries to identify the circumstances under which individuals may be rationed (or not), and analyses the actions undertaken to overcome future constraints. Chapter 2 analyses the problem of credit rationing as it arises in equilibrium, when borrowers differ with respect to their demands for loans. It is shown that if the principal can costlessly observe the agent’s type, then (i) the agents who meet the collateral requirements are not rationed in the sense of Stiglitz-Weiss (1981), (ii) the agents who do not meet the collateral requirements are rationed in the sense of Jaffee-Russell (1976). We further show that if the principal cannot distinguish between different agents, then the previous rationing results still hold in the second best contract which is pooling : agents of different types pick the same contract. Chapter 3 analyses the problem of credit rationing as it emerges in a dynamic setting, when a renegotiation of the original contract may be undertaken. It is conjectured that (i) the principal uses the information revealed about an agent’s type at the time of first repayment, to design future contracts, (ii) the agents who show consistently honest behavior are never rationed, (iii) the agents who showed dishonest behavior impose a negative externality on the agents who were honest; they are rationed in later periods. Finally, in chapter 3, we analyse the role of an exogenously imposed borrowing constraint prompting the individuals to change their life-cycle decisions. This chapter provides an explicit link between human and non-human wealth by making income endogenous through investment in human capital. The chapter also discusses the econometric aspects of the problem: the possible empirical work that can be undertaken in the future using a micro data set. / Ph. D.

Not available

Not available / text