Essays on financial analysis: Capital structure, dynamic dependence and extreme loss modeling
El-Gamal, Mahmoud A.
Doctor of Philosophy
This dissertation contains three essays concerning two broad areas, namely, optimal capital structure and risky assets modeling. In the first paper, we study corporate debt values, capital structure, and the term structure of interest rates in a unified framework. We employ numerical techniques to compute the firm's optimal capital structure and the value of its long-term risky debt with call option embedded and yield spreads when the value of the firm's unleveraged assets and the instantaneous default-free interest rate are risk factors. Debt and leveraged firm value are thus explicitly linked to properties of the firm's unleveraged assets, the term structure of default-free interest rates, taxes, bankruptcy costs, payout rates, and bond covenants. The results clarify the relationship between a firm's capital structure and movements in the term structure and other important aspects of the capital structure decision. In the second chapter, we propose a dynamic copula modeling framework that allows copula association parameters to change with time and macroeconomic variables. We find empirical evidence that nominal interest rate and price index for traded goods differentials between two countries have significant impact on the co-movement of foreign exchange rates. Our Pearson-type goodness-of-fit test has the power to reject constant and time-varying copula modeling approaches at the 95% confidence level. In the third chapter, a new method for solving sample size problem in probabilistic risk assessment has been developed. We propose the use of Bayesian power prior distributions to improve extreme value theory and provide reliable estimates of Value-at-Risk (VaR) and expected shortfall. The Bayesian Monte Carlo Markov chain computational scheme with power prior distributions allows us to properly incorporate historical data and borrow strength and information from related sources to current study.