Research thesis and much of the associated MATLAB code, data, and reference materials used.
Thesis completed as partial requirement for my masters degree in Financial Mathematics, from the University of Queensland, Australia, completed 2008.
The Effectiveness of Structural Bond Pricing Models with Maximum Likelihood Estimation of Asset Dynamics Parameters
Increasingly, companies issue bonds when raising funds to finance their operations. Such bonds are subject to credit risk, that is, the risk that borrowers will be unable to repay their loans. How to fairly price this risk is still unresolved.
Option pricing theory developed in the 1970’s by Black, Scholes and Merton lead to a new analytical approach, ‘contingent claims analysis’, and the Merton structural model of risky bond pricing. However, empirical testing suggests that this and subsequent generations of models are of little use in practice.
Recent research suggests that using different techniques to estimate input parameters improves model performance. We examine the use of maximum likelihood estimation and numerical optimisation to see whether structural model performance is improved to the point where structural models can be applied in real markets.