Modelling financial risk: Essays in asset pricing and stress testing

This thesis comprises two chapters, with each contributing to the current body of knowledge surrounding financial risk modelling. Chapter-1 examines market risk by testing the new Fama-French Five-Factor Model. Chatper-2 focuses on Credit Risk, conducting a case study on the use of stress testing models on credit portfolios. To improve on the previous Three-Factor Asset Pricing Model, Fama and French (2015) propose a new Five-Factor Model, adding portfolio factors that mimic profitability and investment patterns in stock returns. With limited testing of this model carried out so far, further testing is required to determine how effective the model is at explaining excess returns. Chapter-1 of this thesis uses Ordinary Least Squares (OLS) Regression and Quantile Regression (QR) (Koenker & Bassett, 1978) to examine the effectiveness of this new factor model in modelling excess returns of the Dow Jones Industrial Average constituent stocks around the mean and across various quantiles of the return distribution. Starting with the Three-Factor Model and augmenting it one factor at a time to measure the impact of the proposed new investment and profitability factors. Chatper-2 evaluates the credit risk in retail mortgage portfolios using a case study on stress testing, conducted at a bank in Western Australia as a part of honours industry project1. There has been a heightened emphasis on credit risk in the wake of the GFC, with regulators increasing their focus on the credit risk behaviour of banks. Regulators in Australia have a long history of strong regulation of banks, with a particular focus on credit risk. The case study in this chapter focuses on the use of stress testing as a tool for credit risk modelling, focusing on the use of macroeconomic stress testing models on retail mortgage portfolios by examining the literature surrounding stress testing process, and then providing a brief example on the empirical use of stress testing