Forecasting Bankruptcy And Distress Risk

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[Forecasting Bankruptcy and Distress Risk]

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Acknowledgement

I would take this opportunity to thank my research supervisor, family and friends for their support and guidance without which this research would not have been possible.

DECLARATION

I, [type your full first names and surname here], declare that the contents of this dissertation/thesis represent my own unaided work, and that the dissertation/thesis has not previously been submitted for academic examination towards any qualification. Furthermore, it represents my own opinions and not necessarily those of the University.

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Abstract

This dissertation analysis the financial model for forecasting bankruptsy with help of the article “In Search of Distress Risk” by John Y.Campbell, Jens Hilscher, and Jan Szilagyi (2008). This thesis evaluates the predictive ability of two Bankruptcy models: A reduced form logistic regression model based on Campbell et al. (2008) using accounting and market Variables, and an option pricing method- both employs the US data. I find that the first model outperforms the second one significantly in predicting failures. This study also explores through the relation between distress risk and equity return in the US. I find that the distressed stocks (i.e. high Bankruptcy probability derived from the reduced form model), generate higher returns; an evidence which is contrary to most of previous literature.

Table of Contents

Acknowledgementii

DECLARATIONiii

Abstractiv

Chapter 1: Introduction1

Chapter 2: Literature Review3

Chapter 3: Methodology21

Campbell, Hilscher, and Szilagyi (2008) model21

Option Pricing Models22

Model Accuracy Evaluation26

The relation among stock returns, firm's characteristics and momentum29

Data30

Sample Selection31

Failures and non-failures31

Calculations and adjustment of Variables32

Summary Statistics34

Size classification for running Fama MacBeth Regressions37

Chapter 4: Results & Discussion38

Logit Model of Bankruptcy38

Information content of the Logit Model and Default-to-distance measure42

Predictive ability of the CHS and BS models45

Chapter 5: Conclusion51

Limitations of the study53

References55

Appendices61

Chapter 1: Introduction

Corporate Bankruptcy has always been studied due to its severe consequences. The impact of insolvency could be enormous to the firm and its stakeholders, such as equity owners, creditors, managers and employees. Bankruptcy, can also affect the global economy (e.g. increasing the unemployment rate or harming the investors' confidence in financial markets). The occurrence of important bankruptcies, such as WordCom and Enron has made the regulators and governors more cautious of the risks involved in corporate failures. Developing valid and accurate models to predict failures prior to the incident can help the stakeholders to take defensive actions to minimise the probable losses; thus, constructing such prediction models and testing their predictive ability is essential. By applying precise forecasting models based on available data managers would be able to observe the early warning indicators and could make corrective decisions; employees would increase their efforts to survive or start to search for new careers; suppliers could restrict their businesses with distressed companies; governments and regulatory institutes could facilitate the business conditions and ease the regulations of the troubled sector; auditors would convey the early notice by their qualified statements on distressed firms; credit rating agencies would be able to provide a more precise opinion on the ability of firms to raise debt; creditors would structure their lending based on probability of default and would minimise their losses; and investors ...