Acknowledgements

I would like to thank my supervisor Dr. Illias Tsiakas for his continued support and Encouragement. I would like to thank my father, mother and my sister for their tremendous support and understanding not only through the period of this thesis but for the period of the entire masters programme. In addition I would like to thank some of my friends who supported and encouraged me. Special thanks to Dr. Abhay Abhyankar for his assistance and help in the dissertation.

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Abstract

The volatility associated with interest rate movements and the risks arising from exposure to this volatility has made it an important subject of study. Most existing studies examining the phenomenon of interest rate sensitivity have focussed on its effects on the stock returns of banks and financial institutions. While it is certainly true that due to the nature of their activities such firms are bound to be significantly affected by interest rate movements. Nevertheless, interest rate movements also affect firms which are nonfinancial in nature. Little is known about the interest rate exposure faced by nonfinancial firms. One of the main contributions of this paper is that we have attempted to analyse the interest rate exposure of both financial as well as non-financial corporations simultaneously. This paper uses a three factor regression model, whereby we regress the returns on any chosen S&P 500 index on the returns on the S&P 500 composite index, changes in the domestic interest rates and changes in the global interest rates. In addition we have also explored the possibility that interest rate movements and stock returns could be related in a complex manner or are nonlinear functions of each other and therefore we explore the existence of nonlinear exposure profiles. A feature of this paper is that we have made an attempt to analyse and compare the results obtained for the three different model specifications used, thereby making a recommendation on which model specification is the better.

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Table of Contents:

1. Introduction 2. Theoretical Overview

2.1 Explanations based on changes in inflation 2.2 Explanations based on real interest rate changes

page no. 3 6

9 10

3. Literature Review 4. Data description and methodology

4.1 Methodology for linear exposure profiles 4.1.1 Returns on the market portfolio 4.1.2 Unanticipated changes in long-term domestic interest rates 4.1.3 Unanticipated changes in the long-term global interest rates 4.1.4 Orthogonality aspect 4.2 Nonlinearity aspect

13 28

28 31 32 33 37 40 41 44

4.2.1 Motivation for use of square functional specification 4.2.2 Motivation for use of cubic functional specification

5. Discussion of Empirical Results

Table1 – Regression results for linear specification Table 2 - Regression results for cubic specification Table 3 – Regression results for square specification 5.1 S&P 500 Utility index 5.2 S&P500 Bank index

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48 49 50 51 53

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5.3 S&P 500 Industrials index 5.4 S&P 500 Agricultural products index 5.5 S&P 500 Insurance index 5.6 S&P 500 Airline index 5.7 S&P 500 Transportation index 5.8 S&P 500 Financial industry index 5.9 S&P 500 Oil&Gas index 5.10 S&P 500 Entertainment index 5.11 S&P 500 Telecom services index

54 55 56 56 57 58 60 60 62 63-65 66 66 67 68 69 70-72

6.

Conclusion

Appendix A Appendix B Appendix C Appendix D Appendix E Bibliography

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1. Introduction

The relationship between interest rate movements and common stock returns has been the focus of a considerable amount of research in recent years. The chief reason for this increased interest in studying this relationship is that interest rate movements have shown a high degree of volatility historically. This volatility leads to the risks associated with interest rate movements or so called “Interest rate risk exposures”. The risks associated with interest...