M.Com. (Financial Economics) / This study investigates the best measure of extreme losses in the South African equity derivatives market, and applies this to estimate the size of a default fund for Safcom, the central counterparty (CCP) for exchange-traded derivatives in South Africa. The predictive abilities of historic simulation Value at Risk (VaR), Conditional VaR (CVaR), Extreme VaR (EVaR) calculated using a Generalised Extreme Value (GEV) distribution and stress testing are compared during historic periods of stress in this market. The iterative cumulative sum of squares (ICSS) algorithm of Inclan and Tiao (1994) is applied to identify significant and large, positive shifts in the volatility of returns, thus indicating the start of a stress period. The FTSE/JSE Top 40 Index Future (known as the ALSI future) is used as a proxy for this market. Two key periods of stress are identified, namely the 1997 Asian crisis and the 2008 global financial crisis. The maximum daily losses in the ALSI during these stress periods were observed on 28 October 1997 and 6 October 2008. For the VaR-based loss estimates, 2500 trading days’ returns up to 28 October 1997 and 2750 trading days’ returns up to 6 October 2008 is used. The study finds that Extreme VaR predicts extreme losses during these two historic periods of stress the most accurately and is consequently applied to the quantification of a default fund for Safcom, using 2500 daily returns from 5 June 2003 to 31 May 2013. The EVaR-based estimation of a default fund shows that the current Safcom default fund is sufficient to provide for market losses equivalent to what was suffered during the 2008 global financial crisis, but not sufficient for the magnitude of losses suffered during the 1997 Asian crisis.

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Chen Chen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 122-129). / Abstracts in English and Chinese. / ABSTRACT --- p.ii / ACKNOWLEDGEMENT --- p.iv / TABLE OF CONTENTS --- p.v / LIST OF FIGURES --- p.vii / LIST OF TABLES --- p.viii / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Objectives and Motivation --- p.5 / Chapter 1.3 --- The Asian Crisis --- p.9 / Chapter 1.4 --- Procedures and Findings --- p.18 / Chapter 1.5 --- Summary --- p.20 / Chapter II. --- LITERATURE REVIEW --- p.21 / Chapter 2.1 --- Definition and Determinants --- p.21 / Chapter 2.2 --- Measurement Model --- p.25 / Chapter 2.3 --- Exchange Rate Fluctuation and Market Value of the Firm --- p.28 / Chapter 2.3.1 --- Exchange Rate Fluctuation and Stock Return --- p.28 / Chapter 2.3.2 --- Some Problems of the Measurement Model --- p.31 / Chapter 2.4 --- Exchange Rate Fluctuation and Market Risk of the Firm --- p.42 / Chapter 2.5 --- Summary --- p.45 / Chapter III. --- HYPOTHESES，METHODOLOGY & DATA --- p.47 / Chapter 3.1 --- Hypotheses --- p.47 / Chapter 3.2 --- Research Design --- p.50 / Chapter 3.3 --- Sample Selection --- p.56 / Chapter 3.3.1 --- Selection of Sample Group --- p.56 / Chapter 3.3.2 --- Selection of Control Group --- p.61 / Chapter 3.3.3 --- Comparison of Two Groups --- p.62 / Chapter 3.4 --- Data and the Measurement of the Variables --- p.64 / Chapter 3.5 --- Summary --- p.67 / Chapter IV. --- EMPIRICAL RESULTS AND DISCUSSION --- p.68 / Chapter 4.1 --- Exchange Rate Variability and Stock Return Volatility --- p.68 / Chapter 4.2 --- Exchange Rate Variability and Market Risk --- p.81 / Chapter 4.3 --- Interpretations --- p.87 / Chapter 4.3.1 --- Phenomenon 1: Cost of Equity and Net Cash Flows --- p.89 / Chapter 4.3.2 --- Phenomenon 2: Increased Return Variability and the US Stock Market Return --- p.92 / Chapter 4.4 --- Alternative Explanation --- p.96 / Chapter 4.5 --- Summary --- p.99 / Chapter V. --- CONCLUDING REMARKS --- p.100 / APPENDICES / APPENDIX 1. Firm Lists --- p.105 / APPENDIX 2. Estimates of CAPM Betas --- p.115 / BIBLIOGRAPHY --- p.122