Management of Foreign Exchange Risk Evidence from Developing Economies

Foreword

Summary and Preface

Graphs

Tables

Abbreviations

Chapter 1: Strategic Overview

1.1 Background of the study

1.2 Contribution to knowledge

1.3 History of the topic

1.4 Geographical location of the topic

1.5 Benefits to the community

1.6 Why is it significant?

1.7 Who is it significant to?

1.8 Organisation of book

Chapter 2: Exchange-rate Risk Management and Modelling

2.1 Introduction

2.2 Exchange-rate risk and economic liberalisation

2.3 Classical time series models and financial series

2.4 Exchange-rate volatility modelling in a univariate framework

2.5 Exchange-rate volatility modelling in a multivariate framework

2.6 Risk management of exchange-rate volatility

2.7 Conclusion

Chapter 3: Exchange-rate Risk and Economic Liberalisation

3.1 Introduction

3.2 Developments in the Malaysian exchange-rate market

3.2.1 Asian financial crises period

3.2.2 Post-Asian financial crises

3.3 Data analysis of Malaysia’s exchange-rate

3.4 Implications

3.5 Conclusion

Chapter 4: Volatility Modelling of Exchange-rates in a Univariate Framework

4.1 Introduction

4.2 Framework and estimation process

4.2.1 Conditional mean

4.2.2 Autoregressive Conditional Heteroscedastic models

4.2.3 Generalised Autoregressive Conditional Heteroscedastic models

4.2.4 Density functions of GARCH’s innovation process

4.2.5 Exponential GARCH

4.2.6 Misspecification tests

4.3 Empirical results

4.4 Value-at-Risk

4.4.1 RiskMetrics

4.4.2 Asymmetric Power ARCH

4.5 Implications

4.5.1 Risk modelling

4.5.2 Risk measurement

4.6 Conclusion

Chapter 5: Volatility Modelling of Exchange-rates in a Multivariate Framework

5.1 Introduction

5.2 Framework and estimation process

5.2.1 RiskMetrics

5.2.2 BEKK model

5.2.3 Orthogonal GARCH

5.2.4 Generalised O-GARCH

5.2.5 NLS GO GARCH

5.2.6 Constant conditional correlation

5.2.7 Dynamic conditional correlation

5.2.8 Dynamic equicorrelation

5.2.9 Corrected DCC

5.3 Estimation processes

5.4 Diagnostic testing

5.4.1 Portmanteau statistics

5.4.2 CCC tests

5.5 Empirical results

5.6 Implications

5.7 Conclusion

Chapter 6: Concluding Remarks

6.1 Introduction

6.1.1 Risk modelling

6.1.2 Risk measurement

6.1.3 Risk management

6.2 Volatility issues in the exchange-rate market

6.2.1 General volatility issues

6.2.2 Malaysia issues

6.3 Implications on risk measurement

6.3.1 Univariate stochastic volatility modelling

6.3.2 Multivariate stochastic volatility modelling

6.4 Implications on risk management

6.4.1 Government stabilisation policy

6.4.2 Individuals and institutions

6.4.3 Education on risk management

6.4.4 Efficient market hypothesis

6.5 Limitations and areas of further research

6.6 Conclusion

References

Appendices

1: Foreign exchange changes in Malaysia on 1 April 2005

2: Analysis of monthly exchange-rate data

3: Forecasting diagrams of various GARCH models

A.3.1 MYR/USD

A.3.2 MYR/GBP

A.3.3 MYR/EUR

A.3.4 MYR/JPY

A.3.5 MYR/CHF

4: Forecasting diagrams between RiskMetrics and APARCH models

A.4.1 MYR/USD

A.4.2 MYR/GBP

A.4.3 MYR/EUR

A.4.4 MYR/JPY

A.4.5 MYR/CHF

5: Empirical results for multivariate GARCH models

A.5.1 Scalar BEKK (1,1) by Engle and Kroner (1995)

A.5.1.1 Normal distribution for error term

A.5.1.2 Student distribution for error terms

A.5.2 Diagonal BEKK

A.5.2.1 Normal distribution for error terms

A.5.2.2 Student distribution for error terms

A.5.3 RiskMetrics

A.5.3.1 Normal distribution for error terms

A.5.3.2 Student distribution for error terms

A.5.4 Constant Conditional Correlations by Bollerslev (1990)

A.5.4.1 Normal distribution for error terms

A.5.4.2 Student distribution for error terms

A.5.5 Dynamic Conditional Correlations by Tse and Tsui (2002)

A.5.5.1 Normal distribution for error terms

A.5.5.2 Student distribution for error terms

A.5.6 Dynamic Conditional Correlations by Engle (2002)

A.5.6.1 Normal distribution for error terms

A.5.6.2 Student distribution for error terms

A.5.7 Orthogonal GARCH model

A.5.7.1 Normal distribution

A.5.7.2 Student distribution for error terms

A.5.8 GO-GARCH model (by Van der Wedie (2002))

A.5.8.1 Normal distribution for error terms

A.5.8.2 Student distribution for error terms

A.5.9 NLS GO-GARCH model (by Boswijk and Van der Wedie (2006))

A.5.9.1. Normal distribution for error terms

A.5.9.2 Student distribution for error terms

Index

Biography

Yew C. Lum is a Senior Lecturer in Finance and Coordinator of Faculty and Student Services Committee at Xiamen University Malaysia.

Sardar M. N. Islam is currently a Professor of Economic Studies, and has also been a Professor of Business, Economics and Finance (2007–2017) at Victoria University, Melbourne, Australia.