Excerpt
Table of content
List of illustrations
Abstract
1.Introduction
2.Data
3.Methodology
3.1. Properties of an ARMA model
3.2. Properties of a GARCH model
4.Data Analysis
5.Examining gold close data
5.1. Gold log - returns
5.2. ACF and PACF of the gold log-returns
5.3. Applying ARMA-models on gold log-returns
5.4. Testing the residuals of the gold log – returns
5.5. Normality assumption of the residuals of the gold log - returns
5.6. Heteroscedasticity of the gold log - returns
5.7. Using GARCH to model the time series of the gold log - returns
5.8. Testing for skewed t-distribution of the residuals in a GARCH - model
6.Examining the silver close data
6.1. Silver log-returns & ACF/PACF of the silver return data
6.2. Testing ARMA models on the silver log-returns
6.3. Independence assumption of the residuals of the silver log-return data
6.4. Normality assumption of the residuals of the silver log-return data
6.5. Heteroscedasticity of the residuals of the silver log-return data
6.6. Examining GARCH - models on the silver log-return data
6.7. Testing skewed t-distribution and independence assumption of residuals of the silver log – return data
7. Forecasting gold and silver returns
8. Drawbacks of the research
9. Conclusion
10. References
Appendix 1: Testing of models - AR (1); MA (1); ARMA (1,1) for gold log-returns
Appendix 2: Overfitting approach with MA (2); MA (3) for gold log-returns
Appendix 3: Testing of models - AR (1); MA (1); ARMA (1,1) for silver log-returns
Appendix 4: Overfitting approach with MA (2); MA (3) for gold log-returns
Appendix 5: fitted GARCH(1,1)-model skewed t-distributed with mean for silver returns
Appendix 6: Attempt of forecasting the gold and silver returns
Appendix 7: R codes used to examine the gold return data
Appendix 8: R codes used to examine the gold return data
- Quote paper
- Van Anh Hoang (Author), 2016, Application of ARMA and GARCH models to the daily gold and silver exchange prices in US dollar, Munich, GRIN Verlag, https://www.grin.com/document/319861
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