EUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL
In this final project, the objective of the study is to develop GARCH model for European option pricing. The motivation behind this study is based on observations on the volatility of financial assets which tends to contain volatility clustering. Volatility clustering in financial assets can be capt...
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id-itb.:280132018-05-11T13:34:33ZEUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL LIZAL (NIM: 10114001), IMELDA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/28013 In this final project, the objective of the study is to develop GARCH model for European option pricing. The motivation behind this study is based on observations on the volatility of financial assets which tends to contain volatility clustering. Volatility clustering in financial assets can be captured by the ARCH (Auto Regressive Conditional Heteroskedasticity) and GARCH (Generalized ARCH) models which then had been developed into GARCH-M (GARCH in-mean). The European option price can be determined under risk-neutral probability measure which satisfies Locally Risk Neutral Valuation Relationship (LRNVR) assuming the log-return of an asset is normally distributed. On the other hand, based on observations, the normal distribution is not an adequate choice for modelling financial assets. Therefore, the assumption that the log-return of an asset is normally distributed is not suitable. Furthermore, the LRNVR criterion had been generalized into GLRNVR. Under the GLRNVR criterion, the log-return of an asset does not have to be assumed as normally distributed. Hence, its distribution can be assumed to be leptokurtic. The results of option pricing based on GARCH-M(1,1) model with Gaussian innovation is compared with Black-Scholes formula and Generalized Error Distribution innovation. text |
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In this final project, the objective of the study is to develop GARCH model for European option pricing. The motivation behind this study is based on observations on the volatility of financial assets which tends to contain volatility clustering. Volatility clustering in financial assets can be captured by the ARCH (Auto Regressive Conditional Heteroskedasticity) and GARCH (Generalized ARCH) models which then had been developed into GARCH-M (GARCH in-mean). The European option price can be determined under risk-neutral probability measure which satisfies Locally Risk Neutral Valuation Relationship (LRNVR) assuming the log-return of an asset is normally distributed. On the other hand, based on observations, the normal distribution is not an adequate choice for modelling financial assets. Therefore, the assumption that the log-return of an asset is normally distributed is not suitable. Furthermore, the LRNVR criterion had been generalized into GLRNVR. Under the GLRNVR criterion, the log-return of an asset does not have to be assumed as normally distributed. Hence, its distribution can be assumed to be leptokurtic. The results of option pricing based on GARCH-M(1,1) model with Gaussian innovation is compared with Black-Scholes formula and Generalized Error Distribution innovation. |
format |
Final Project |
author |
LIZAL (NIM: 10114001), IMELDA |
spellingShingle |
LIZAL (NIM: 10114001), IMELDA EUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL |
author_facet |
LIZAL (NIM: 10114001), IMELDA |
author_sort |
LIZAL (NIM: 10114001), IMELDA |
title |
EUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL |
title_short |
EUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL |
title_full |
EUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL |
title_fullStr |
EUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL |
title_full_unstemmed |
EUROPEAN OPTION PRICING WITH GARCH-M(1,1) MODEL |
title_sort |
european option pricing with garch-m(1,1) model |
url |
https://digilib.itb.ac.id/gdl/view/28013 |
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1821994938345193472 |