Modelling volatilities of financial time series using the GARCH (1, 1) model
The autoregressive conditional heteroscedasticity (ARCH) model introduced by Engle (1982) and generalized autoregressive conditional heteroscedasticity (GARCH) model proposed by Bollseslev (1986) are such models that could model time varying volatility. Literally, ARCH/GARCH model take autocorrelati...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2013
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| Online Access: | https://eprints.nottingham.ac.uk/26445/ |
| _version_ | 1848793173328920576 |
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| author | Zhou, Ze |
| author_facet | Zhou, Ze |
| author_sort | Zhou, Ze |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The autoregressive conditional heteroscedasticity (ARCH) model introduced by Engle (1982) and generalized autoregressive conditional heteroscedasticity (GARCH) model proposed by Bollseslev (1986) are such models that could model time varying volatility. Literally, ARCH/GARCH model take autocorrelation and heteroscedasticity into account when measuring volatility. The aim in this dissertation is to estimate the volatilities of real financial data using GARCH (1, 1) model. |
| first_indexed | 2025-11-14T18:56:05Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-26445 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:56:05Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-264452017-10-19T13:29:54Z https://eprints.nottingham.ac.uk/26445/ Modelling volatilities of financial time series using the GARCH (1, 1) model Zhou, Ze The autoregressive conditional heteroscedasticity (ARCH) model introduced by Engle (1982) and generalized autoregressive conditional heteroscedasticity (GARCH) model proposed by Bollseslev (1986) are such models that could model time varying volatility. Literally, ARCH/GARCH model take autocorrelation and heteroscedasticity into account when measuring volatility. The aim in this dissertation is to estimate the volatilities of real financial data using GARCH (1, 1) model. 2013-09-05 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/26445/1/Ze_ZHOU_MSc_Dissertation.pdf Zhou, Ze (2013) Modelling volatilities of financial time series using the GARCH (1, 1) model. [Dissertation (University of Nottingham only)] (Unpublished) |
| spellingShingle | Zhou, Ze Modelling volatilities of financial time series using the GARCH (1, 1) model |
| title | Modelling volatilities of financial time series using the
GARCH (1, 1) model |
| title_full | Modelling volatilities of financial time series using the
GARCH (1, 1) model |
| title_fullStr | Modelling volatilities of financial time series using the
GARCH (1, 1) model |
| title_full_unstemmed | Modelling volatilities of financial time series using the
GARCH (1, 1) model |
| title_short | Modelling volatilities of financial time series using the
GARCH (1, 1) model |
| title_sort | modelling volatilities of financial time series using the
garch (1, 1) model |
| url | https://eprints.nottingham.ac.uk/26445/ |