Measuring and Modelling the Volatility of Financial Time Series
The thesis studies the measures and models of volatility for financial time series. We address the dependency of volatility on sampling frequency and show that this relationship can be explained by using delay equations for the underlying prices. In addition, a new implied volatility process is prop...
| Main Author: | |
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| Format: | Thesis |
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Curtin University
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/48861 |
| _version_ | 1848758117757616128 |
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| author | Luong, Phan Anh Chuong |
| author_facet | Luong, Phan Anh Chuong |
| author_sort | Luong, Phan Anh Chuong |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The thesis studies the measures and models of volatility for financial time series. We address the dependency of volatility on sampling frequency and show that this relationship can be explained by using delay equations for the underlying prices. In addition, a new implied volatility process is proposed to reduce the impact of the price movement. This allows us to improve the forecast accuracy of future volatility via the heterogeneous autoregressive model and random forest algorithm. |
| first_indexed | 2025-11-14T09:38:54Z |
| format | Thesis |
| id | curtin-20.500.11937-48861 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:38:54Z |
| publishDate | 2016 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-488612017-03-06T01:25:47Z Measuring and Modelling the Volatility of Financial Time Series Luong, Phan Anh Chuong The thesis studies the measures and models of volatility for financial time series. We address the dependency of volatility on sampling frequency and show that this relationship can be explained by using delay equations for the underlying prices. In addition, a new implied volatility process is proposed to reduce the impact of the price movement. This allows us to improve the forecast accuracy of future volatility via the heterogeneous autoregressive model and random forest algorithm. 2016 Thesis http://hdl.handle.net/20.500.11937/48861 Curtin University fulltext |
| spellingShingle | Luong, Phan Anh Chuong Measuring and Modelling the Volatility of Financial Time Series |
| title | Measuring and Modelling the Volatility of Financial Time Series |
| title_full | Measuring and Modelling the Volatility of Financial Time Series |
| title_fullStr | Measuring and Modelling the Volatility of Financial Time Series |
| title_full_unstemmed | Measuring and Modelling the Volatility of Financial Time Series |
| title_short | Measuring and Modelling the Volatility of Financial Time Series |
| title_sort | measuring and modelling the volatility of financial time series |
| url | http://hdl.handle.net/20.500.11937/48861 |