E-Thesis 509 views 222 downloads
Modelling and forecasting stock and stock market volatility. / Craig Paul Gower
Swansea University Author: Craig Paul Gower
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Abstract
The examination of stock price volatility has come under increased scrutiny due to the large swings in stock price movements that have occurred with greater frequency than the historical average. Additionally, the substantial increases in the volume of options trading has increased the importance of...
| Published: |
2001
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| Institution: | Swansea University |
| Degree level: | Doctoral |
| Degree name: | Ph.D |
| URI: | https://cronfa.swan.ac.uk/Record/cronfa42339 |
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| Abstract: |
The examination of stock price volatility has come under increased scrutiny due to the large swings in stock price movements that have occurred with greater frequency than the historical average. Additionally, the substantial increases in the volume of options trading has increased the importance of accurate volatility forecasts due to the volatility forecast being the most important parameter affecting the pricing of options. Consequently, the aim of the thesis is to analyse the volatility of forty-five FTSE 100 stocks, the FTSE 100 index together with other major and emerging market stock indices. In particular, a comparison of the modelling and forecasting ability of GARCH type and stochastic volatility models is undertaken. The forecasting ability of the above models is compared against three benchmark models: the historical mean, random walk and exponential smoothing models. In terms of forecasting, the thesis is of interest because there have been few comparative studies for individual UK stocks. Additionally, the volatility-volume relationship is also considered in order to test the mixture of distributions hypothesis rationalisation for GARCH. In an extension of the current volatility volume literature, the CGARCH-volume model is used to examine the temporary volatility volume interactions. In terms of modelling ability, the stochastic volatility model performs on a par with the GARCH type models. In the forecasting analysis, the daily forecasts of FTSE 100 stocks perform poorly against the benchmark models with the four-weekly volatility forecasts performing relatively better. For the indices, the GARCH type models perform substantially better than for the FTSE 100 stocks. |
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| Keywords: |
Finance.;Economics. |
| College: |
Faculty of Humanities and Social Sciences |