The Analysis of Stochastic Volatility in High-Frequency Financial Data
碩士 === 國立交通大學 === 統計學研究所 === 104 === The thesis focus on the analysis of high-frequency financial data. There are lots of estimation methods in univariate asset such as two-time scale realized volatility (TSRV) which we would introduced here. In multiple assets, we present the Wishart-Autoregressive...
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| Format: | Others |
| Language: | en_US |
| Published: |
2016
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| Online Access: | http://ndltd.ncl.edu.tw/handle/91629146301434611755 |
| Summary: | 碩士 === 國立交通大學 === 統計學研究所 === 104 === The thesis focus on the analysis of high-frequency financial data.
There are lots of estimation methods in univariate asset such as two-time scale realized
volatility (TSRV) which we would introduced here.
In multiple assets, we present the Wishart-Autoregressive process which can be used
to model the dynamic structure of volatility matrices in financial application, with the
closed-form prediction and model flexibility, it is alternative to GARCH or stochastic
Models. Another method is combination approaches which can simply compute the
estimations or predictions without losing any information of available data.
Finally, we compare the estimations for intraday returns in stochastic volatility.
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