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| Title: | 隱含波動率指數的分析及預測 - Mixed Causal-Noncausal Model 的應用
Modeling and Predicting The CBOE Volatility Index - Application of Mixed Causal-Noncausal Model |
| Authors: | 王姸之 |
| Contributors: | 徐士勛
王姸之 |
| Keywords: | 非因果模型
混合模型
隱含波動率指數
可拆解性質
Noncausal
Mixed causal-noncausal model
VIX
Filter |
| Date: | 2017 |
| Issue Date: | 2017-07-11 12:06:48 (UTC+8) |
| Abstract: | 本研究主要針對 Breidt et al.(1991) 等多位學者所建構的 Mixed causal-noncausal model,探討其假設與可拆解特性,並仔細討論相關資料模擬估計及預測的方法,最後將其實際應用於隱含波動率指數 (Volatility Index)的估計及預測上。根據本研究的實證結果,我們發現隱含波動率指數確實包含非因果的特性,並可進一步對其拆解及預測。另外 , 我們也以移動窗格的方式觀察係數估計結果的變化,發現 Mixed Causal-Noncausal Model 的確能夠捕捉到泡沫或危機正在生成的過程。
This paper first focuses on Mixed causal-noncausal model constructed by Breidt et al.(1991) and then conducts empirical research on the CBOE Volatility Index. The assumptions, simulation, estimation and prediction methods of Mixed causal-noncausal model are introduced in great detail. Our empirical results show that the CBOE Volatility Index really contains non-causal parts, such that we can filter this part from the index and then further predict it. Moreover, by employing the rolling window estimation scheme the resulting coefficients of Mixed causal-noncausal model really could detect a bubble or a crisis which is going to happen. |
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| Description: | 碩士
國立政治大學
經濟學系
104258028 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0104258028 |
| Data Type: | thesis |
| Appears in Collections: | [經濟學系] 學位論文
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