| DC 欄位 |
值 |
語言 |
| DC.contributor | 統計研究所 | zh_TW |
| DC.creator | 林韋成 | zh_TW |
| DC.creator | Wei-Cheng Lin | en_US |
| dc.date.accessioned | 2018-8-24T07:39:07Z | |
| dc.date.available | 2018-8-24T07:39:07Z | |
| dc.date.issued | 2018 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=105225002 | |
| dc.contributor.department | 統計研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 在本文中，我們提出對於copula之下馬可夫鍊模型的估計問題，由於在股票市場中其厚尾的特性，我們選用混和常態模型作為我們的邊際分布，基於邊際分布為混和常態分佈和Clayton copula，我們得到相應的概似函數，為了解決最大概似估計量的問題，我們應用了牛頓-拉弗森方法，在實證分析中，我們分析了道瓊斯工業平均指數的股票價格。 | zh_TW |
| dc.description.abstract | In this paper, we propose the estimation problem for a copula-based Markov model. Owing to the fat tail feature in stock market, we select mixture normal distribution as the marginal distribution for the log return. Based on the mixture normal distribution as the marginal distribution and the Clayton copula, we obtain the corresponding likelihood function. In order to solve the maximum likelihood estimators, we apply Newton Raphson method. In the empirical analysis, the stock price of Dow Jones Industrial Average is analyzed for illustration. | en_US |
| DC.subject | copula | zh_TW |
| DC.subject | 混和常態模型 | zh_TW |
| DC.subject | 牛頓-拉弗森 | zh_TW |
| DC.subject | k-平均演算法 | zh_TW |
| DC.subject | 馬可夫模型 | zh_TW |
| DC.subject | 對數報酬 | zh_TW |
| DC.subject | copula | en_US |
| DC.subject | mixture normal distribution | en_US |
| DC.subject | Newton-Raphson | en_US |
| DC.subject | k-means clustering | en_US |
| DC.subject | Markov model | en_US |
| DC.subject | log return | en_US |
| DC.title | Estimation in copula-based Markov mixture normal model | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Estimation in copula-based Markov mixture normal model | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |