| dc.contributor.advisor | 謝淑貞 | zh_TW |
| dc.contributor.advisor | Shieh, Shwu-Jane | en_US |
| dc.contributor.author (Authors) | 邱天禹 | zh_TW |
| dc.contributor.author (Authors) | Chiu, Tien-Yu | en_US |
| dc.creator (作者) | 邱天禹 | zh_TW |
| dc.creator (作者) | Chiu, Tien-Yu | en_US |
| dc.date (日期) | 2005 | en_US |
| dc.date.accessioned | 18-Sep-2009 14:09:54 (UTC+8) | - |
| dc.date.available | 18-Sep-2009 14:09:54 (UTC+8) | - |
| dc.date.issued (上傳時間) | 18-Sep-2009 14:09:54 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0093351006 | en_US |
| dc.identifier.uri (URI) | https://nccur.lib.nccu.edu.tw/handle/140.119/35100 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 國際經營與貿易研究所 | zh_TW |
| dc.description (描述) | 93351006 | zh_TW |
| dc.description (描述) | 94 | zh_TW |
| dc.description.abstract (摘要) | 本篇論文使用SWARCH模型探討布蘭特原油期貨市場的波動性。SWARCH模型將條件變異設定為可隨時間變動而改變，甚至移轉到不同的區間上。實證結果顯示SWARCH (3,3)模型具有最佳配適度與最準確的預測能力。樣本在不同區間下的平滑機率的估計值有助於補捉資料特性，而且當樣本落在高波動率區間上時會對應著重大事件的發生，如1990年波斯灣戰爭、1997年亞洲金融風暴與2001年的911恐怖攻擊。 | zh_TW |
| dc.description.abstract (摘要) | This paper investigates the volatility of the Brent crude oil futures markets using Markov-switching ARCH (SWARCH) model. The SWARCH model allows the conditional disturbances to change as time passes and even to switch in different regimes. The empirical evidence shows that the SWARCH (3,3) model performs the best goodness of fit and the best forecast performance between different fitting models. The estimation of smoothing probabilities of data under different regimes facilitates to capture the characteristics of data, and the high-volatility regime is associated with the extraordinary events, such as the 1990’s Persian Gulf War, the 1997’s Asia Financial Crisis, and the 2001’s 911 terrorist attack. | en_US |
| dc.description.tableofcontents | 1. Introduction 12. Methodology 52-1 Markov-switching ARCH (SWARCH) model 52-1-1 Markov chain and SWARCH model 52-1-2 Filter probability and smoothing probability 72-2 Maxima likelihood estimator 92-3 Forecast performance 93. Data and empirical result 103-1 Data 103-2 Statistic characteristics of data 123-3 Empirical results 133-3-1 Statistic fit comparisons for various specifications of different models 133-3-2 The forecast performance of different models 143-3-3 The estimation model and the probability under different regimes 144. Conclusions 16Appendix 18Reference 18Table 1 Descriptive Statistics of 20Table 2 ADF and PP Test 21Table 3 Statistic fit comparisons for various specifications of different models 22Table 4 Forecast performance of different models 23Figure 1 Daily closing price series and daily log-return series 24Figure 2 Q-Q plot against Normal and Student-t(7) 25Figure 3 ACF and PACF of log-return 26Figure 4 ACF and PACF of square of log-return 27Figure 5 Smoothing probability under different regimes 28 | zh_TW |
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| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0093351006 | en_US |
| dc.subject (關鍵詞) | 馬可夫轉換 | zh_TW |
| dc.subject (關鍵詞) | 波動率 | zh_TW |
| dc.subject (關鍵詞) | 布蘭特原油 | zh_TW |
| dc.subject (關鍵詞) | Markov-switching ARCH | en_US |
| dc.subject (關鍵詞) | SWARCH | en_US |
| dc.subject (關鍵詞) | volatility | en_US |
| dc.subject (關鍵詞) | Brent crude oil | en_US |
| dc.title (題名) | 布蘭特原油期貨的波動率－以馬可夫移轉模型分析 | zh_TW |
| dc.title (題名) | Regime-switched volatility of Brent crude oil futures using Markov-switching ARCH model | en_US |
| dc.type (資料類型) | thesis | en |
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