| DC 欄位 |
值 |
語言 |
| DC.contributor | 財務金融學系 | zh_TW |
| DC.creator | 劉炳麟 | zh_TW |
| DC.creator | Bin-Lin Liu | en_US |
| dc.date.accessioned | 2003-1-8T07:39:07Z | |
| dc.date.available | 2003-1-8T07:39:07Z | |
| dc.date.issued | 2003 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=88425007 | |
| dc.contributor.department | 財務金融學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 波動性在財務上扮演著關鍵的角色，若能適當的描述波動性模型，將有助於投資組合配置的最適化，進而能有效的控管風險。ARCH/GARCH族模型在波動性的預測上已被廣泛的應用，而且也能在實證上得到良好的成效。然而Chou(2002)將GARCH模型結合變幅在波動性預測上的優勢進一步提出CARR(Conditional Auto-Regressive Range)模型，並且在S&P500股價指數波動性預測實證上獲得優於GARCH模型的結論，本文想驗證是否在台股指數上也能得到相同的結論。
本文中將簡單的介紹CARR模型及其性質，並以台股指數為研究對象，分別進行CARR模型和GARCH模型在樣本內及樣本外波動性的預測能力比較。本文的實證結果可推論CARR模型在刻畫波動性方面優於GARCH模型，此與Chou(2002)的論述一致。另外，本文隨機選取了10檔個股資料，並比較其樣本內波動性預測能力用以強化論證的完整性。除此之外，本研究並推廣CARR模型的應用層面，考慮財務槓桿效應及漲跌幅限制的影響，並探討其背後所隱含的經濟意義。 | zh_TW |
| dc.description.abstract | In finance, volatility plays a key role in several sub-fields. Whether the construct of portfolio is optimal or not, partly depends on the control of volatility. Since 1982, ARCH/GARCH family models have been used in the forecast of volatilities, and have performed well in many empirical studies. Recently, Chou(2002) proposed the CARR (Conditional Auto-Regressive Range) model as an alternative volatility model. The main concept of the CARR model is to use a simple dynamic structure for range to characterize the volatility process. In Chou(2002), comparing the CARR model and traditional GARCH model, the former is better in the volatility forecasting based on the data of the S&P 500 index. The main motivation in this paper is to explore the forecasting power of the CARR model based on the trading data of the Taiwan Stock Exchange Capitalization Weighted Stock Index. Our emperical results show that in both the in-sample forecast and the out-of-sample forecast the CARR model is preferable to the GARCH model in the volatility forecasting, supporting the claims of Chou(2002). In order to strenghten the completeness of our demonstration, we arbitrarily choose 10 stocks in Taiwan to compare the two models again in the in-sample volatilities forecasting. Moreover, we also consider the economic implications of financial leverage effect and price limit by utilizing the CARR model. | en_US |
| DC.subject | CARR | zh_TW |
| DC.subject | GARCH | zh_TW |
| DC.subject | 變幅 | zh_TW |
| DC.subject | 波動性 | zh_TW |
| DC.subject | 財務槓桿效應 | zh_TW |
| DC.subject | 漲跌幅限制 | zh_TW |
| DC.subject | CARR | en_US |
| DC.subject | GARCH | en_US |
| DC.subject | Range | en_US |
| DC.subject | Volatility | en_US |
| DC.subject | Leverage Effect | en_US |
| DC.subject | Price Limit | en_US |
| DC.title | CARR模型之實證研究---以台股指數為例 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | An empirical study of the CARR model: an axample of the Taiwan Stock Index | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |