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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 呂育道 | |
| dc.contributor.author | Yu-Chieh Chang | en |
| dc.contributor.author | 章宇傑 | zh_TW |
| dc.date.accessioned | 2021-06-13T05:51:33Z | - |
| dc.date.available | 2006-07-06 | |
| dc.date.copyright | 2006-07-06 | |
| dc.date.issued | 2006 | |
| dc.date.submitted | 2006-07-04 | |
| dc.identifier.citation | Duan, Jin-Chuan, The GARCH Option Pricing Model, Mathematical Finance 5, 1995, 13-32.
Yuh-Dauh Lyuu, Chi-Ning Wu, On Accurate and Provably Efficient GARCH Option Pricing Algorithms, Quantitative Finance, 5, No. 2 (April 2005), 181-198.Yuh-Dauh Lyuu, A General Computational Method for Calibration Based on Differential Trees, Journal of Derivatives, 7, No. 1 (Fall 1999),79-90. R. Douglas Martin, GARCH Modeling of Time-Varying Volatilities and Correlations, Financial Engineering News, No. 4, May 1998. William H. Press, Saul A. Teukoksky, William T. Vetterling, Brian P. Flannery, Numerical Recipe in C++, Cambridge Universidy Press. Peter Ritchken, Rob Trevor, Pricing Options under Generalized GARCH and Stochastic Volatility Processes, Journal of Finance, 54, No.1 1999,377-402. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/34012 | - |
| dc.description.abstract | GARCH是一個相當常見的隨機變異數模型。這個模型成功的描繪了資產報酬的序列相關。這個模型有五個參數，而其中某些參數並沒有直覺的經濟意義，所以如何決定參數是GARCH模型所面臨最重要的問題之一。傳統上最常用的方法是在歷史資料上使用最大概似法來估計，本論文提供了一個有效率的數值演算法以選擇權價格來校對模型參數。 | zh_TW |
| dc.description.abstract | GARCH is one of the most popular stochastic variance models. The model successfully captures the serial correlation of asset return volatilities. The model needs five parameters, and some of them do not have intuitively economic meanings. So how to determine the parameters is one of the most challenging problems facing the GARCH model. Applying the maximum likelihood method to the
historical data is the most common approach to obtaining the parameters. As an alternative, this thesis develops efficient numerical algorithms to calibrate the model with option prices. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-13T05:51:33Z (GMT). No. of bitstreams: 1 ntu-95-R93922034-1.pdf: 246816 bytes, checksum: 605e157b8615740078dc233a465f443c (MD5) Previous issue date: 2006 | en |
| dc.description.tableofcontents | Introduction 1
The GARCH model 3 The mean-tracking (MT) tree 5 Calibration based on the di®erential tree 9 Applying the Newton-Raphson method 14 Choices of the products 16 Estimating the parameters 21 Conclusion 24 | |
| dc.language.iso | en | |
| dc.subject | 參數估計 | zh_TW |
| dc.subject | 隨機變異數模型 | zh_TW |
| dc.subject | parameter estimation | en |
| dc.subject | GARCH | en |
| dc.title | GARCH模型之參數估計 | zh_TW |
| dc.title | Parameters Estimation of the GARCH Model | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 94-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 金國興,戴天時 | |
| dc.subject.keyword | 參數估計,隨機變異數模型, | zh_TW |
| dc.subject.keyword | GARCH,parameter estimation, | en |
| dc.relation.page | 25 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2006-07-06 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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