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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 管中閔 | |
| dc.contributor.author | Hui-Ru Ma | en |
| dc.contributor.author | 馬惠茹 | zh_TW |
| dc.date.accessioned | 2021-06-16T13:37:51Z | - |
| dc.date.available | 2018-07-19 | |
| dc.date.copyright | 2013-07-19 | |
| dc.date.issued | 2013 | |
| dc.date.submitted | 2013-07-16 | |
| dc.identifier.citation | 1. 管中閔, 統計學: 觀念與方法 (二版), 台北, 華泰書局, 2004.
2. Andersen, T. and B. Sorensen (1996), GMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study, Journal of Business and Economic Statistics, 14,328–352. 3. Angrist, J., G. Imbens, and A. Krueger (1999), Jackknife Instrumental Variables Estimation, Journal of Applied Econometrics, 14, 57–67. 4. Altonji, J. and L. Segal (1996), Small Sample Bias in GMM Estimation of Covariance Structures, Journal of Business and Economic Statistics, 14, 353–366. 5. Brenner, R., R. Harjes, and K. Kroner (1996), Another Look at Models of the Short-Term Interest Rate, Journal of Financial and Quantitative Analysis, 31, 85–107. 6. Butler, J. S., and B. Schachter (1986), Unbiased Estimation of the Black-Scholes Formula, Journal of Financial Economics, 15, 341–357. 7. Chan, K., G. Karolyi, F. Longstaff, and A. Sanders (1992), An Empirical Comparison of Alternative Models of the Short-Term Rate, Journal of Finance, 47,1209–1227. 8. Chausse, P. (2010), Computing Generalized Method of Moments and Generalized Empirical Likelihood with R, Journal of Statistical Software, 34, 1–35. 9. Cox, J., J. Ingersoll, and S. Ross (1985), Theory of the Term Structure of Interest Rates, Econometrica, 53, 385–407. 10. Dell’Aquila, R., E. Ronchetti, and F. Trojani (2003), Robust GMM Analysis of Models for the Short Rate Process, Journal of Empirical Finance, 10, 373–397. 11. Donald, S. and W. Newey (2000), A Jackknife Interpretation of the Continuous Updating Estimator, Economics Letter, 67, 239–243. 12. Efron, B. (1982), The Jackknife, the Bootstrap, and Other Resampling Plans, Philadelphia: SIAM. 13. Hall, A. R. (2005), Generalized Method of Moments, New York: Oxford University Press. 14. Hamilton, J. D. (1994), Time Series Analysis, Princeton, NJ: Princeton University Press. 15. Hansen, L. P. (1982), Large Sample Properties of Generalized Methods of Moments Estimators, Econometrica, 50, 1029–1054. 16. Hansen, L. P., J. Heaton, and A. Yaron (1996), Finite-Sample Properties of Some Alternative GMM Estimators, Journal of Business and Economic Statistics, 14, 262–280. 17. Harvey, A. C., and N. Shephard (1996), Estimation of an Asymmetric Model of Asset Prices, Journal of Business and Economic Statistics, 14, 429–434. 18. Hull, J. (2000), Options, Futures, and Other Derivatives (2d ed.), NJ: Prentice-Hall. 19. Jagannathan, R., G. Skoulakis, and Z. Wang (2002) Generalized Method of Moments: Applications in Finance, Journal of Business and Economic Statistics, 20,470–481. 20. Knight, J., S. Satchell (1997), Existence of Unbiased Estimators of the Black-Scholes Option Price, Other Derivatives, and Hedge Ratios, Econometric Theory, 13, 791– 807. 21. Kuan, C.-M. (2011), Generalized Method of Moment Lecture Note, National Taiwan University, Taipei. 22. Lehmann, E. L. (1983), Theory of Point Estimation, New York: Wiley. 23. Newey, W., and R. Smith (2004), Higher Order Propertiew of GMM and Generalized Empirical Likelihood Estimators, Econometrica, 72, 219–255. 4324. Newey, W., and F. Windmeijer (2009), GMM with Many Weak Moment Conditions: Replication and application, Journal of Applied Econometrics, 27, 791–807. 25. Phillips, P. C. B. and J. Yu (2005), Jackknifing Bond Option Prices, Review of Financial Studies , 18, 707–742. 26. Quenouille, M. (1956), Notes on Bias in Estimation, Biometrika, 43, 353–360. 27. Sheppard, K. (2012), Financial Econometrics Notes, University of Oxford, Oxford. 28. Shao, J., and D. Tu (1995), The Jackknife and the Bootstrap, New York: Springer. 29. Shao, J. and C. F. J. Wu (1989), A General Theory for Jackknife Variance Estimation, Annals of Statistics, 17, 1176–1197. 30. Stock, J. and J. Wright (2000), Gmm with Weak Identifcation, Econometrica, 68,1055–1096. 31. Taylor, S. (1982), Financial Returns Modelled by the Product of Two Stochastic Processes - A Study of Daily Sugar Prices 1961–1979, Time Series Analysis: Theory and Practice, 1,203 - 226. 32. Tukey, J. W. (1958), Bias and Confidence in Not Quite Large Samples, Annals of Mathematical Statistics, 29, 343–346. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/62272 | - |
| dc.description.abstract | 本篇論文介紹一種能減少估計式偏誤的方法: Quenouille (1956) 提出的折刀法 (jackknife)。我們也說明,在 GMM 的架構下,根據傳統折刀法所得到的估計式, 事實上與 Angrist, Imbens,and Krueger(1999)所介紹的折刀法工具變數估計式的作法並不相同。模擬結果顯示傳統折刀法的估計式與折刀法工具變數皆能皆能減少 GMM 估計式的偏誤,但傳統折刀法的估計式效果較好且適用範圍較為廣泛。實證結果亦支持傳統折刀法的估計式的確能減少 GMM 估計式的偏誤。 | zh_TW |
| dc.description.abstract | This paper introduces a bias reduction estimator method: Quenouille (1956) proposed jackknife. We also shows that in the GMM framework, according to the traditional jackknife estimator obtained, in fact, is not the same with Angrist, Imbens, and Krueger (1999) described jackknife instrumental variables estimation approach. Simulation results show that the traditional jackknife estimation method and jackknife instrumental variables estimator both can reduce the bias of GMM estimator, but the traditional jackknife estimator has better performance and wider application. The empirical results also support the traditional jackknife estimator can indeed reduce the bias of GMM estimator. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T13:37:51Z (GMT). No. of bitstreams: 1 ntu-102-R98723082-1.pdf: 2985525 bytes, checksum: a14082694a1a1eed66703aad26900d9e (MD5) Previous issue date: 2013 | en |
| dc.description.tableofcontents | 目錄
1 前言 6 2 折刀法的概念與性質 8 2.1 Jackknife Delete-1 參數估計式 . . . . . . . . . . . . . 8 2.2 Jackknife Delete-d 參數估計式 . . . . . . . . . . . 12 2.3 Group Jackknife . . . . . . . . . . . . . . . . . . 15 3 GMM 估計方法與性質 . . . . . . . . . . . . . . . . . 17 3.1 GMM 的概念與性質 . . . . . . . . . . . . . . . . . . 18 3.2 GMM 估計方法 .. . . . . . . . . . . . . . . . . . . . 20 3.3 財務模型的應用 . . . . . . . . . . . . . . . . . . . . 24 3.3.1 隨機波動模型 . . . . . . . .. . . . . . . . . . . . . 25 3.3.2 消費為基礎下的資本資產定價模型 . . . . . . . . . . . . . 28 3.3.3 利率期限結構模型 . . . . . . . . . . . . . . . . . . . 31 4 GMM-Jackknife . . . . . . . . . . . . . . . . . . . 32 4.1 工具變數估計式 . . . . . . . . . . . . . . . . . . . . 33 4.2 JIVE 工具變數 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 4.3 Jackknife Delete-1 與 Group Jackknife 工具變數 . 37 5 模擬研究 38 45.1 模擬的模型設計 . . . . . . . . . . . . . . . . . . . . 38 5.2 模擬結果 . . . . . . . . . . . . . .. . . . . 41 6 實證分析 43 6.1 模型與資料的選取 .. . . . . . . . . . . . . . . . . 43 6.2 實證結果與討論 . . . . . . . . . . . . . . . . 44 7 結論 45 | |
| dc.language.iso | zh-TW | |
| dc.subject | JIVE | zh_TW |
| dc.subject | 折刀法 | zh_TW |
| dc.subject | jackknife delete-1 | zh_TW |
| dc.subject | group jackknife | zh_TW |
| dc.subject | GMM | zh_TW |
| dc.subject | 偏誤估計式 | zh_TW |
| dc.subject | CIR | zh_TW |
| dc.subject | bias estimator | en |
| dc.subject | CIR | en |
| dc.subject | JIVE | en |
| dc.subject | GMM | en |
| dc.subject | group jackknife | en |
| dc.subject | jackknife delete-1 | en |
| dc.subject | jackknife | en |
| dc.title | 以折刀法減少估計式偏誤:方法與財務應用 | zh_TW |
| dc.title | Reducing Estimator Bias by Jackknife: Method and Financial Application | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 101-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 徐之強,何耕宇 | |
| dc.subject.keyword | 偏誤估計式,折刀法,jackknife delete-1,group jackknife,GMM,JIVE,CIR, | zh_TW |
| dc.subject.keyword | bias estimator,jackknife,jackknife delete-1,group jackknife,GMM,JIVE,CIR, | en |
| dc.relation.page | 44 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2013-07-16 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 財務金融學研究所 | zh_TW |
| 顯示於系所單位： | 財務金融學系 | |
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