Responsive image
博碩士論文 etd-0724108-133705 詳細資訊
Title page for etd-0724108-133705
論文名稱
Title
高頻財務資料的長記憶及單根檢定
Statistical tests for long memory and unit root of high frequency financial data
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
73
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2008-06-25
繳交日期
Date of Submission
2008-07-24
關鍵字
Keywords
MPP單根檢定法、DF-GLS單根檢定法、ERS單根檢定法、KPSS單根檢定法、PP單根檢定法、擴大型的DF單根檢定法、門檻單根檢定、R/S 長記憶檢定法、GPH長記憶檢定法
GPH long memory test, MPP unit root test, R/S long memory test, PP unit root test, DF-GLS unit root test, ERS unit root test, threshold unit root test, ADF unit root test, KPSS unit root test
統計
Statistics
本論文已被瀏覽 5728 次,被下載 0
The thesis/dissertation has been browsed 5728 times, has been downloaded 0 times.
中文摘要
本篇論文主要探討單根檢定方法(包含了ADF、PP和KPSS單根檢定)、長記憶檢定方法(R/S和GPH檢定)及其在高頻資料的應用。我們利用SPLUS軟體分析資料,並對其單根檢定的一些錯誤提出修正。針對這兩種高頻資料的檢定方法,我們引用Yan及Zivot在2003年所設計的函式庫HFlibrary進行資料的初步分析並提出一個新的函式庫HFanalysis,該函式庫具有校正高頻資料的功能,包含剔除N.A.值、排序交易時間和擷取某時間的交易、等距化交易時間間隔和套裝檢定單根和長記憶性質。此外,我們利用此函式庫模擬文中六個單根檢定法和R/S與GPH長記憶檢定法的型一誤機率及檢定力並對實例進行分析。最後,我們探討有門檻限制資料的單根檢定並模擬門檻單根檢定之檢定統計量:WALD、LM、LR和W λ的百分位。
Abstract
In this thesis, we study the unit root tests which includes the ADF, PP and KPSS tests, the long memory tests such as the R/S and GPH tests, and the applications of these methods in high frequency
financial data analysis. The software SPLUS was adopted to analyze data and correction of the SPLUS program in unit tests are also proposed. To apply these two test methods in high frequency data, we
quoted the library, HFlibrary designed by Yan and Zivot in 2003 for preliminary data analysis and propose a new library HFanalysis, which can be used in correcting high frequency data (excluding N.A. value, sorting transactions and retrieve a certain time of
transactions), obtaining equi-distanced time intervals and testing for unit root and long memory properties. In additions, we apply this proposed library to simulate the power of traditional unit root methods such as the ADF test and long memory test method such as the R/S and to perform an empirical study. Finally, we explore the power of the ADF for testing data simulated from a threshold unit root model and simulate the percentiles of the null distribution of
the following threshold unit root tests: WALD, LM, LR and Wλ.
目次 Table of Contents
1 前言 1
2 文獻回顧 3
2.1 單根檢定 3
2.2 長記憶檢定 7
3 函式庫介紹 11
3.1 HFlibrary函式庫 11
3.2 HFanalysis函式庫 16
4 高頻資料的單根檢定和長記憶檢定 20
4.1 原始資料的型態 20
4.2 資料處理和時間等距化的過程與指令 20
4.3 高頻資料之單根檢定與長記憶檢定 21
4.3.1 利用處理後的資料作單根檢定 21
4.3.2 利用處理後的資料作長記憶檢定 22
4.4 非高頻資料之單根檢定與長記憶檢定 22
5 模擬與實證分析 23
5.1 模擬分析 23
5.1.1 單根檢定之模擬 23
5.1.2 長記憶檢定之模擬 25
5.2 實證分析 25
5.2.1 單根檢定之實證分析 26
5.2.2 長記憶檢定之實證分析 27
6 門檻單根檢定的模擬 27
6.1 有門檻之一般單根檢定模擬 27
6.2 門檻單根檢定檢定統計量的模擬 28
7 結論 29
附錄 31
附錄.A 一般指令查詢 31
參考文獻 References
[1] Anderson, T. G., (2000) ”Some Reflections on Analysis of High-Frequency Data,” Journal of Busisness and Economic Statistics, 18, 146-153.
[2] Bec, F., A. Guay and E. Guerre (2006) ”Adaptive consistent unit root tests based on autoregressive threshold model,” Working Paper, CREST-ENSAE, France.
[3] Campbell, J. Y. , A. W. Lo, A. C. MacKinlay, R. F. Whitelaw(1997), ”The Econometrics of Financial Markets,” Princeton University Press, New Jersey.
[4] Dickey, D. and W. Fuller, (1979) ”Distribution of the Estimators for Autoregressive Time Series with a Unit Root,” Journal of the American Statistical Association, 74, 427-431.
[5] Elliot, G., T. J. Rothenberg, and J. H. Stock (1996) ”Efficient Tests for an autoregressive
Unit Root,” Econometrica, 64, 813-836.
[6] Goodhart, C. A. E. , and M. , O’Hara, 1997). ”High Frequency Data in Financial
Markets: Issues and Applications,” Journal of Empirical Finance, 4, 73-114.
[7] Granger, C. W. J. and P.E. NewBold(1974). ”Spurious Regression in Economics,”
Journal of Econometrics, 2, 111-120.
[8] Granger, C. W. J. and R. Joyeux, (1980). ”An introduction to Long-Memory Seres Models and Factional Differencing,” Journal of Time Series Analysis, 1, 15-29.
[9] Hosking, J. R. M. (1981). ”Factional Differencing,” Biometrika, 68, 165-176.
[10] Hurst, H. E. (1951). ”Long Term Storage Capacity of Reservoirs,” Transactions of the
American Society of Civil Engineers, 116, 770-799.
[11] Kapetaniosa, G., Y. Shin, and A. Snell, (2003). ”Testing for a unit root in the nonlinear
STAR framework,” Journal of Econometrics, 112, 359-379.
[12] Kwiatkowski, D., P. C. B. Phillips , P. Svhmidt and Y. Shin (1992) ”Testing The Null Hypothesis of Stationary Against the Alternative of a Unit Root,” Journal of Econometrics, 54, 159-178.
[13] Leybourne, S. , P. Newbold and D. Vougas (1998). ”Unit roots and smooth transitions”
University of Nottingham, 19, 83-97.
[14] Mandelbrot, B. B. (1975). ”Limit Theorems on the self-normalized range for weakly and strongly dependent processes,” Zeitsschrift fur Wahrscheinlichkeitstheorie und
verwandte Gebiete, 31, 271-285.
[15] Ng, S. and P. Perron (2001) ”Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power,” Econometrica, 69, 1519-1554.
[16] Phillips, P. C. B. (1987). ”Time Series Regression With a Unit Root,” Econometrica,
55, 227-301.
[17] Phillips, P. C. B. and P. Perron (1988). ”Testing for Unit Roots in Time Series Regression,” Biometrika, 75, 335-346.
[18] Said, S.E. and D. Dickey (1984)”Testing for unit Roots in Autoregressive Moving-Average Models with Unknown Order,” Biometrika, 71, 599-607.
[19] Schwert, W. (1989)”Test for Unit Roots: A Monte Carlo Investigation,” Journal of Business and Economic Statistics, 7, 147-159.
[20] Tsay, R. A., (2001)”Analysis of Finanvcial Time Series,” John Wiley & Sons, Inc.
[21] Yan, B. and E. Zivot (2003) ”Analysis of High Frequency Financial Data with S-Plus,”Department of Economics, University of Washington.
[22] Zivot E. and Donald W. K. Andrews, (1992)”Further Evidence on the Great Crash,
the Oil-Price Shock, and the Unit-Root Hypothesis,” Journal of Business & Economic
Statistics, 10, 251-270.
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:校內校外均不公開 not available
開放時間 Available:
校內 Campus:永不公開 not available
校外 Off-campus:永不公開 not available

您的 IP(校外) 位址是 54.224.52.210
論文開放下載的時間是 校外不公開

Your IP address is 54.224.52.210
This thesis will be available to you on Indicate off-campus access is not available.

紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 已公開 available

QR Code