具有EGARCH误差项和NGARCH误差项时序的单位根检验

文档编号:XXLW092 文档字数:8383,页数:22

摘     要
 ARCH模型是一种动态非线性的时间序列模型，它反映了经济变量之间的特殊的不确定形式：方差随时间变化而变化。作为一种全新的理论，ARCH模型在近年来取得了极为迅速的发展，已被广泛应用于经济金融领域。具有GARCH类的单位根过程对常规ADF检验临界值的影响程度如何，是进行ADF检验时需要认真分析的问题，因而备受关注。由于GARCH族模型中，较多的金融数据中存在波动的杠杆效应和滞后系数对波动的影响，同时GARCH和ARCH还不足以描述很多时间序列，EGARCH和NGARCH模型能较好地描述金融时间序列，因而EGARCH-error和NGARCH-error的单位根检验值得关注。
 本文用eviews软件通过Monte Carlo随机模拟在有限样本条件下通过加权最小二乘法讨论了在EGARCH和NGARCH条件下的单位根检验，探索性地分析研究误差项为正态分布时检验统计量的临界值及其实际扭曲水平和势，并且给出滞后阶数对其检验统计量的影响。在有限样本的情况下，通过随机模拟，考察了扰动项的条件方差时变时的单位根检验，用加权最小二乘法考察ADF检验的统计量和统计量在不同情况下哪个更有效。
关键词：    ARCH  单位根检验  检验统计量 

Abstract
 ARCH model is a kind of dynamic non-linear time series model. It reflects a special feature of economic variables time-varying variances. As a new theory, ARCH model has caused extensive interests of economists and has been developed very fast since it came into being. The class has GARCH unit root test of conventional ADF degree of influence how critical is to analyze seriously ADF test, and attention.. Because GARCH model, more financial data exist in the fluctuation of leverage and lag coefficient of the ARCH and GARCH, at the same time, to describe a lot of time sequence, NGARCH and EGARCH model can describe the financial time series, and NGARCH and EGARCH as freely though they and the unit root test - as freely though they concern.
  In this text，using the Monte Carlo eviews software through random simulation in limited samples through weighted least-square method are discussed in NGARCH and EGARCH under the condition of unit root test, exploratory analysis for normal distribution error when the critical test statistics and actual and potential, and the level of distortion are lagging order number on the test statistics. In the cases of limited samples, through random simulation, the disturbance of conditional variances of time-varying unit root test.
Keywords： ARCH; Unit root test; Test statistics

目  录
中文摘要 Ⅰ
英文摘要 Ⅱ
目  录 Ⅲ
第一章  绪论 1
1.1研究动机与目的 1
1.2 研究背景 1
1.3 研究方法 2
1.4 文档内容概述 2
第二章 EGARCH和NGARCH模型 3
2.1 ARCH模型简介 3
2.2泛函中心极限定理 4
2.3 单位根检验 7
 2.3.1 关于单位根检验 7
 2.3.2 EGARCH条件下的单位根检验 7
 2.3.3 NGARCH条件下的单位根检验 8
第三章 代入数据得出各自条件下的统计量的临界值表 10
3.1 EGARCH条件下的统计量的临界值表 10
3.2 NGARCH条件下的统计量的临界值表 13
第四章 结论 17
致  谢 18
参考文献 19

相关论文