面板分数阶Ornstein-Uhlenbeck过程最小二乘检验的局部幂

IF 1 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Katsuto Tanaka, Weilin Xiao, Jun Yu
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引用次数: 0

摘要

近年来,在识别金融资产价格泡沫方面取得了重大进展,特别是通过开发具有分数积分误差的时间序列单位根检验和面板单位根检验。本文介绍了一种基于α的最小二乘估计的创新方法,用于评估面板分数阶Ornstein-Uhlenbeck过程中持久性参数(α)的符号。该方法结合了基于Hurst参数(H)的三种不同的检验统计量,其取值范围为(1 / 2,1),等于1 / 2,或者落在(0,1 / 2)区间内。零假设对应于α = 0。基于一组连续的观测记录,当时间跨度(T)固定且截面数(N)趋于无穷时,得到零渐近分布。在α接近于0的1 / (tn)阶的局部替代下,得到了试验的幂函数。这种替代方案涵盖了从爆炸侧偏离单位根假设的情况,从而可以在气泡试验中计算较低的功率。假设检验问题和局部幂函数也被考虑,当一组离散采样的观测值在连续极限下可用,即采样间隔缩小到零,然后N趋于无穷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Local powers of least-squares-based test for panel fractional Ornstein–Uhlenbeck process

Local powers of least-squares-based test for panel fractional Ornstein–Uhlenbeck process

In recent years, significant advancements have been made in the field of identifying financial asset price bubbles, particularly through the development of time-series unit-root tests featuring fractionally integrated errors and panel unit-root tests. This study introduces an innovative approach for assessing the sign of the persistence parameter ( α ) within a panel fractional Ornstein-Uhlenbeck process, based on the least squares estimator of α . This method incorporates three distinct test statistics based on the Hurst parameter ( H ), which can take values in the range of ( 1 / 2 , 1 ) , be equal to 1 / 2 , or fall within the interval of ( 0 , 1 / 2 ) . The null hypothesis corresponds to α = 0 . Based on a panel of continuous records of observations, the null asymptotic distributions are obtained when the time span ( T ) is fixed and the number of cross sections ( N ) goes to infinity. The power function of the tests is obtained under the local alternative where α is close to zero in the order of 1 / ( T N ) . This alternative covers the departure from the unit root hypothesis from the explosive side, enabling the calculation of lower power in bubble tests. The hypothesis testing problem and the local power function are also considered when a panel of discrete-sampled observations is available under a sequential limit, that is, the sampling interval shrinks to zero followed by the N goes to infinity.

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来源期刊
Journal of Time Series Analysis
Journal of Time Series Analysis 数学-数学跨学科应用
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering. The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world''s leading experts in Time Series Analysis.
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