{"title":"面板分数阶Ornstein-Uhlenbeck过程最小二乘检验的局部幂","authors":"Katsuto Tanaka, Weilin Xiao, Jun Yu","doi":"10.1111/jtsa.12777","DOIUrl":null,"url":null,"abstract":"<p>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 (<span></span><math>\n <mrow>\n <mi>α</mi>\n </mrow></math>) within a panel fractional Ornstein-Uhlenbeck process, based on the least squares estimator of <span></span><math>\n <mrow>\n <mi>α</mi>\n </mrow></math>. This method incorporates three distinct test statistics based on the Hurst parameter (<span></span><math>\n <mrow>\n <mi>H</mi>\n </mrow></math>), which can take values in the range of <span></span><math>\n <mrow>\n <mo>(</mo>\n <mn>1</mn>\n <mo>/</mo>\n <mn>2</mn>\n <mo>,</mo>\n <mn>1</mn>\n <mo>)</mo>\n </mrow></math>, be equal to <span></span><math>\n <mrow>\n <mn>1</mn>\n <mo>/</mo>\n <mn>2</mn>\n </mrow></math>, or fall within the interval of <span></span><math>\n <mrow>\n <mo>(</mo>\n <mn>0</mn>\n <mo>,</mo>\n <mn>1</mn>\n <mo>/</mo>\n <mn>2</mn>\n <mo>)</mo>\n </mrow></math>. The null hypothesis corresponds to <span></span><math>\n <mrow>\n <mi>α</mi>\n <mo>=</mo>\n <mn>0</mn>\n </mrow></math>. Based on a panel of continuous records of observations, the null asymptotic distributions are obtained when the time span (<span></span><math>\n <mrow>\n <mi>T</mi>\n </mrow></math>) is fixed and the number of cross sections (<span></span><math>\n <mrow>\n <mi>N</mi>\n </mrow></math>) goes to infinity. The power function of the tests is obtained under the local alternative where <span></span><math>\n <mrow>\n <mi>α</mi>\n </mrow></math> is close to zero in the order of <span></span><math>\n <mrow>\n <mn>1</mn>\n <mo>/</mo>\n <mo>(</mo>\n <mi>T</mi>\n <msqrt>\n <mrow>\n <mi>N</mi>\n </mrow>\n </msqrt>\n <mo>)</mo>\n </mrow></math>. 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 <span></span><math>\n <mrow>\n <mi>N</mi>\n </mrow></math> goes to infinity.</p>","PeriodicalId":49973,"journal":{"name":"Journal of Time Series Analysis","volume":"46 5","pages":"997-1023"},"PeriodicalIF":1.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jtsa.12777","citationCount":"0","resultStr":"{\"title\":\"Local powers of least-squares-based test for panel fractional Ornstein–Uhlenbeck process\",\"authors\":\"Katsuto Tanaka, Weilin Xiao, Jun Yu\",\"doi\":\"10.1111/jtsa.12777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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 (<span></span><math>\\n <mrow>\\n <mi>α</mi>\\n </mrow></math>) within a panel fractional Ornstein-Uhlenbeck process, based on the least squares estimator of <span></span><math>\\n <mrow>\\n <mi>α</mi>\\n </mrow></math>. This method incorporates three distinct test statistics based on the Hurst parameter (<span></span><math>\\n <mrow>\\n <mi>H</mi>\\n </mrow></math>), which can take values in the range of <span></span><math>\\n <mrow>\\n <mo>(</mo>\\n <mn>1</mn>\\n <mo>/</mo>\\n <mn>2</mn>\\n <mo>,</mo>\\n <mn>1</mn>\\n <mo>)</mo>\\n </mrow></math>, be equal to <span></span><math>\\n <mrow>\\n <mn>1</mn>\\n <mo>/</mo>\\n <mn>2</mn>\\n </mrow></math>, or fall within the interval of <span></span><math>\\n <mrow>\\n <mo>(</mo>\\n <mn>0</mn>\\n <mo>,</mo>\\n <mn>1</mn>\\n <mo>/</mo>\\n <mn>2</mn>\\n <mo>)</mo>\\n </mrow></math>. The null hypothesis corresponds to <span></span><math>\\n <mrow>\\n <mi>α</mi>\\n <mo>=</mo>\\n <mn>0</mn>\\n </mrow></math>. Based on a panel of continuous records of observations, the null asymptotic distributions are obtained when the time span (<span></span><math>\\n <mrow>\\n <mi>T</mi>\\n </mrow></math>) is fixed and the number of cross sections (<span></span><math>\\n <mrow>\\n <mi>N</mi>\\n </mrow></math>) goes to infinity. The power function of the tests is obtained under the local alternative where <span></span><math>\\n <mrow>\\n <mi>α</mi>\\n </mrow></math> is close to zero in the order of <span></span><math>\\n <mrow>\\n <mn>1</mn>\\n <mo>/</mo>\\n <mo>(</mo>\\n <mi>T</mi>\\n <msqrt>\\n <mrow>\\n <mi>N</mi>\\n </mrow>\\n </msqrt>\\n <mo>)</mo>\\n </mrow></math>. 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 <span></span><math>\\n <mrow>\\n <mi>N</mi>\\n </mrow></math> goes to infinity.</p>\",\"PeriodicalId\":49973,\"journal\":{\"name\":\"Journal of Time Series Analysis\",\"volume\":\"46 5\",\"pages\":\"997-1023\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jtsa.12777\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Time Series Analysis\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jtsa.12777\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Time Series Analysis","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jtsa.12777","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
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 () within a panel fractional Ornstein-Uhlenbeck process, based on the least squares estimator of . This method incorporates three distinct test statistics based on the Hurst parameter (), which can take values in the range of , be equal to , or fall within the interval of . The null hypothesis corresponds to . Based on a panel of continuous records of observations, the null asymptotic distributions are obtained when the time span () is fixed and the number of cross sections () goes to infinity. The power function of the tests is obtained under the local alternative where is close to zero in the order of . 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 goes to infinity.
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.