Testing the Intercept of a Balanced Predictive Regression Model
Testing predictability is known to be an important issue for the balanced predictive regression model. Some unified testing statistics of desirable properties have been proposed, though their validity depends on a predefined assumption regarding whether or not an intercept term nevertheless exists....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/11/1594 |
| _version_ | 1797468398396899328 |
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| author | Qijun Wang Xiaohui Liu Yawen Fan Ling Peng |
| author_facet | Qijun Wang Xiaohui Liu Yawen Fan Ling Peng |
| author_sort | Qijun Wang |
| collection | DOAJ |
| description | Testing predictability is known to be an important issue for the balanced predictive regression model. Some unified testing statistics of desirable properties have been proposed, though their validity depends on a predefined assumption regarding whether or not an intercept term nevertheless exists. In fact, most financial data have endogenous or heteroscedasticity structure, and the existing intercept term test does not perform well in these cases. In this paper, we consider the testing for the intercept of the balanced predictive regression model. An empirical likelihood based testing statistic is developed, and its limit distribution is also derived under some mild conditions. We also provide some simulations and a real application to illustrate its merits in terms of both size and power properties. |
| first_indexed | 2024-03-09T19:05:54Z |
| format | Article |
| id | doaj.art-e39e59c83e234a58bdec0dda80255e93 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T19:05:54Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-e39e59c83e234a58bdec0dda80255e932023-11-24T04:36:47ZengMDPI AGEntropy1099-43002022-11-012411159410.3390/e24111594Testing the Intercept of a Balanced Predictive Regression ModelQijun Wang0Xiaohui Liu1Yawen Fan2Ling Peng3School of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaSchool of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaSchool of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaSchool of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaTesting predictability is known to be an important issue for the balanced predictive regression model. Some unified testing statistics of desirable properties have been proposed, though their validity depends on a predefined assumption regarding whether or not an intercept term nevertheless exists. In fact, most financial data have endogenous or heteroscedasticity structure, and the existing intercept term test does not perform well in these cases. In this paper, we consider the testing for the intercept of the balanced predictive regression model. An empirical likelihood based testing statistic is developed, and its limit distribution is also derived under some mild conditions. We also provide some simulations and a real application to illustrate its merits in terms of both size and power properties.https://www.mdpi.com/1099-4300/24/11/1594balanced predictive regression modelinterceptempirical likelihoodstationarynon-stationary |
| spellingShingle | Qijun Wang Xiaohui Liu Yawen Fan Ling Peng Testing the Intercept of a Balanced Predictive Regression Model Entropy balanced predictive regression model intercept empirical likelihood stationary non-stationary |
| title | Testing the Intercept of a Balanced Predictive Regression Model |
| title_full | Testing the Intercept of a Balanced Predictive Regression Model |
| title_fullStr | Testing the Intercept of a Balanced Predictive Regression Model |
| title_full_unstemmed | Testing the Intercept of a Balanced Predictive Regression Model |
| title_short | Testing the Intercept of a Balanced Predictive Regression Model |
| title_sort | testing the intercept of a balanced predictive regression model |
| topic | balanced predictive regression model intercept empirical likelihood stationary non-stationary |
| url | https://www.mdpi.com/1099-4300/24/11/1594 |
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