Robust testing for explosive behavior with strongly dependent errors
A heteroskedasticity-autocorrelation robust (HAR) test statistic is proposed to test for the presence of explosive roots in financial or real asset prices when the equation errors are strongly dependent. Limit theory for the test statistic is developed and extended to heteroskedastic models. The new...
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sg-smu-ink.soe_research-36302024-07-04T01:47:30Z Robust testing for explosive behavior with strongly dependent errors LUI, Yiu Lim PHILLIPS, Peter C. B. YU, Jun A heteroskedasticity-autocorrelation robust (HAR) test statistic is proposed to test for the presence of explosive roots in financial or real asset prices when the equation errors are strongly dependent. Limit theory for the test statistic is developed and extended to heteroskedastic models. The new test has stable size properties unlike conventional test statistics that typically lead to size distortion and inconsistency in the presence of strongly dependent equation errors. The new procedure can be used to consistently time-stamp the origination and termination of an explosive episode under similar conditions of long memory errors. Simulations are conducted to assess the finite sample performance of the proposed test and estimators. An empirical application to the S&P 500 index highlights the usefulness of the proposed proceduresin practical work. 2022-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2631 https://ink.library.smu.edu.sg/context/soe_research/article/3630/viewcontent/TestStrongDependence23_A5_jun_allen.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University HAR test Long memory Explosiveness Unit root test S&P 500 Econometrics |
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HAR test Long memory Explosiveness Unit root test S&P 500 Econometrics LUI, Yiu Lim PHILLIPS, Peter C. B. YU, Jun Robust testing for explosive behavior with strongly dependent errors |
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A heteroskedasticity-autocorrelation robust (HAR) test statistic is proposed to test for the presence of explosive roots in financial or real asset prices when the equation errors are strongly dependent. Limit theory for the test statistic is developed and extended to heteroskedastic models. The new test has stable size properties unlike conventional test statistics that typically lead to size distortion and inconsistency in the presence of strongly dependent equation errors. The new procedure can be used to consistently time-stamp the origination and termination of an explosive episode under similar conditions of long memory errors. Simulations are conducted to assess the finite sample performance of the proposed test and estimators. An empirical application to the S&P 500 index highlights the usefulness of the proposed proceduresin practical work. |
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LUI, Yiu Lim PHILLIPS, Peter C. B. YU, Jun |
author_facet |
LUI, Yiu Lim PHILLIPS, Peter C. B. YU, Jun |
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LUI, Yiu Lim |
title |
Robust testing for explosive behavior with strongly dependent errors |
title_short |
Robust testing for explosive behavior with strongly dependent errors |
title_full |
Robust testing for explosive behavior with strongly dependent errors |
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Robust testing for explosive behavior with strongly dependent errors |
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Robust testing for explosive behavior with strongly dependent errors |
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robust testing for explosive behavior with strongly dependent errors |
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Institutional Knowledge at Singapore Management University |
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2022 |
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https://ink.library.smu.edu.sg/soe_research/2631 https://ink.library.smu.edu.sg/context/soe_research/article/3630/viewcontent/TestStrongDependence23_A5_jun_allen.pdf |
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