The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board
The commonly used Maximum Likelihood Estimator (MLE) to estimate the parameters of a time series model requires that the process is normally distributed. However, in real situations, many processes are not normal and have a heavy tail distribution. Hence, the aim of this study is to propose using a...
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Asian Network for Scientific Information
2010
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Online Access: | http://psasir.upm.edu.my/id/eprint/17259/1/The%20performance%20of%20bootstrapping%20autoregressive%20AR.pdf http://psasir.upm.edu.my/id/eprint/17259/ https://scialert.net/abstract/?doi=jas.2010.2101.2107 |
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my.upm.eprints.172592019-10-02T06:23:01Z http://psasir.upm.edu.my/id/eprint/17259/ The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board Midi, Habshah Zamzuri, Zamira Hasanah The commonly used Maximum Likelihood Estimator (MLE) to estimate the parameters of a time series model requires that the process is normally distributed. However, in real situations, many processes are not normal and have a heavy tail distribution. Hence, the aim of this study is to propose using a distribution free bootstrap method for parameter estimations, when the assumption of normality is not met. The performance of the Bootstrap Estimates (BE) and the MLE estimates of the AR (9) process were then investigated using the Malaysian Opening Price for Second Board data and simulation study. The empirical results indicate that the BE is reasonably close to the MLE estimates, hence, can be established as one reliable alternative approach to the MLE estimates. Asian Network for Scientific Information 2010 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/17259/1/The%20performance%20of%20bootstrapping%20autoregressive%20AR.pdf Midi, Habshah and Zamzuri, Zamira Hasanah (2010) The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board. Journal of Applied Sciences, 10 (18). pp. 2101-2107. ISSN 1812-5654; ESSN: 1812-5662 https://scialert.net/abstract/?doi=jas.2010.2101.2107 10.3923/jas.2010.2101.2107 |
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The commonly used Maximum Likelihood Estimator (MLE) to estimate the parameters of a time series model requires that the process is normally distributed. However, in real situations, many processes are not normal and have a heavy tail distribution. Hence, the aim of this study is to propose using a distribution free bootstrap method for parameter estimations, when the assumption of normality is not met. The performance of the Bootstrap Estimates (BE) and the MLE estimates of the AR (9) process were then investigated using the Malaysian Opening Price for Second Board data and simulation study. The empirical results indicate that the BE is reasonably close to the MLE estimates, hence, can be established as one reliable alternative approach to the MLE estimates. |
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Midi, Habshah Zamzuri, Zamira Hasanah |
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Midi, Habshah Zamzuri, Zamira Hasanah The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board |
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Midi, Habshah Zamzuri, Zamira Hasanah |
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Midi, Habshah |
title |
The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board |
title_short |
The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board |
title_full |
The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board |
title_fullStr |
The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board |
title_full_unstemmed |
The performance of bootstrapping autoregressive AR(9) process on the Malaysian opening price for second board |
title_sort |
performance of bootstrapping autoregressive ar(9) process on the malaysian opening price for second board |
publisher |
Asian Network for Scientific Information |
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2010 |
url |
http://psasir.upm.edu.my/id/eprint/17259/1/The%20performance%20of%20bootstrapping%20autoregressive%20AR.pdf http://psasir.upm.edu.my/id/eprint/17259/ https://scialert.net/abstract/?doi=jas.2010.2101.2107 |
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