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An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data

Financial data is characterized as non-linearity, chaotic in nature and volatility thus making the process of forecasting cumber- some, hence a successful forecasting model must be able to capture long- term dependencies from chaotic data. In this study, an ensemble model, called UKF-NARX, consi...

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Main Author: Lai, Fong Woon
Format: Conference or Workshop Item
Published: 2014
Online Access:http://eprints.utp.edu.my/11579/1/Vivian-iconip14_Nov2014.pdf
http://eprints.utp.edu.my/11579/
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spelling my.utp.eprints.115792015-04-28T02:54:12Z An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data Lai, Fong Woon Financial data is characterized as non-linearity, chaotic in nature and volatility thus making the process of forecasting cumber- some, hence a successful forecasting model must be able to capture long- term dependencies from chaotic data. In this study, an ensemble model, called UKF-NARX, consists of unscented kalman �lter and parallel non- linear autoregressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic �nancial forecasting. The proposed ensemble model is compared with the conventional non-linear autoregressive network and �nancial static forecasting model employed by �nancial analysts when applying in multi-step-ahead forecasting. Ex- perimental results on Burssa Malaysia KLCI show that the proposed ensemble model outperforms the other two commonly used models. 2014 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/11579/1/Vivian-iconip14_Nov2014.pdf Lai, Fong Woon (2014) An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data. In: The 21st International Conference on Neural Information Processing, ICONIP 2014. http://eprints.utp.edu.my/11579/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description Financial data is characterized as non-linearity, chaotic in nature and volatility thus making the process of forecasting cumber- some, hence a successful forecasting model must be able to capture long- term dependencies from chaotic data. In this study, an ensemble model, called UKF-NARX, consists of unscented kalman �lter and parallel non- linear autoregressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic �nancial forecasting. The proposed ensemble model is compared with the conventional non-linear autoregressive network and �nancial static forecasting model employed by �nancial analysts when applying in multi-step-ahead forecasting. Ex- perimental results on Burssa Malaysia KLCI show that the proposed ensemble model outperforms the other two commonly used models.
format Conference or Workshop Item
author Lai, Fong Woon
spellingShingle Lai, Fong Woon
An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data
author_facet Lai, Fong Woon
author_sort Lai, Fong Woon
title An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data
title_short An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data
title_full An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data
title_fullStr An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data
title_full_unstemmed An Ensembel Model for Modelling Chaotic Behaviour of Bursa Malaysia Time Series Data
title_sort ensembel model for modelling chaotic behaviour of bursa malaysia time series data
publishDate 2014
url http://eprints.utp.edu.my/11579/1/Vivian-iconip14_Nov2014.pdf
http://eprints.utp.edu.my/11579/
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score 13.211869

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