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

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.

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Abstract

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.

Item Type:Conference or Workshop Item (Paper)
Academic Subject One:Academic Department - Management And Humanities - Business and Marketing
Departments / MOR / COE:Departments > Management & Humanities
ID Code:11579
Deposited By: Dr. Fong-Woon Lai
Deposited On:28 Apr 2015 02:54
Last Modified:28 Apr 2015 02:54

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