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)
Departments / MOR / COE: Departments > Management & Humanities
Depositing User: Dr. Fong-Woon Lai
Date Deposited: 28 Apr 2015 02:54
Last Modified: 28 Apr 2015 02:54
URI: http://scholars.utp.edu.my/id/eprint/11579

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