Title: Finite mixture model: a comparison method for nonlinear time series data

Authors: Seuk Yen Phoong; Mohd Tahir Ismail; Seuk Wai Phoong; Rosmanjawati Binti Abdul Rahman

Addresses: Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim, Perak, Malaysia ' School of Mathematical Sciences, University Science Malaysia, 11800 Penang, Malaysia ' Faculty of Business and Finance, University Tunku Abdul Rahman, 31900 Kampar, Perak, Malaysia ' School of Mathematical Sciences, University Science Malaysia, 11800 Penang, Malaysia

Abstract: Global Financial Crisis 2009 caused the finance collapse in Asia countries. The crisis leads to the economic and financial time series confronted with structural changes or jumps during the time. Stock price and exchange rate play a crucial role as symbol of development for a country's economy. Hence, it is critical to investigate the relationship between these two variables. A two-component finite mixture model is used to examine this issue. In spite of that, maximum likelihood estimation and Bayesian method are applied to fit the finite mixture model. Additionally, this paper concerns on investigating the developing Asian countries since they are easily affected by economic changes of the western countries. In relation to the results, there is a positive relation between the exchange rate and stock price for Malaysia, Thailand, Philippines and Indonesia. Also, this paper highlighted that Bayesian method is superior to maximum likelihood in modelling nonlinear time series data although both methods provided roughly equal results.

Keywords: global financial crisis; finance collapse; structural changes; stock prices; exchange rates; finite mixture model; maximum likelihood estimation; MLE; Bayesian method; developing countries; Asia; nonlinear time series data; modelling; Malaysia; Thailand; Philippines; Indonesia.

DOI: 10.1504/IJCSM.2016.078684

International Journal of Computing Science and Mathematics, 2016 Vol.7 No.4, pp.381 - 393

Received: 04 Apr 2014
Accepted: 09 Apr 2015

Published online: 01 Sep 2016 *

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