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A new procedure in stock market forecasting based on fuzzy random auto-regression time series model

Efendi, Riswan and Arbaiy, Nureize and Mat Deris, Mustafa (2018) A new procedure in stock market forecasting based on fuzzy random auto-regression time series model. Information Sciences, 441. pp. 113-132. ISSN 00200255

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Various models used in stock market forecasting presented have been classified accord- ing to the data preparation, forecasting methodology, performance evaluation, and perfor- mance measure. However, these models have not sufficiently discussed in data prepara- tion to overcome randomness, as well as uncertainty and volatility of stock prices issues in achieving high forecasting accuracy. Therefore, the focus of this paper is the data prepa- ration procedure of triangular fuzzy number to build an improved fuzzy random auto- regression model using non-stationary stock market data for forecasting purposes. The im- proved forecasting model considers two types of input, which are data with low-high and single point values of stock market prices. Even though, low-high data present variabil- ity and volatility in nature, the single data has to be form in symmetry left-right spread to present variability and standard error. Then, expectations and variances, confidence- intervals of fuzzy random data are constructed for fuzzy input-output data. By using the input-output data and simplex approach, parameters of the model can be estimated. In this study, some real data sets were used to represent both types of inputs, which are the Kuala Lumpur stock exchange and Alabama University enrollment. The study found that variability and spread adjustment are important factors in data preparation to improve ac- curacy of the fuzzy random auto-regression model.

Item Type: Article
Uncontrolled Keywords: Low-high procedure; left-right spread; fuzzy random variable; auto-regression model; stock market
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 31 Jul 2019 00:58
Last Modified: 31 Jul 2019 00:58
URI: http://eprints.uthm.edu.my/id/eprint/11350
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