Xue, Meiyu and Lai, Choi-Hong ORCID: 0000-0002-7558-6398 (2018) From time series analysis to a modified ordinary differential equation. Journal of Algorithms and Computational Technology, 12 (2). pp. 85-90. ISSN 1748-3018 (Print), 1748-3026 (Online) (doi:https://doi.org/10.1177/1748301817751480)

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Abstract

In understanding Big Data, people are interested to obtain the trend and dynamics of a given set of temporal data, which in turn can be used to predict possible futures. This paper examines a time series analysis method and an ordinary differential equation approach in modeling the price movements of petroleum price and of three different bank stock prices over a time frame of three years. Computational tests consist of a range of data fitting models in order to understand the advantages and disadvantages of these two approaches. A modified ordinary differential equation model, with different forms of polynomials and periodic functions, is proposed. Numerical tests demonstrated the advantage of the modified ordinary differential equation approach. Computational properties of the modified ordinary differential
equation are studied.

Item Type:	Article
Additional Information:	Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Uncontrolled Keywords:	Time series analysis, autoregressive integrated moving average, ordinary differential equation, mean absolute percentage error.
Subjects:	Q Science > QA Mathematics
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Last Modified:	04 Mar 2022 13:07
URI:	http://gala.gre.ac.uk/id/eprint/19724

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