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- Title
From time series analysis to a modified ordinary differential equation.
- Authors
Xue, Meiyu; Lai, Choi-Hong
- 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.
- Subjects
TIME series analysis; ORDINARY differential equations; BIG data; POLYNOMIALS; COMPUTATIONAL complexity
- Publication
Journal of Algorithms & Computational Technology, 2018, Vol 12, Issue 2, p85
- ISSN
1748-3018
- Publication type
Article
- DOI
10.1177/1748301817751480