Stock price prediction based on technical indicators with soft computing models
- Title
- Stock price prediction based on technical indicators with soft computing models
- Creator
- Kumar Chandar S.
- Description
- Stock market prediction is a very tough task in the finance world. Since stock prices are dynamic, noisy, non-scalable, non-linear, non-parametric and complicated. In recent years, soft computing techniques are used for developing stock prediction model. The main focus of this study is to develop and compare the efficiency of the three different soft computing techniques for predicting the intraday price of individual stocks. The proposed models are based on Time Delay Neural Network (TDNN), Radial Basis Function Neural Network (RBFNN) and Back Propagation Neural Network (BPNN). The predictive models are developed using technical indicators. Sixteen technical indicators were calculated from the historical price and used as inputs of the developed models. Historical prices from 01/01/2018 to 28/02/2018, where the time interval between samples is one minute, are utilized for developing models. The performance of the proposed models is evaluated by measuring some metrics. Also, this study compares the results with other existing models. The experimental result revealed that the BPNN outperforms TDNN, RBFNN as well as other existing models considered for comparison. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.
- Source
- Advances in Intelligent Systems and Computing, Vol-1200 AISC, pp. 685-699.
- Date
- 2021-01-01
- Publisher
- Springer
- Subject
- Back Propagation Neural Network (BPNN); Intraday stock price prediction; MAE; MAPE; Technical indicators; Time Delay Neural Network (TDNN)
- Coverage
- Kumar Chandar S., School of Business and Management, CHRIST (Deemed to Be University), Bangalore, India, Department of Management Studies, Christ University, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISSN: 21945357; ISBN: 978-303051858-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Kumar Chandar S., “Stock price prediction based on technical indicators with soft computing models,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20629.