A DFS Model for Forecasting Stock Price
Authors
Xiaolu Li, Hanghang Zhao, Kaiqiang Zheng, Shuaishuai Sun
Corresponding Author
Xiaolu Li
Available Online May 2016.
- DOI
- 10.2991/wartia-16.2016.334How to use a DOI?
- Keywords
- DFS model, time series model, combination forecast model, wavelet analysis, Fourier transform, fitting analysis
- Abstract
Currently, forecasting stock price is the hotter topic for achieving the smallest lost in investment. However, the previous stock price forecasting model practically cannot satisfy the requirement of accuracy. To raise the forecast accuracy, a decomposition-forecast- synthesis (DFS) model is proposed by this paper, based on the analysis of the characteristics of the stock price time series, combined with the established single stock price prediction model, for instance, time series model, grey prediction model, neural network prediction model, etc.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaolu Li AU - Hanghang Zhao AU - Kaiqiang Zheng AU - Shuaishuai Sun PY - 2016/05 DA - 2016/05 TI - A DFS Model for Forecasting Stock Price BT - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications PB - Atlantis Press SP - 1676 EP - 1681 SN - 2352-5401 UR - https://doi.org/10.2991/wartia-16.2016.334 DO - 10.2991/wartia-16.2016.334 ID - Li2016/05 ER -