Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)

Stock Price Short-term Forecasting Based On GARCH Model

Authors
Wanle Chi
Corresponding Author
Wanle Chi
Available Online March 2018.
DOI
https://doi.org/10.2991/mecae-18.2018.7How to use a DOI?
Keywords
Forecasting, Stock Price, GARCH.
Abstract
Using the stock price data to set up a sequence to explain the relationship of stock price data, the future stock price can be forecasted. This paper conducts the real modeling research on the shanghai composite index utilized the GARCH-class models. The results of this paper had indicated that stock price undulation in the Shanghai Stock market has the obvious GARCH effect. The condition variance sequence of returns rate is stationary, the GARCH model has the predictability. And GARCH (1, 1) model may well in the fitting and the forecast the shanghai stock price index. This simulation model may realize the short-term high accuracy to forecast well that. The forecast value of shanghai index was closer to actual value, indicating that the GARCH model in the paper was a certain accuracy. This paper was helpful to dodge the risk regarding, and develop the profit space for the investors.
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Proceedings
2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
Part of series
Advances in Engineering Research
Publication Date
March 2018
ISBN
978-94-6252-493-4
DOI
https://doi.org/10.2991/mecae-18.2018.7How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wanle Chi
PY  - 2018/03
DA  - 2018/03
TI  - Stock Price Short-term Forecasting Based On GARCH Model
BT  - 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/mecae-18.2018.7
DO  - https://doi.org/10.2991/mecae-18.2018.7
ID  - Chi2018/03
ER  -