Comparison of harmony search derivatives for artificial neural network parameter optimisation: stock price forecasting
by Mehmet Özçalıcı; Ayşe Tuğba Dosdoğru; Aslı Boru İpek; Mustafa Göçken
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 14, No. 4, 2022

Abstract: This study has been conducted on forecasting, as accurately as possible, the next day's stock price using harmony search (HS) and its variants [improved harmony search (IHS), global-best harmony search (GHS), self-adaptive harmony search (SAHS), and intelligent tuned harmony Search (ITHS) together with artificial neural network (ANN)]. The advantage of the proposed models are that the useful information in the original stock data is found by input variable selection and simultaneously the most proper number of hidden neurons in hidden layer is discovered to mitigate overfitting/underfitting problem in ANN. The results have shown that forecasts made by HS-ANN, IHS-ANN, GHS-ANN, SAHS-ANN, and ITHS-ANN demonstrate a tendency to achieve hit rates above 89%, which is considerably better than previously proposed forecasting models in literature. Hence, ANN models provide more valuable forecasting results for investors to hedge against potential risk in stock markets.

Online publication date: Tue, 01-Nov-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining, Modelling and Management (IJDMMM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com