TITLE:
Combination Method between Fuzzy Logic and Neural Network Models to Predict Amman Stock Exchange
AUTHORS:
Mohammad M. Alalaya, Hani A. Al Rawashdeh, Ahmad Alkhateb
KEYWORDS:
MAPE, MACD, Fuzzy Logic, Neural Network, Time Series, ASE, Wavelet ANFIS
JOURNAL NAME:
Open Journal of Business and Management,
Vol.6 No.3,
June
22,
2018
ABSTRACT: The purpose of this paper is to consider the potential in the projection of
Fuzzy logic and Neural networks, also to make some combination between
models to address implementation issues in the prediction of index and prices
for Amman stock exchange in different models, where the previous researchers
have to demonstrate the differences between these measures. We have
used in this research Amman stock Exchange index prices data as a sample set
to compare the different application models, where predicting the stock market
was very difficult since it depends on nonstationary financial data, in addition
to the most of the models are nonlinear systems. These papers draw an
existing academic and practitioner in literature review as a combination of
these models and compare them, the facilities of the development of conceptual
methods and the research proposition are the basis for serving this combination.
Hence, the present and recent papers can serve the further researchers
into addressing contemporary barriers in the direction of these researchers.
The authors show in this paper the Fuzzy logic and Neural networks, in
addition to time series analysis through these models, utilized of RSI, OS,
MACD, and OBV, then using MSE, MAPE, and RMSE. The research implication
represents of too much data for the period of study, also this paper is
conceptual in its nature, the paper highlights in finding that the implementation
challenges, and how these challenges can facilitate the trader decision in
the stock market. The results of the analysis show that the ANFIS is the better
model to achieve prediction of stock market more than others. When are
MAPE and RMSE the best more than simulating the errors in other methods?
Also the fuzzy-neural models as the results of table show that more prominent
in fuzzy-neural models ,while it appears that in MSE as medium, MAD posses less amount than other models in all table testing fuzzy-neural models, therefore,
it becomes superior in stock prediction.