Stock market prediction is important because successful prediction of stock prices may promise attractive benefits. This task is complicated and very difficult. In this paper, the predictability of stock market index with Adaptive Network-Based Fuzzy Inference System (ANFIS) is investigated. The goal is to determine whether an ANFIS algorithm is capable to predict stock market return and trying to find best architecture. We attempt to model and predict the return on stock price index of the Tehran Stock Exchange (TEDPIX) with ANFIS. We use six macroeconomic variables as input variables. The experimental results reveal that the model successfully forecasts the daily return of TEDPIX Index. ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of the stock price index return.
Farazmand, S., Kordnaeij, A., & Moshabaki, A. (2013). Predicting Tehranâs Stock Market Index With Adaptive Nework-Based Fuzzy Inference System (ANFIS). Journal of Asset Management and Financing, 1(1), 27-44.
MLA
Sajad Farazmand; Asadollah Kordnaeij; Asghar Moshabaki. "Predicting Tehranâs Stock Market Index With Adaptive Nework-Based Fuzzy Inference System (ANFIS)". Journal of Asset Management and Financing, 1, 1, 2013, 27-44.
HARVARD
Farazmand, S., Kordnaeij, A., Moshabaki, A. (2013). 'Predicting Tehranâs Stock Market Index With Adaptive Nework-Based Fuzzy Inference System (ANFIS)', Journal of Asset Management and Financing, 1(1), pp. 27-44.
VANCOUVER
Farazmand, S., Kordnaeij, A., Moshabaki, A. Predicting Tehranâs Stock Market Index With Adaptive Nework-Based Fuzzy Inference System (ANFIS). Journal of Asset Management and Financing, 2013; 1(1): 27-44.
)