PREDICTING TEHRAN'S STOCK MARKET INDEX USING ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM (ANFIS)

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MOSHABAKI A.; KORDNAEIJ A.; FARAZMAND S.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Paper Information

Journal: JOURNAL OF ASSET MANAGEMENT AND FINANCING Year:2013 | Volume:1 | Issue:1 Page(s): 27-44

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Title

PREDICTING TEHRAN'S STOCK MARKET INDEX USING ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM (ANFIS)

Author(s)

MOSHABAKI A. | KORDNAEIJ A. | FARAZMAND S. | Issue Writer Certificate

Keywords

PREDICTIONQ2

STOCK MARKETQ2

TEDPIXQ2

ANFISQ2

ANNQ2

HIT RATEQ2

Abstract

This paper investigates the predictability of STOCK MARKET index using an Adaptive Network-Based Fuzzy Inference System (ANFIS). The goal is to determine whether an ANFIS algorithm is capable to predict STOCK MARKET return and trying to find the 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 on TEDPIX Index. ANFIS can be a useful tool for economists and practitioners dealing with the forecasting of the stock price index return.

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APA: Copy

MOSHABAKI, A., KORDNAEIJ, A., & FARAZMAND, S.. (2013). PREDICTING TEHRAN'S STOCK MARKET INDEX USING ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM (ANFIS). JOURNAL OF ASSET MANAGEMENT AND FINANCING, 1(1), 27-44. SID. https://sid.ir/paper/245732/en

Vancouver: Copy

MOSHABAKI A., KORDNAEIJ A., FARAZMAND S.. PREDICTING TEHRAN'S STOCK MARKET INDEX USING ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM (ANFIS). JOURNAL OF ASSET MANAGEMENT AND FINANCING[Internet]. 2013;1(1):27-44. Available from: https://sid.ir/paper/245732/en

IEEE: Copy

A. MOSHABAKI, A. KORDNAEIJ, and S. FARAZMAND, “PREDICTING TEHRAN'S STOCK MARKET INDEX USING ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM (ANFIS),” JOURNAL OF ASSET MANAGEMENT AND FINANCING, vol. 1, no. 1, pp. 27–44, 2013, [Online]. Available: https://sid.ir/paper/245732/en

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