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Kazemi, Mohammad, Mohammadi Peyhani, Hamed, Akbari, Mohsen. (1404). A novel leading moving average indicator using ANFIS-Wavelet hybrid method for financial market forecasting. فیزیولوژی و بیوتکنولوژی آبزیان, 13(4), 817-830. doi: 10.22124/jmm.2025.30492.2737
Mohammad Kazemi; Hamed Mohammadi Peyhani; Mohsen Akbari. "A novel leading moving average indicator using ANFIS-Wavelet hybrid method for financial market forecasting". فیزیولوژی و بیوتکنولوژی آبزیان, 13, 4, 1404, 817-830. doi: 10.22124/jmm.2025.30492.2737
Kazemi, Mohammad, Mohammadi Peyhani, Hamed, Akbari, Mohsen. (1404). 'A novel leading moving average indicator using ANFIS-Wavelet hybrid method for financial market forecasting', فیزیولوژی و بیوتکنولوژی آبزیان, 13(4), pp. 817-830. doi: 10.22124/jmm.2025.30492.2737
Kazemi, Mohammad, Mohammadi Peyhani, Hamed, Akbari, Mohsen. A novel leading moving average indicator using ANFIS-Wavelet hybrid method for financial market forecasting. فیزیولوژی و بیوتکنولوژی آبزیان, 1404; 13(4): 817-830. doi: 10.22124/jmm.2025.30492.2737

A novel leading moving average indicator using ANFIS-Wavelet hybrid method for financial market forecasting

Journal of Mathematical Modeling
مقاله 5، دوره 13، شماره 4، اسفند 2025، صفحه 817-830    اصل مقاله (3.76 M)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22124/jmm.2025.30492.2737
نویسندگان
Mohammad Kazemi* 1؛ Hamed Mohammadi Peyhani2؛ Mohsen Akbari3
1Department of Statistics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
2Department of Information Science, University of Ottago, Dunedin, New Zealand
3Department of Business Administration, Faculty of Management and Economics, University of Guilan, Rasht, Iran
چکیده
Technical analysis aims to identify market trends and forecast future direction to support profitable trading decisions. This paper introduces a novel leading moving average indicator based on a hybrid ANFIS-Wavelet approach. The proposed method consists of two main components. First, a hybrid model combining an Adaptive Network-based Fuzzy Inference System (ANFIS) and Wavelet Transform (WT) is employed to forecast future market prices, with the full wavelet decomposition of the price time series serving as input parameters for ANFIS. Second, a leading moving average is constructed using both historical and forecasted prices. Similar to the other leading indicators, the proposed indicator can serve as a market predictor due to its incorporation of forecasted values. Empirical evaluation on NASDAQ-listed stocks demonstrates that this indicator is effective as a trading decision-support tool in financial markets, such as stock exchanges.
کلیدواژه‌ها
Artificial neural network (ANN)؛ financial forecasting؛ moving average؛ time series؛ wavelet transform
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