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Journals / İşletme / 2025 / Cilt: 6 Sayı: 2

Stock Price Forecasting Using Single Multiplicative Neuron Model Artificial Neural Network (SMNM-ANN): A Case Of Iron-Steel Sector in Türkiye

Tek Çarpan Nöron Modeli Yapay Sinir Ağı (SMNM-ANN) Kullanarak Hisse Senedi Fiyat Tahmini: Türkiye Demir-Çelik Sektörü Örneği

Mehmet Akif Kara(Giresun Üniversitesi)0000-0003-4308-9933
Dilayla Bayyurt(GİRESUN ÜNİVERSİTESİ)0000-0001-9930-2313
Journal
İşletme
Pages
213–225
Publication Date
2025-09-24
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This research highlights the potential of SMNM-ANN to enhance decision-making processes and resource allocation in the steel sector, thereby contributing significantly to the industry.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study employs the Single Multiplicative Neuron Model Artificial Neural Network (SMNM-ANN) Automatic Forecasting Method for Stock Price Prediction in Turkey's steel industry.
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Key Findings & Data:Accurate financial forecasts are critical for businesses and investors, as the primary goal is to maximize profits through predicting future stock prices.
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Conclusion & Impact:This research highlights the potential of SMNM-ANN to enhance decision-making processes and resource allocation in the steel sector, thereby contributing significantly to the industry.
🔬Design:Modeling & Simulation
📍Scope:2015 Verileri
⚙️Variables:Tek Çarpanlı Nöron Modeli · yapay sinir ağı · hisse senedi fiyatı

Abstract

This study employs the Single Multiplicative Neuron Model Artificial Neural Network (SMNM-ANN) Automatic Forecasting Method for Stock Price Prediction in Turkey's steel industry. Accurate financial forecasts are critical for businesses and investors, as the primary goal is to maximize profits through predicting future stock prices. A variety of methods are used in stock price predictions, with traditional techniques being complemented by artificial neural networks and machine learning methods in recent times. In this context, the SMNM-ANN method provides a flexible, nonlinear approach for predicting stock prices. The study utilizes 1101 stock closing price data between January 28, 2015, to May 30, 2025. To facilitate comparisons, machine learning techniques such as Boosted Tree, Decision Tree, and SVM are also employed. The application calculates forecast values for the next 10 data points, revealing that the SMNM-ANN-AFM method exhibits lower error rates. The obtained RMSE value is 0.6983, while the MAPE value is 2.5138. This research highlights the potential of SMNM-ANN to enhance decision-making processes and resource allocation in the steel sector, thereby contributing significantly to the industry.

Özet

Bu çalışma, Türkiye'deki demir-çelik sektöründe Hisse Senedi Fiyat Tahmini için Tek Çarpanlı Nöron Modeli Yapay Sinir Ağı (SMNM-ANN) Otomatik Tahmin Yöntemini kullanmaktadır. Doğru finansal tahminler, işletmeler ve yatırımcılar için kritik öneme sahiptir. Bu sürecin en önemli kısmı da gelecekteki hisse senedi fiyatlarını tahmin ederek elde edilecek karı maksimize etmektir. Hisse senedi tahminlerinde birçok farklı yöntem kullanılmaktadır. Geleneksel yöntemleri yanı sıra yapay sinir ağları ve makine öğrenmesi teknikleri son dönemlerde sıkça kullanılmaya başlanmıştır. Bu bağlamda, çalışmada kullanılan SMNM-ANN yöntemi, esnek ve doğrusal olmayan bir yaklaşım sunarak hisse senedi fiyatlarını tahmin etmektedir. Çalışmada, 28 Ocak 2015 ile 30 Mayıs 2025 tarihleri arasında 1101 hisse senedi kapanış fiyatı verisi kullanılmıştır. Çalışmada karşılaştırma yapabilmek için ayrıca makine öğrenmesi tekniklerinden Boosted Tree, Decision Tree ve SVM kullanılmıştır. Uygulamada, gelecek 10 gözleme ait tahmin değerleri hesaplanmış ve elde edilen sonuçlar, SMNM-ANN-AFM yönteminin daha düşük hata oranları sergilediğini göstermiştir. Elde edilen RMSE değeri 0.6983, MAPE değeri ise 2.5138 olarak belirlenmiştir. Bu araştırma, SMNM-ANN'nin demir çelik sektöründe karar verme süreçlerini ve kaynak tahsisini geliştirme potansiyelini açıkça vurgulamaktadır, böylece sektör için önemli bir katkı sağlamaktadır.

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Cite This Article

Kara, M. A., Bayyurt, D. (2025). Stock Price Forecasting Using Single Multiplicative Neuron Model Artificial Neural Network (SMNM-ANN): A Case Of Iron-Steel Sector in Türkiye. İşletme, Cilt: 6 Sayı: 2, 213–225. https://doi.org/10.57116/isletme.1737812

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