Decoding Tomorrow's Gold Prices: A Comparative Study of GRU and CNN-LSTM in the Iranian Market

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Baradaran Amir Hossein; Bohlouli Masoumeh; Jahed Motlagh Mohammad Reza

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2024 | Issue:10

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Title

Decoding Tomorrow's Gold Prices: A Comparative Study of GRU and CNN-LSTM in the Iranian Market

Author(s)

Baradaran Amir Hossein | Bohlouli Masoumeh | Jahed Motlagh Mohammad Reza

Keywords

Forecast

18-Carat Gold

Convolutional Neural Network

Long Short-Term Memory

Gated Recurrent Unit

Abstract

With the rising prominence of gold as a lucrative investment avenue in Iran, this research delves into predicting the future price of 18-Carat Gold. In pursuit of this objective, a comprehensive comparison is conducted between two neural network architectures: the Gated Recurrent Unit (GRU) as a single structure and a hybrid model combining Convolutional Neural Network (CNN) and Long Short-Term Memory Neural Network (LSTM). The evaluation criteria employed focus on error metrics to gauge the accuracy of price predictions. Results reveal that the CNN-LSTM hybrid neural network exhibits superior performance, showcasing lower error values in predicting the price of 18-Carat Gold in Iran. Consequently, the chosen model, CNN-LSTM, is employed to Forecast the following day's gold prices, providing valuable insights for investors navigating the Iranian market. This research contributes to the ongoing discourse on gold investment strategies by highlighting the effectiveness of advanced neural network models in enhancing predictive accuracy.

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APA: Copy

Baradaran, Amir Hossein, Bohlouli, Masoumeh, & Jahed Motlagh, Mohammad Reza. (2024). Decoding Tomorrow's Gold Prices: A Comparative Study of GRU and CNN-LSTM in the Iranian Market. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/1147648/en

Vancouver: Copy

Baradaran Amir Hossein, Bohlouli Masoumeh, Jahed Motlagh Mohammad Reza. Decoding Tomorrow's Gold Prices: A Comparative Study of GRU and CNN-LSTM in the Iranian Market. 2024. Available from: https://sid.ir/paper/1147648/en

IEEE: Copy

Amir Hossein Baradaran, Masoumeh Bohlouli, and Mohammad Reza Jahed Motlagh, “Decoding Tomorrow's Gold Prices: A Comparative Study of GRU and CNN-LSTM in the Iranian Market,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2024, [Online]. Available: https://sid.ir/paper/1147648/en

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