Optimized Modular Deep Neural Network for Forex Stock Price Forecasting

Hossein Adabifirouzjaei
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Hossein Adabifirouzjaei: Shahid Beheshti University, Tehran, Iran.

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Abstract: Investment in the foreign exchange (Forex) market is an effective strategy to enhance capital and gain profit. As one of the most profitable financial markets worldwide, Forex can provide substantial investment returns for those equipped with the right trading and economics knowledge. This decentralized market for currency trading and exchange is globally recognized as one of the largest investment markets, playing a critical role in determining currency exchange rates. The Forex market facilitates currency exchange in various transactions, particularly those related to the purchase and sale of goods and services by companies, covering travel expenses, and enabling investments by individuals or agencies in countries that utilize the respective currencies. The dynamic nature of the Forex market allows traders and investors to capitalize on fluctuations in currency values, which can be influenced by a multitude of factors including economic indicators, geopolitical events, and market sentiment. The present study aims to provide a comprehensive review of the data collection process, focusing on the selection of relevant Forex market datasets. It meticulously evaluates the measures adopted to ensure the consistency and reliability of each dataset, which is critical for accurate analysis and forecasting. Given the complexity and volatility of the Forex market, maintaining high-quality datasets is essential for effective trading strategies and decision-making. In addition to the data review, the study also proposes and describes a modular neural network (MNN) model designed specifically for forecasting price fluctuations within the Forex market. This advanced modeling approach leverages machine learning techniques to enhance predictive accuracy, allowing traders to make informed decisions based on anticipated market movements. By integrating rigorous data analysis with sophisticated forecasting models, this research aims to provide valuable insights into the complexities of Forex trading and its potential for profit maximization.

Date: 2025-05-28
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Published in Journal of Economics, Management and Trade, 2025, 31 (6), pp.161-168. ⟨10.9734/jemt/2025/v31i61305⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05089471

DOI: 10.9734/jemt/2025/v31i61305

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