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This is a Quantitative Study study.

September 16, 2025Frontiers in Applied Mathematics and StatisticsOpen Access

Artificial intelligence and exchange rate forecasting: assessing predictive accuracy and macroeconomic sensitivity

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Authors

OAOumaima AbouzaidChouaib Doukkali University FBFaouzi BoussedraChouaib Doukkali University

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Implication

This analysis reveals predictive accuracy of various AI models in exchange rate forecasting, suggesting limited macroeconomic impact on forecast errors.

Key Points

LSTM model demonstrates superior predictive accuracy with an R-squared value of 0.9234, outperforming other models.
Macroeconomic indicators have limited power in explaining forecast errors, with only Eurozone interest rates showing weak significance.
The study evaluates machine learning architectures including MLP, RF, and LSTM for forecasting exchange rates.
Findings underscore the importance of hybrid AI frameworks that combine macroeconomic theory with data-driven learning.

Cite This Study

Abouzaid et al. (2025) studied this question.

synapsesocial.com/papers/68d4538731b076d99fa58966 https://doi.org/10.3389/fams.2025.1654093

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Implication

This analysis reveals predictive accuracy of various AI models in exchange rate forecasting, suggesting limited macroeconomic impact on forecast errors.

Artificial intelligence and exchange rate forecasting: assessing predictive accuracy and macroeconomic sensitivity

Discussion

Member takes

Implication

Key Points

Cite This Study

Artificial intelligence and exchange rate forecasting: assessing predictive accuracy and macroeconomic sensitivity

Discussion

Member takes

Implication

Key Points

Cite This Study

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