Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 10, 2025Transactions on Computer Science and Intelligent Systems Research

Exchange Rate Prediction: Micro and Macro Factors, Machine Learning, and Future Directions

View Full Paper
Ask AI
Bookmark
Share

Authors

BWBohan Wang

Discussion

Loading...

Member takes

Overview

Review reveals machine learning's role in predicting exchange rates, emphasizing macroeconomic and microeconomic factors.

Key Points

  • Machine learning techniques improve exchange rate predictions by capturing complex interactions in data, suggesting enhanced accuracy.
  • A focus on both macroeconomic factors, such as political stability, and microeconomic factors, including market sentiment, is essential for effective models.
  • The review showcases significant gaps in the current literature on exchange rates, highlighting the need for further exploration of diverse data sources.
  • Future work must address limitations in data acquisition and model selection to develop more adaptive and robust predictive models.

Cite This Study

Bohan Wang (2025) studied this question.

synapsesocial.com/papers/68af55ccad7bf08b1eadc0edhttps://doi.org/10.62051/rv2qre97
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Novel Hybrid Deep Learning Method for Accurate Exchange Rate Prediction2024 · 2 citations
  2. 2Macroeconomic Fundamentals and the Exchange Rate Volatility: Empirical Evidence From Somalia2020 · 89 citations
  3. 3Empirical analysis of dynamic spillovers between exchange rate return, return volatility and investor sentiment2020 · 13 citations
  4. 4Asymmetric effect of exchange rate and investors' sentiments on stock market performance2022 · 12 citations