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This is a Systematic Review study.

September 16, 2025Journal of World Economy

Machine Learning in Financial Time Series Forecasting: A Systematic Review

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Authors

XYXuanqi YangHang Seng University of Hong Kong

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Implication

This systematic review analyzes the effectiveness of machine learning prediction models in financial time series, highlighting limitations and future improvements.

Key Points

Machine learning improves prediction models for financial time series, with significant advancements in recent years.
The review assesses various models, finding notable performance differences while addressing limitations in current methodologies.
Time series analysis is essential for tackling nonlinearity and chaos in financial data, aiding model development.
Integration of computational intelligence and big data approaches offers new insights for enhancing financial predictions.

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Xuanqi Yang (2025) studied this question.

synapsesocial.com/papers/68d4508231b076d99fa58462 https://doi.org/10.56397/jwe.2025.08.14

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Implication

This systematic review analyzes the effectiveness of machine learning prediction models in financial time series, highlighting limitations and future improvements.

Machine Learning in Financial Time Series Forecasting: A Systematic Review

Discussion

Member takes

Implication

Key Points

Cite This Study

Machine Learning in Financial Time Series Forecasting: A Systematic Review

Discussion

Member takes

Implication

Key Points

Cite This Study

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