Advanced Machine Learning for Financial Markets: A PCA-GRU-LSTM Approach

Liu, Bingchun; Lai, Mingzhao

doi:10.1007/s13132-024-02108-3

J Knowl Econ

2024

DOI: 10.1007/s13132-024-02108-3

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Advanced Machine Learning for Financial Markets: A PCA-GRU-LSTM Approach

Bingchun Liu,

Mingzhao Lai

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Cited by 3 publications

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AI in Forecasting Financial Markets

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2024

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Artificial Intelligence (AI) is transforming the landscape of financial market forecasting, offering innovative approaches to predict trends, optimize investments, and mitigate risks. By leveraging machine learning, natural language processing (NLP), and advanced statistical methods, AI-driven models analyze vast amounts of structured and unstructured data in real time, uncovering patterns and insights beyond human capabilities. This research explores the application of AI in financial market forecasting, emphasizing techniques such as deep learning for time-series analysis, sentiment analysis of news and social media, and reinforcement learning for adaptive trading strategies. Case studies from equity, commodity, and cryptocurrency markets demonstrate the effectiveness of AI in enhancing prediction accuracy and decision-making efficiency. The study also addresses challenges, including data quality, overfitting, and the ethical implications of AI-driven trading. By bridging the gap between computational intelligence and financial theory, this research aims to advance the understanding of AI’s role in forecasting financial markets, contributing to more robust, transparent, and equitable financial systems.

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Advanced Machine Learning for Financial Markets: A PCA-GRU-LSTM Approach

Cited by 3 publications

References 75 publications

MLBGK: A Novel Feature Fusion Model for Forecasting Stocks Prices

MLBGK: A Novel Feature Fusion Model for Forecasting Stocks Prices

A Stochastic Residual-Based Dominant Component Analysis for Speech Enhancement

AI in Forecasting Financial Markets

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