Machine Learning Algorithms for Algorithmic Trading: An Empirical Study
Abstract
This paper investigates the application of machine learning algorithms in algorithmic trading. It explores various ML models, such as neural networks and ensemble methods, to develop trading strategies based on historical data and market indicators. The research provides an empirical analysis of the effectiveness of these algorithms in generating profitable trading signals and optimizing trading performance.
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References
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