High algo-trading and predictions in stocks

Investment in a portfolio of assets has never been simple, and due to the unusual nature of the financial market, it is impossible to use straightforward models to make more precise predictions about future asset prices. Machine learning is the process of teaching computers to carry out tasks that w...

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Bibliographic Details
Main Authors: Balaji, T. S., Balaji, Rishikesh, Vishnu, K.
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Machine learning
Recurrent neural networks
Online Access:Get full text
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Summary:Investment in a portfolio of assets has never been simple, and due to the unusual nature of the financial market, it is impossible to use straightforward models to make more precise predictions about future asset prices. Machine learning is the process of teaching computers to carry out tasks that would typically be handled by people. The current major trend in scientific study is human intelligence. This article’s goal is to develop a model utilizing Recurrent Neural Networks (RNN) and, in particular, the Long-Short Term Memory model (LSTM), which are used to “predict future stock market moves. The main goal of this work is to evaluate the prediction accuracy and size of machine learning algorithms. Epochs are useful for our model.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0197726