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Trade Ease With Machine Learning and AWS
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AI
DOI：10.1109/ACCESS.2023.3257037.png)
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摘要
En 中文
Global trading is undergoing significant changes, necessitating modifications to the trading strategies. This study presents a newly developed cloud-based trading strategy that uses Amazon Web Services (AWS), machine learning (ML), and data science to automate trading tasks. The study begins by creating a machine learning trading strategy using a customized deep neural network (DNN). The strategy was then tested using a trading station before deployment on a cloud machine. The execution of the strategy resulted in a total profit of 42.74526 USD, with a test accuracy score of 87.45% and a training accuracy score of 89.15% over 6047 epochs. The roadmap provides a step-by-step overview of the entire process from strategy development to execution. In addition, this study offers insights into related issues and solutions that can enhance the effectiveness of trading strategies. Overall, this study contributes significantly to the field of cloud-based trading strategies and opens avenues for future research.
Keyword:
Predictive models
Cloud computing
Deep learning
Neural networks
Computational modeling
Finance industry
Method of moments
AWS
deep neural network (DNN)
machine learning (ML)
trade strategy
financial market
cloud computing
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
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