In today’s digital age, the financial market is increasingly showing its complexity and dynamics. With the continuous progress of science and technology, especially the rise of artificial intelligence technology, machine learning algorithms are increasingly widely used in financial markets. As an important tool in the financial field, the accuracy and efficiency of the financial market forecasting model are directly related to the success or failure of investment decisions. The financial market forecasting model based on machine learning makes use of its powerful data analysis and learning ability to forecast the financial market accurately. However, the change of market environment and the complexity of data also put forward higher requirements for the forecasting model. In view of this, this paper will systematically explain the basic concepts and classification of machine learning, analyze the basic characteristics and influence factors of financial markets, and deeply discuss the advantages of machine learning in financial market forecasting. This paper will also focus on the optimization principle and process of financial market forecasting model based on machine learning algorithms. Through the analysis and interpretation of relevant theories and practices, it is expected to provide more scientific and accurate solutions for financial forecasting.
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Share and Cite
Yang,S. (2022) Research on Optimization of Financial Market Forecasting Model Based on Machine Learning. Hong Kong Financial Bulletin,1(1), 60-66.