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Application of Machine Learning to Financial Asset Price Forecasting and Allocation: A Literature Review |
ZHAO Qi,XU Weijun,JI Yucheng,LIU Guifang,ZHANG Weiguo |
1. South China University of Technology, Guangzhou, China; 2. Guangzhou Financial Service Innovation and Risk Management Research Base, Guangzhou, China;3. Guangdong University of Finance and Economics, Guangzhou, China |
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Abstract By combing the application of machine learning to asset price prediction and allocation and the progress of the research in this field, this paper briefly summarizes the characteristics and shortcomings of existing research. On this basis, the main application frameworks of machine learning in existing studies and their applicability and limitations are summarized, and the possible trends of the studies on asset price prediction and allocation via machine learning methods are further discussed. Existing literature shows that machine learning methods can mine the financial data and make use of the information related to asset price changes, make accurate predictions of future asset prices or profitable asset allocation decisions. The combination of machine learning algorithms and financial theories is an important direction for future research.
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Received: 11 March 2020
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