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Research on Forecasting of China's Monetary Policy Based on Random Forest Algorithm.pdf (401.65 kB)
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Research on Forecasting of China's Monetary Policy Based on Random Forest Algorithm.pdf

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posted on 09.04.2020 by chuanxin qiu
This paper uses the random forest algorithm model to quantify and predict the monetary policy of the People's Bank of China under the input of 16 indicators macroeconomic indicators. It is compared with three other machine learning algorithms (CART decision tree, support vector machine and neural network algorithm), discrete selection model and combined prediction model. The results show that the random forest algorithm shows better prediction accuracy in predicting the direction of the central bank's monetary policy.

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Email Address of Submitting Author

qiuchuanxin@email.szu.edu.cn

Submitting Author's Institution

Shenzhen University

Submitting Author's Country

China

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