Construction of artificial neural network economic forecasting model based on the consideration of state transition diagram


In order to quantify the time-varying dependent structure between the assets and forecast the portfolio risk accurately, the difference in the preferences for asset risk is taken into consideration in this paper. It is assumed that the new interest rate of asset return sequence is subject to the standard t distribution. A kind of artificial neural network economic forecasting model is put forward. The two-step state transition diagram estimation method for the economic forecasting is deduced, and the forecasting method for the profile risk is obtained. Finally, Shanghai Securities Composite Index and Standard & Poor’s 500 Index are selected to verify the feasibility and superiority of the model and method put forward in this paper. At the same time, the model can accurately quantify the time-varying dependent structural characteristics of the two indices after the subprime mortgage crisis.

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The work has been sponsored by Project Supported by the National Natural Science Foundation of China (No. 71601087) and the Humanities and Social Sciences Fund of the Ministry of Education (No. 15YJC630088). The authors gratefully acknowledge this support.

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Correspondence to Xiaofang Luo.

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Luo, X. Construction of artificial neural network economic forecasting model based on the consideration of state transition diagram. Neural Comput & Applic 31, 8289–8296 (2019).

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  • State transition diagram
  • Artificial neural network
  • Economic forecasting model
  • Risk management