Forecasting the public financial budget expenditure in Dongguan with an optimal weighted combination Markov model

Dewang Li; Daming Xu; Meilan Qiu; Shuiping Yang; Dewang Li; Daming Xu; Meilan Qiu; Shuiping Yang

doi:10.3934/math.2023796

AIMS Mathematics

2023, Volume 8, Issue 7: 15600-15617. doi: 10.3934/math.2023796

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Research article

Forecasting the public financial budget expenditure in Dongguan with an optimal weighted combination Markov model

1.
School of Mathematics and Statistics, Huizhou University, Guangdong, Huizhou 516007, China
2.
Hunan college for preschool education, Hunan, Changde 415000, China

Received: 27 December 2022 Revised: 18 March 2023 Accepted: 19 March 2023 Published: 27 April 2023
MSC : 62P05, 62P20, 62M05, 62M10, 91-10

In this work, a novel optimal weighted combination Markov model (OWCMM) is proposed to forecast the public financial budget expenditure of Dongguan, China, from 2016 to 2020. The new model is constructed based on the optimal combination, which includes the fractional grey model, the Fourier function regression model and the autoregressive integrated moving average model (ARIMA), and modifies this optimal combination by the Markov model. The number of the optimal fractional order is determined by particle swarm optimization algorithm. One example is provided to verify the high fitting accuracy of the new model, the results show that the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the optimal weighted combination Markov model are smaller than that of the quadratic function model (QFM), the classical combinatorial model and its three sub-models, which proves the robustness of the optimal weighted combination Markov model. This work will provide a scientific basis and technical reference for the further research in finance field.
- optimal weighted combination Markov model,
- public finance budget expenditure,
- particle swarm optimization algorithm,
- MAPE,
- RMSE
Citation: Dewang Li, Daming Xu, Meilan Qiu, Shuiping Yang. Forecasting the public financial budget expenditure in Dongguan with an optimal weighted combination Markov model[J]. AIMS Mathematics, 2023, 8(7): 15600-15617. doi: 10.3934/math.2023796

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Abstract

In this work, a novel optimal weighted combination Markov model (OWCMM) is proposed to forecast the public financial budget expenditure of Dongguan, China, from 2016 to 2020. The new model is constructed based on the optimal combination, which includes the fractional grey model, the Fourier function regression model and the autoregressive integrated moving average model (ARIMA), and modifies this optimal combination by the Markov model. The number of the optimal fractional order is determined by particle swarm optimization algorithm. One example is provided to verify the high fitting accuracy of the new model, the results show that the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the optimal weighted combination Markov model are smaller than that of the quadratic function model (QFM), the classical combinatorial model and its three sub-models, which proves the robustness of the optimal weighted combination Markov model. This work will provide a scientific basis and technical reference for the further research in finance field.

References

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