价格“同频共振”与产业链安全稳定

doi:10.16381/j.cnki.issn1003-207x.2021.2707

Abstract

Abstract:

The hog industry chain is a typical dissipative structure system. The security and stability of the chain is the internal entropy flow while the price resonance is external， which determines the dynamic evolution of the system. Based on dissipative structure theory and Hidden Markov model， combining neural network and forward algorithm， Baum-Welch algorithm and Viterbi algorithm in machine learning， a stable state prediction method of hog industry chain based on price modal dissipation of each node of the chain is proposed. The STL-NAR model is used to predict the prices of corn， piglet and hog. Then the price resonance of the chain is represented as different price modes to confirm the smoothness of price transmission through application of symbolic dynamics. The Hidden Markov Model is also applied to evaluate and predict the security and stability and abnormal risk of the chain. The empirical results show that， the STL-NAR model has good predictive performance for the smoothness of price transmission at each node of the industry chain， and it can provide a reference for the prediction and alertness of abnormal price fluctuations. There is a Markov property between the price resonance and the security and stability of the industry chain and the smoothness of price transmission can effectively predict the security and stability of the chain， which provides insights into future scientific research and judgment.

Key words: hog industry chain, security and stability, dissipative structure, price modes, resonance

CLC Number:

TP18

Jian-fei LI,Kun TANG,Yang SHEN. Price Resonance and the Security and Stability of Hog Industry Chain: A Prediction Based on Price Mode Dissipation[J]. Chinese Journal of Management Science, 2023, 31(12): 290-300.

Figures/Tables 10

References 24

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时间	玉米			仔猪			生猪
时间	趋势	季节	随机	趋势	季节	随机	趋势	季节	随机
2000.01—2003.05	67.66	2.30	30.04	59.89	10.30	29.81	27.32	57.45	15.23
2003.05—2006.06	55.86	0.56	43.58	60.15	7.50	32.35	59.70	8.62	31.68
2006.06—2010.04	86.35	-1.26	14.91	45.08	-1.30	56.22	52.59	2.86	44.55
2010.04—2014.04	92.63	4.37	3.00	60.73	3.90	35.37	37.47	19.89	42.64
2014.04—2018.05	80.41	5.37	14.23	48.84	0.24	50.92	29.35	9.91	60.74
2018.05—2020.08	60.59	5.63	33.78	89.75	0.53	9.72	71.43	3.02	25.55

数据分布	玉米	仔猪	生猪
训练集	174	174	174
测试集	37	37	37
验证集	37	37	37

时刻	隐状态1	隐状态2	隐状态3	时刻	隐状态1	隐状态2	隐状态3
2020-09	0.002	0.000	0.998^*	2022-05	0.705^*	0.214	0.081
2020-10	0.002	0.000	0.998^*	2022-06	0.879^*	0.080	0.042
2020-11	0.001	0.000	0.999^*	2022-07	0.001	0.000	0.999^*
2020-12	0.933^*	0.000	0.067	2022-08	0.917^*	0.000	0.083
2021-01	0.001	0.000	0.999^*	2022-09	0.930^*	0.025	0.045
2021-02	0.922^*	0.000	0.078	2022-10	0.001	0.000	0.999^*
2021-03	0.871^*	0.086	0.043	2022-11	0.002	0.000	0.998^*
2021-04	0.699^*	0.230	0.070	2022-12	0.925^*	0.000	0.075
2021-05	0.663^*	0.265	0.071	2023-01	0.800^*	0.110	0.090
2021-06	0.750^*	0.212	0.037	2023-02	0.860^*	0.092	0.049
2021-07	0.641^*	0.293	0.065	2023-03	0.816^*	0.109	0.075
2021-08	0.646^*	0.284	0.071	2023-04	0.001	0.000	0.999^*
2021-09	0.769^*	0.190	0.041	2023-05	0.955^*	0.000	0.045
2021-10	0.705^*	0.216	0.079	2023-06	0.929^*	0.026	0.045
2021-11	0.821^*	0.133	0.046	2023-07	0.001	0.000	0.999^*
2021-12	0.799^*	0.127	0.074	2023-08	0.964^*	0.000	0.036
2022-01	0.001	0.000	0.999^*	2023-09	0.001	0.000	0.999^*
2022-02	0.963^*	0.000	0.037	2023-10	0.957^*	0.000	0.043
2022-03	0.739^*	0.186	0.074	2023-11	0.884^*	0.067	0.048
2022-04	0.682^*	0.247	0.072	2023-12	0.771^*	0.151	0.079

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Price Resonance and the Security and Stability of Hog Industry Chain: A Prediction Based on Price Mode Dissipation

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