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- Title
AR Model Based on Time Series Modeling for Predicting Egg Market Price in 2021.
- Authors
Min YAO; Qingmeng LONG; Di ZHOU; Jun LI; Ping LI; Ying SHI; Yan WANG
- Abstract
Eggs, as a meat consumer product in China, are closely related to the vegetable basket project. Exploring and predicting the future trend of egg market price is of great significance for stabilizing egg price and market supply. In this study, the time series AR model was used for fitting the egg market prices in the 66 d from January 1 to March 7, 2021, and the delay operator nlagl8 was used for white noise test, giving pr >probability of chisq <0. 005. The time series was not a white noise series, and then the stationary series was used for modeling. The optimal model was selected as the AR series ( BIC (3,0) ), and finally, the egg market price model AM was obtained as X, ~ 9. 055 6 + ( 1 + 0. 892 6) s,, which was the optimal model. The model showed that the egg price fluctuations in 2021 will be clustered, and the later price will be significantly affected by external factors in the previous period. The dynamic prediction results of the model showed that the egg price would stop falling in March 2020, and the egg price would continue to slow down in March.
- Subjects
CHINA; AUTOREGRESSIVE models; MARKET prices; TIME series analysis; MARKET pricing; PRICE fluctuations; WHITE noise
- Publication
Agricultural Biotechnology (2164-4993), 2021, Vol 10, Issue 2, p89
- ISSN
2164-4993
- Publication type
Article