Title: Research on Chengdu air cargo forecast based on improved ARIMA-GARCH

Authors: Hu Xueqin; Jia Ruimin; Wang Yaqi

Addresses: Beijing Wuzi University, Beijing 101149, China ' Beijing Wuzi University, Beijing 101149, China ' Beijing Wuzi University, Beijing 101149, China

Abstract: With the transformation of China's economic growth mode and the upgrading of industrial structure, aviation logistics is becoming a strategic industry for China's economic and social development. Accurately predicting the dynamic trend of air cargo volume plays an important role in China's aviation logistics planning and construction, which will promote China's economic and social sustainable development. Due to the long-term trend, seasonal effect and uncertainty characteristics of air cargo volume, a single prediction model can not fit the trend of air cargo volume better, resulting in lower prediction accuracy. In this paper, based on the improved ARIMA-GARCH model, the Chengdu air cargo volume prediction model is established. In which, based on the ARIMA-GARCH model, the default white noise sequence in the GARCH model is replaced by the distribution estimated by the Bootstrap algorithm, thus improving the model's prediction precision.

Keywords: air cargo volume prediction; improved ARIMA-GARCH model; Bootstrap algorithm.

DOI: 10.1504/IJMOM.2021.116802

International Journal of Modelling in Operations Management, 2021 Vol.8 No.3, pp.299 - 312

Received: 23 Mar 2020
Accepted: 16 Oct 2020
Published online: 02 Aug 2021 *

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