The Fluctuation And Seasonal Patterns Of The Containerized Freight Index Research

Container shipment has always been the main access to the international trade, and its market pattern is the key research project. The core of the container shipment market, which is the freight, constitutes one of the most important parts of trade logistics. The changes of freight can be influenced by all kinds of factors, so profound research on those factors has played an important role on the movement of the whole market.In actual economics, the freight is always affected by variety of factors such as the relation between the demand and the supply, science development and plenty of other error factors, so that the fluctuation pattern is different, such as long-term fluctuation pattern, seasonal fluctuation pattern, periodic fluctuation pattern and etc. The seasonal fluctuation pattern is the most important pattern and mastering the pattern means mastering the demand and the supply of the market. It’s important to study and analyze the pattern of the container shipment, so that we can dominate the market.The project The Fluctuation and Seasonal patterns of the Containerized Freight Index Research has regarded the container shipment freight as the main research object, and the monthly data of China Containerized Freight Index (CCFI) has been collected as the time series, to demonstrate the container shipment freight’s seasonal patterns by founding the related model and analyzing the statistics of the time series. First of all, the project will give a general introduction of the container shipment market and the freight index, focusing on the development of the container shipment market, the system of the market and today’s market and giving a general idea of constitutions of the shipment market and all kinds of factors that affect the freight, in order to analyze the freight fluctuation. After that, by testing the unit root we can set a solid foundation for the next step. At last, a conclusion will be made after the detailed analysis of the models of the seasonal container shipment freight patterns.