The Cyclicity & Fluctuation Of CCFI

Maritime transport is of the largest transport volume in various modes of transport.It plays an irreplaceable role in the international economic and trade.Shipping cycle has a significant effect on shipping companies,and it is their fundamental base to develop business strategy.Most of the studies used the BDI(Baltic Dry Index)to observe the shipping industry.For China,the world factory,large quantities of electronic products and electrical appliances,machinery and 7 categories of labor-intensive products(clothing,textiles,footwear,Furniture,plastic products,bags,toys)are almost all transported in containers.CCFI(China Export Container Freight Index)can be sensitive to reflect the situation of Chinese manufacturing industry.It is of research value.This paper briefly introduces the container transportation market,CCFI and index calculation method,and then uses the HEGY method to analyze the seasonal nature of CCFI and implements Monte Carlo simulation with Matlab programming to determine the critical value.The results found that in addition to the Japanese line service contains a semi-annual unit root,the other line services only contain a non-seasonal unit root.This result shows that in most cases it is fine to use general unit root test methods(such as DF test)in non-seasonal ARIMA models and VAR models.The deterministic seasonal trend exists in the freight series of all line services,and the seasonality is more pronounced when the annual supply-demand is relatively balanced.In addition,this paper uses the HP filter to explore the existence of shipping cycle and find a cycle of 4 years and a cycle of 7 years.For the series of seasonal unit root,this paper carries out the corresponding seasonal differencing,get the smooth shipping sequence of each route,to achieve seasonal purpose from the tariff index to eliminate the purpose.On the base of the stationary time series,the GARCH model is used to model the volatility of the freight rates.The EViews software is used to estimate the parameters,and the results are diagnosed by the ARCH test(conditional heteroskedasticity test).Finally,this paper summarizes the research and provides suggestions for the operation and decision-making of shipping enterprises in order to avoid the risk of shipping cycle and reduce some negative effect of shipping cycle through counter-cyclical operation and complementary industry management.