Abstract: The volatility of China containerised freight index (CCFI) can reflect the fluctuation of shipping market effectively. It is an important reference for the business decision-making of shipping enterprises and the policy making of shipping industry in government departments. In this paper, CCFI has been decomposed into several independent intrinsic modes (IMFs) effectively by empirical mode decomposition (EMD) method for its characteristics of data-driven and effectiveness on the nonlinear, non-stationary and multi-scale data processing. Then, composition on IMFs is proposed by considering P-values of T-test and fluctuation frequencies, and the economic connotation of each component is discussed based on the Hilbert transform and statistical analysis. Finally, we study the long-term trend, the effect of a significant event such as financial crisis, seasonal fluctuations and short-term fluctuations caused by market disequilibrium of CCFI from the perspective of intrinsic factors. The conclusions are as follows. CCFI has been declining slowly for a long time, because the capacity of transportation is greater than the demand for freight. A sharp rise or fall of CCFI has been caused by significant events such as financial crisis with big impact and long duration. Its seasonal fluctuation is affected by seasonal production, which shows a regular sinusoidal fluctuation. The peak is around September and October, and the trough is around march and April. Its market disequilibrium for short is caused by oil price, exchange rate and other factors, which have no serious impact. The fluctuation of CCFI has a large cycle of about 4 years and a small cycle of 1 year.

Key words: China’s containerised freight index, volatility, empirical mode decomposition, freight forecasting