Seasonality patterns in the container shipping freight rate market

ABSTRACT

Shipping indexes have attracted many researchers because they reflect the overall trend of corresponding seaborne markets and can provide implications for the future. Apart from the Baltic Dry Bulk Index (BDI) and correlated indices, the China Containerized Freight Index (CCFI) has been gaining more attention. As a country with large-scale manufacturing, China is an important exporting country and the CCFI was chosen to reflect the container shipping market because the data are more convincing and representative. There have been no systematic attempts to understand the seasonality patterns of container freights. Seasonality patterns reveal the regular fluctuation patterns within a 1-year period. They exist in time series, which are observed more than once a year, like the CCFI. To investigate the nature of seasonality (stochastic and/or deterministic) in container freight rates across different line services, we analyze the CCFI. This paper uses the HEGY method and Monte Carlo method comprehensively to figure out the small sample problem. In addition, seasonal dummy variables are used to test deterministic seasonality. Except for the Japan service series, which contains a half-year unit root, the other container freight rates seem to only involve a non-seasonal unit root at the zero frequency. Deterministic seasonality exists in all the line service series. Furthermore, the seasonality depends on the balance between supply and demand. Under this premise, the seasonal law of freight rates is much obvious.

KEYWORDS:

• Container shipping
• CCFI
• seasonality
• HEGY method
• Monte Carlo method

Acknowledgement

This research is supported by National Social Science Fund of China (Grant no.: 17BGL259); the Fundamental Research Funds for the Central Universities (Grant no.: 16JCHY08).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Social Science Foundation of China [17BGL259]; the Fundamental Research Funds for the Central Universities [16JCHY08]; Shanghai Pujiang Talent Program [Grant no. 14PJC070].