Time–frequency analysis of the Baltic Dry Index

In this paper, the dynamic spectral content of the Baltic Dry Index (BDI) is explored. Conventional spectrum analysis, often utilized in economic time series as a complementary tool, provides a static representation of a specific time period, unsuitable for assessing possible frequency shifts over time. Recent studies have shown that the daily BDI has a rich spectral content, which has never been explored utilizing the domains of time and frequency simultaneously. This work attempts to supplement the discussion of the BDI cyclical behavior by highlighting its evolving structure through time–frequency analysis and contributes to the literature by first, assessing the existence of five distinct cycles within the low-frequency band of the BDI, as well as other high-frequency components; second, constraining their frequency ranges; and third, capturing their variability through time, as well as possible stylized frequency shifts. The data-driven trend removal methodology empirical mode decomposition utilized, improved the interpretability of the time–frequency representations. This approach constitutes a framework for capturing frequency/periodicity variations and drifts of the BDI, useful for risk reduction for both maritime demand and supply side stakeholders.