Chapter 3: Cycles in the shipping industry
|47 - 69||This chapter aims to detect the shipping cycles which are non-periodic in the shipping industry. It was the unanimous opinion among scientists that shipping is a cyclical, volatile and risky industry. After the elaboration of the characteristics of the shipping industry, we discuss 'shipping paradox', which focus on action of ship owners in new ordering ships will eventually dampen the market. We also discuss the tools to examine cycles particularly the analysis that time series may exhibit a random walk, persistence or antipersistence. When using the Hurst exponent to examine shipping cycles, the value is 0.72 which is less than unity but greater than 0.50 (random walk). This exponent, depending on its numerical value, provides information indicating persistence, antipersistence or random walk. In addition, the time series is shown to have a fractal (non-integer) dimension (1.39 < 2), a rate of decay of the Fourier series of 2.44, and a degree of integration in an ARFIMA model of 0.22. The next step is to determine cycles using two robust methods:|
1 the ratio of log R/S to log n, indicating a cycle of 11 years (for freight rates between 1741 and 1938)
2 the Vn statistic [equal to (R / S)n ⁄ √n]. The results demonstrate that different sizes of ships produce cycles of different duration.
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