Skipjack, the most caught species of tuna globally, is a critical raw material for tuna industry in Thailand, the world’s
largest tuna-processing hub. However, tuna processors are finding it difficult to manage costs of these imported materials because
of price fluctuations over time. Whereas most time series forecasting methods used in the literature model only three
components: trend, seasonality and error, this study proposes a method to handle a fourth component as well: cycle. This method
smooths monthly price data using a cubic spline that can detect cycles varying in both frequency and amplitude, and thus
generates plausible forecasts by refitting the model after duplicating data from its most recent cycle. Results show that world tuna
prices have a slightly upward trend in cyclical patterns with each cycle lasting approximately six years. Peak-to-peak amplitudes
suggest that prices reached their peak at 2,350 US dollars per metric ton in 2017 and have started to fall, but will rebound after
2021
Keywords
skipjack tuna prices, seasonal adjustment, cyclical pattern, spline interpolation, time series forecasting
SONGKLANAKARIN JOURNAL OF SCIENCE & TECHNOLOGY
Published by : Prince of Songkla University Contributions welcome at : http://rdo.psu.ac.th
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