Modelling exchange-driven fish price dynamics
Journal of Modelling in Management
ISSN: 1746-5664
Article publication date: 27 August 2021
Issue publication date: 25 November 2021
Abstract
Purpose
This paper aims to put forward and compare two accessible approaches to model and forecast spot prices in the fishing industry. The first modelling approach is a Markov-switching model (MSM) in which a Markov chain captures different economic regimes and a stochastic convenience yield is embedded in the spot price. The second approach is based on a multi-factor model (MFM) featuring three correlated stochastic factors.
Design/methodology/approach
The two proposed approaches are analysed in terms of parameter-estimation accuracy, information criteria and prediction performance. For MSM’s calibration, the quasi-log-likelihood method was applied directly while for the MFM’s parameter estimation, this paper designs an enhanced multi-variate maximum likelihood method with the aid of moments matching. The numerical experiments make use of both simulated and actual data compiled by the Fish Pool ASA. Data on both the Fish Pool’s forwards and Norwegian T-bill yields were additionally used in the MFM’s implementation.
Findings
Using simulated data sets, the MSM estimation gives more accurate results than the MFM estimation in terms of the norm in ℓ2 between the “true” and “computed” parameter estimates and significantly lower standard errors. With actual data sets used to evaluate the forecast values, both approaches have similar performances based on the error analysis. Under some metrics balancing goodness of fit and model complexity, the MFM outperforms the MSM.
Originality/value
With the aid of simulated and observed data sets examined in this paper, insights are gained concerning the appropriateness, as well as the benefits and weaknesses of the two proposed approaches. The modelling and estimation methodologies serve as prelude to reliable frameworks that will support the pricing and risk management of derivative contracts on fish price evolution, which creates price risk transfer mechanisms from the fisheries/aquaculture sector to the financial industry.
Keywords
Acknowledgements
R. Mamon acknowledges the hospitality of the Division of Physical Sciences and Mathematics, University of the Philippines Visayas, where the writing of certain parts of this manuscript was initiated during an academic visit both as an Adjunct Professor and a DOST-PCIEERD Balik Scientist for the Philippine government. Comments and feedback from the participants of the third International Conference on Fisheries and Aquatic Sciences held in Iloilo City, Philippines are appreciated.
Funding: This work is supported by the Natural Sciences and Engineering Research Council of Canada through R. Mamon’s Discovery Grant (RGPIN-2017–04235). Likewise, M. Chavez is grateful for the financial support provided by the Office of International Linkages of the University of the Philippines System through its Cooperate Programme.
Citation
Xiang, R., Jones, C., Mamon, R. and Chavez, M. (2021), "Modelling exchange-driven fish price dynamics", Journal of Modelling in Management, Vol. 16 No. 4, pp. 1054-1069. https://doi.org/10.1108/JM2-04-2020-0101
Publisher
:Emerald Publishing Limited
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