Putting a price tag on temperature

Xiong, Heng; Mamon, Rogemar

doi:10.1007/s10287-017-0291-8

Cited by 4 publications

(1 citation statement)

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“…The apparent limitation in this study is that the parameter estimations have to be re-run every time a new batch of real or simulated data becomes available. Thus, a particular research's natural direction is to extend the MSM approach to a hidden Markov model (HMM) approach with an online parameter estimation scheme (Tenyakov et al, 2016a(Tenyakov et al, , 2016bGu et al, 2020;Xiong and Mamon, 2018). Then, a further extension with the embedding of a higher-order HMM could be formulated; see, for example, Xi and Mamon (2011) or Xiong and Mamon (2019).…”

Section: Discussionmentioning

confidence: 99%

Modelling exchange-driven fish price dynamics

Xiang

Jones

Mamon

et al. 2021

JM2

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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 $l^2$ 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.

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