Salmon price volatility: A weight-class-specific multivariate approach

Daumantas Bloznelis

52 citations0/0 files storedAquaculture Economics & Management

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Financial Risk and Volatility Modeling Economics of Agriculture and Food Markets Market Dynamics and Volatility

Abstract

Salmon spot price has been highly volatile and hard to predict since mid-2000s, obscuring the industry players’ planning decisions. ARMA-GARCH and dynamic conditional correlation (DCC) models were employed on weekly data for 1995–2013 to examine the behavior of weight-class-specific prices which are directly relevant for salmon production and risk management. Two periods of different volatility regimes were identified, before and after 2006 when the salmon market was undergoing fundamental changes. Both volatility and conditional correlations increased from 1996–2005 to 2007–2013, and return dynamics became more homogenous across weight classes. This development is conducive to the functioning of the salmon futures and options exchange.

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 2002Dynamic Conditional Correlation 1995Journal of the American Statistical Association 2001Empirical properties of asset returns: stylized facts and statistical issues 1998Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts n.d.Multivariate GARCH models: a survey 2006Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns

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2018Big Fish: Valuation of the World’s Largest Salmon Farming Companies 2021Analytic formulas for futures and options for a linear quadratic jump diffusion model with seasonal stochastic volatility and convenience yield: Do fish jump?2019Pricing efficiency across destination markets for Norwegian salmon exports

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