Modeling the return distribution of salmon farming companies: A quantile regression approach

Abstract

As the companies have grown larger, the salmon farming industry has received increased attention from investors, financial analysts and other representatives of the financial community. Still, little is known about the risk and return characteristics of salmon farming companies’ shares. This paper approaches this topic by applying quantile regression to investigate the relationship between risk factors and monthly stock price returns over the entire return distribution at both industry and firm level. The results show that the overall market return, changes in the salmon price and the lagged returns for the major company in the industry have a positive impact on company stock price returns. The risk factor sensitivities are quite stable across quantiles at industry-level, there are substantial differences at the firm level, but formal testing cannot reject the hypothesis that the quantiles are equal. This implies that the relationship between risk factors and stock returns may vary under different return levels reflected in the salmon price cycles. We show how the results can be implemented and applied in a Value-at-Risk analysis.