Modelling the return distribution of salmon farming companies : a quantile regression approach

Abstract

The salmon farming industry has gained increased attention from investors, portfolio managers, financial analysts and other stakeholders the recent years. Despite this development, very little is known about the risk and return of salmon farming company stocks, and especially how the relationship between risk and return varies under different market conditions, given the volatile nature of the salmon farming industry. We approach this problem by using quantile regression to examine the relationship between risk factors and stock price returns over the entire return distribution at both the industry and firm-level. As potential risk factors, we include the market return, changes in the salmon price, changes in exchange rates, changes in the long-term interest rate and the lagged stock return of the industry leader.

The results show that the market return, changes in the salmon price and the lagged stock return of the industry leader have a positive and significant impact on stock price returns. Furthermore, while the risk factor sensitivities are quite stable across quantiles at the industry-level, there are larger differences across quantiles at the firm-level. This implies that the relationship between risk factors and stock price returns varies under different market conditions, at least at the firm-level. In addition, the companies have different risk and return characteristics that might be of particular interest for investors when it comes to asset allocation and hedging decisions. Finally, we also show how the results can be implemented and applied in Value-at-Risk analysis, where these different characteristics are taken into consideration.