Value relevance in the aquaculture industry

Abstract

I study which variables are value relevant in the Aquaculture Industry. The first part of the thesis establish that the Residual Income Valuation Model (RIV-model) and Value Relevance field of research is applicable in this industry. I find that my results are in line with what the field of value relevance research predicts.

The second part of the thesis looks at the Aquaculture industry more thoroughly. I look at which variable is most suitable as a proxy for eliminating the effect of company size, different choices for proxies, both in abnormal earnings and in “other information”. Here, I apply a unique handpicked dataset containing operating data from quarterly financial statements. I find that total assets is the best proxy for the size effect of the companies, net income is the best proxy for abnormal income, the salmon price is the best single proxy for other information and the salmon price, biological assets, harvest volumes and intangible assets are jointly the best variables for other information.

I contribute to the field of value relevance by establishing that the RIV-framework is applicable, by ascertaining which variables are value relevant and which variables should be used in the aquaculture industry. In addition, I build on Dechow (1994); Eccher & Healy (2000); Wu, Koo & Kao (2005) and Misund & Osmundsen (2007) by applying the Vuong-test to determine value relevance in the aquaculture industry.