Long Only, Special Situations, Growth At A Reasonable Price, Contrarian
Contributor Since 2011
I recently read an article on Seeking Alpha entitled 10 Low Debt Tech Stocks With Strong Corporate Governance. The article screened stocks with low debt to equity ratios that were also ranked as low risk according to Institutional Shareholder Services (ISS). I have read many research articles showing a positive correlation between strong corporate governance and strong stock returns, but I have never looked into the services of a company like ISS to do the work for me. Their scoring process made me curious. I wondered if using such a service would be an effective way of finding great market performers, as the Seeking Alpha article implied. So, I decided to examine this further.
I began by doing a Google (GOOG) search for the ISS website. In the search results, I found a research report paid for by the ISS to show the correlations between their scoring process and stock returns. One thing in the report immediately bothered me. It was a phrase in the fine print that was being used over and over again. Next to many of their tested factors the fine print said, "Becomes positively (or negatively) significant... when Spearman Correlations are used." I am not a statistician, but when I'm reading about a statistical process and it is described as, "Becomes significant," then I skeptically wonder if the data is being manipulated in order to produce the results that are necessary to sell their service. Naturally, my next question was, "What are Spearman Correlations?" Another quick Google search resulted in an example explaining Spearman Correlation:
As an example, let us consider a musical (solo vocal) talent contest where 10 competitors are evaluated by two judges, A and B. Usually judges award numerical scores for each contestant after his/her performance. A product moment correlation coefficient of scores by the two judges hardly makes sense here as we are not interested in examining the existence or otherwise of a linear relationship between the scores. What makes more sense is correlation between ranks of contestants as judged by the two judges. Spearman Rank Correlation Coefficient can indicate if judges agree to each other’s views as far as talent of the contestants are concerned (though they might award different numerical scores) – in other words if the judges are unanimous.In other words, Spearman Correlation ranks perceived governance among companies of the same industry and can be called, "a correlation coefficient between the ranks." Does it make sense to use this type of ranking system?