I've been reading Gauging Corporate Financial Results for a while now and really enjoy the site. I mentioned them in my Random Thoughts post on Friday as a further inspiration for my Fundamental Data Neural Net Model. Well inspiration did hit me last week when I remembered that when I data mined fundamental stock data, certain key components (Forward PE, Capitialization, etc) would have greater influences on price appreciation.
Still, the fundamental data makeup of a stock can be quite large and sifting through all that data can be tiresome, but there's a way to solve that. I can either create a Cluster Neural Net model to see which components are grouped together or I can create a Genetic Algorithm model to help choose the best fundamental components to analyze. Decisions, decisions!