With General Solicitation open for all, there is a new interest in portfolio design for angel investors and data around angel investment success. There isn’t a lot of data out there as people investing in the next big thing are surprisingly quiet about the whole thing. Before I get into the data that is available, I want to bring up one point… all of the data scientists that discuss portfolio design take the same approach, analyze investments, add a little monte carlo simulation, and then voila they have a portfolio design theory. The trouble is that this statistical approach forces the inputs to comply and conform with a statistical analysis and surprisingly they answers always include diversification into a larger set of investments. You hear this all the time in public exchange portfolio design articles – diversify, diversify, diversify… another way to phrase that is – statistics is the law of large numbers and suprisingly every statistical analysis of equity investments results in a recommendation to invest in large numbers.
Enough of my rant, I promise I’ll put something up more constructive (around how I view portfolio design) in the near future. Just note that in my thinking process, I have considered all this other information out there and have started to share some of the learnings so far in my post Reflections on angel due diligence.
Simeon Simeonov @simeons put together this econometric study of data from the Kauffman foundation. What is interesting is it appears to include independent and group investments and indicates 50+ angel investments are required to get a reasonable return.