Posts Tagged ‘outliers’

Angels, VCs and Homeruns

Posted in research on April 22nd, 2009 by Michael Ewens – Be the first to comment

Stephen Fleming argues that differences in fund structure and investment horizons creates conflict between the interests of angels and VCs:
Read more: “Angels, VCs and Homeruns – Michael’s posterous” – http://snewe.posterous.com/angels-vcs-and-homerunds#ixzz0DR2Wiu0T&A

  1. Venture economics dictate that VC funds must have a certain number of home runs to make up for the number of deals that simply go broke.
  2. The average size of a venture fund has grown from $100M to $350M in ten years. That means the home runs have to be bigger… as a rule of thumb, you probably need to exit at $200M to “move the needle.”

This article is another motivation for my mixture model.

Posted via web from Michael’s posterous

Return Outliers and Venture Capital

Posted in economics on March 18th, 2009 by Michael Ewens – Be the first to comment

Ken French discusses Taleb’s criticism of academics supposed dismissal of outliers of fat tails:

The possibility of extreme outcomes is certainly important for things like risk management, option pricing, and many complicated “arbitrage” strategies. Investors should also recognize the potential effect of outliers when assessing the distribution of future returns on their portfolios. None of this implies, however, that the existence of outliers undermines modern portfolio theory or asset pricing theory. And the central implications of modern portfolio theory and asset pricing—the benefits of diversification and the trade-off between risk and return—remain valid under any reasonable distribution of returns.

One of the innovations in my paper on VC returns in the use of a mixture distribution to accurately model the tails of the distribution. VC returns have more extreme outcomes — in both the left and right tail — than any sensible normal distribution would imply. Imposing normality is incorrect. Surprisingly, parameter estimates such as the alpha and beta are basically unchanged after the introduction of the mixture. However, the individual regimes of the final distribution do generate insight about both the probabilities of outcomes (VCs lose money 66% of the time) and risk exposures across return types.