The paper doesn’t say VC risk is high. It says that 50% of the investments are predictably bad and can be safely dropped because there are better risk adjusted alternatives in the public markets (stocks or bonds) and dropping these would boost returns.
I know he seems to score returns on features such as funding raised and the founder’s background (he claims VCs over value the background). But how do they compare those features with bonds and stocks? I was expecting sales growth, margins or P/S ratios to be the features.
This seems to miss the point. If you are pursuing a particular rate of return, you can be almost guaranteed of not reaching it with bonds and traditional equities. Risk adjusted return is only one framework for examining your portfolio.
The inherit risk in a given asset should not be a constraint.
You can simply lever bonds, equities or most other investments by a variety of means. For example you can get way more risk in 2-year US gov securities via futures than would be sensible.
Likewise, you can de-risk an asset by holding cash alongside that asset.
The point is not to stop investing in VC, but stop investing in the subset of VC that doesn’t measure up to your otherwise available investments. (About half the shots).
You can redistribute the same amount of money into the other (better) half.
Absolutely. But in this case the author claims he does know which half. That’s what the whole paper is really about: figuring out which half. (Not saying you have to agree with him)
I know he seems to score returns on features such as funding raised and the founder’s background (he claims VCs over value the background). But how do they compare those features with bonds and stocks? I was expecting sales growth, margins or P/S ratios to be the features.
Can someone parse the feature set and algo used?