Shai Goldman published some headline numbers from the PitchDeck database on Twitter
The DPI thresholds of the 3981 VC Funds below $2 Billion in size are...
5x = 1.4% (Top) (Note: 65% of the funds that generated 5x DPI are sub $100 Million size funds)
4x = 2.2% (Top)
3x = 4.7% (Top)
2x = 13.3% (Top)
1x = 45.4% (Top)
If you strip out the 2010+ vintage funds you discover
5x = 2.4% (Top)
4x = 3.7% (Top)
3x = 7.8% (Top)
2x = 21.5% (Top)
1x = 68.9% (Top)
Now if you assume the average life of the fund is 10 years then the fund needs to return >2x to beat investing the passive market index
This indicates that even achieving a listing in the top quartile is not enough for a fund to beat the index
So let's explore this insight by mashing up another VC market simulation
This model simulates the probability of a VC fund manager assembling a portfolio of startup investments and bundling them into a fund capable of beating the passive market index.
It does this by estimating the probability of the return of the fund based on the performance of the previous fund.
The key insight here is
a. The probability of beating the market is low.
b. The probability of repeating this result is even lower.
c. However, given enough swings, you will probably assemble a fund capable of delivering a top quartile position
In the chart below 5th Quartile = Top 15% / 4th Quartile = Top 25% / 3rd Quartile Top 50% / 2nd Quartile Bottom 50% / 1st Quartile Bottom 25%
This model does not account for the reality VCs are more likely to achieve higher success with their first fund than subsequent funding rounds
If we repeat the simulation enough times we begin to see the familiar market curve take shape
We see how large funds with an established reputation utilise their market leverage to have more swings at success...
Thereby skewing the data to create the illusion they are more capable of picking winners than the new entrants
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