“Unpacking Alpha in Venture Capital“ is a great series of articles by Ahmad M. Butt and an excellent read on VCs and a systematic apporach to create an “ecology map and building an institutional footprint” based on deep look “at the VC asset class, running analysis of historical VC fund returns (+1500 funds globally), digested and parsed a broad array of market and academic research (50+ academic papers published over the last two decades); and completed 100+ expert interviews with a range of top tier GPs, FoFs and entrepreneurs based in the US, EU and Asia.” You can follow a thread on his Twitter profile regarding his project with the following major findings.
Core findings of the first parts of this series
- VC is a challenging asset class to digest. A majority of large institutional pools of capital would struggle to list more than a handful of brand name VC firms or investors.
- VC is a cottage industry but done scrupulously and systematically it can deliver strong, uncorrelated returns. Alpha generation is very poorly attributed.
- Dollars should be focused into capacity constrained strategies that attack the early stages. VC doesn’t scale.
- Top decile returns in VC are extremely impressive.
- There are no obvious warning signs that this is a poor time to enter the asset class. Technology-led innovation is pervasive and cumulative.
- The historical narrative for prospective investors into this asset class has been one that believes the only way to access these returns is to invest in brand name funds.
- Such funds are capacity constrained and are usually closed to new Limited Partners (LP). As a counter narrative, there are continually new funds entering the market and capturing value. This presents a problem.
- Base hypothesis is that as a pool of capital, an allocation to VC can deliver uncorrelated, strong returns and that there's an informational benefit to having a lens into the future technologies that will continue to displace operations, impair assets and disrupt incumbents.
- Whilst Silicon Valley has undoubtedly been the epicentre of technology innovation, other hubs of ideation, innovation and global problem solving are developing fast.
- VC is a human capital business, driven by prescient General Partners (GP) and outlier founders. There is limited evidence to support long-term consistent firm-level performance, in fact persistence of performance is declining.
- Investing with more metrics = less alpha. The best investors are comfortable investing at the edges, but do so on the basis of a scientific and rigorous process that appreciate the risk. A quick summary of rigorous methodology is inspired by P. Tetlock’s Superforecasting.
- The best Early Stage investors are “foxes”. They are curious polymaths, with broad peripheral vision. LPs should test for and allocate to investors with the optimal attributes versus making their own editorial about where the next tech wave will come from.
- Technology KPIs have evolved but I believe most Public Market investors still don’t understand the pervasiveness of technology. Every listed asset is potentially impaired.
- LPs have not challenged their GPs to innovate nor gone deeper on GP level data. I consider the industry must mature faster and both sides must do better.
- Most early stage investors waste the informational alpha generated. It provides a lens into what will work in the future but in nearly every scenario tells you what isn’t working within incumbents. Cross-pollinate this info to unlock more alpha in public portfolios.
- Whilst VC is auto correlated and initial successes matter - there is strong evidence of mean reversion as GPs struggle to stay hungry and mentally agile.
Summary of possible feasable and successful VC strategies
Agile and small by design with no intrinsic desire to overgrow a fund size meets a very dense and concentrated portfolio (<20-25). An investment is taken, when data is ambiguous meanwhile avoiding market timing risk and the fear of missing out (FOMO) by beeing anti-thematic and anti-cyclical. A key to success is the set of founders, who can scale and develop while pivoting their way through. In this case, they don't have to be replaced.
“As a systematic public market investor, venture capital was an asset class that felt opaque to me based on only my limited exposure of angel investing and my friends in the industry. It is a challenging asset class to digest and I am sure a majority of large institutional pools of capital would struggle to list more than a handful of brand name VC firms or investors. That said, top decile returns in VC are extremely impressive so I decided to take a deeper look with a view to create a ecology map and building an institutional footprint from first principles.”
“The purpose of this chapter is to give a brief introduction to VC from an external lens and to state some of the myths that I think objectively, less informed pools of institutional capital have about the asset class.”
“The purpose of this chapter is to walk through my thinking on alpha generation, or outperformance, in venture capital. I think VC Performance can be attributed to a basic Beta measured by median performance in the asset class and then isolating factors that deliver top decile performance in the asset class. Without being too scientific in the approach (and discounting any impact of uncalled capital) as data issues pervade and others have done far more comprehensive work on this, my model based on the historical returns.”
Unpacking Alpha in Venture Capital — Chapter 4: Solving for the Human Capital Challenge in Venture Capital
“So if we haven’t found a strong argument why we should not try and build a fund from scratch as there appears no structural barrier to entry that cannot be overcome?—?how do we therefore do this? How do we solve the human capital challenge of identifying the top performing venture capitalists and founders!”
Unpacking Alpha in Venture Capital — Chapter 5: Hidden informational Alpha