Abstract

This paper revisits the study of Cochrane (2005), to estimate the risk and returns of venture capital investments while correcting for the selection bias. We use an up-to-date dataset and enhance it to account for missing firm valuations using machine learning. The model is able to infer, with a median error of less than 4%, the true log value of the firm, for a total of nearly 120,000 observations, or six times more than the original paper, from 2010 to 2022. We find an annualized expected return of around 38%, an annualized alpha of 32.14%, a beta of 1.37, and a 40% idiosyncratic risk. Our results are robust to the choice of the benchmark index. Depending on the sector, we find a beta lower than 1 for the health industry and of up to 1.86 for the tech sector. The health industry exhibits the lowest alpha (24%) and the tech the highest (36%). We use the cyber-security sector as a case-study and find an alpha of 36%, on par with the tech sector, but with a lower beta of 1.56.

Research Paper

article

Source: The Journal of Portfolio Management

BibTex

@article{burguet2022risk,
  title={The Risk and Return of Venture Capital Revisited},
  author={Burguet, Fran{\c{c}}ois and Mar{\'e}chal, Lo{\"\i}c},
  journal={Available at SSRN 4247910},
  year={2022}
}