The new risk and return of venture capital investments (with F. Burguet)

Boosted trees regression of post-money valuations

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 benchmakr 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 case-study and find an alpha of 36%, on par with the tech sector, but with a lower beta of 1.56

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Loïc Maréchal
Ph.D. in finance

My research interests include finance, market microstructure, machine learning, and data extraction for financial applications.

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