The Inference and Machine Learning Group is Radicle's data science intelligence unit. We apply modern statistical
methods to better understand startups and venture capital.
The Inference and Machine Learning Group
Applied research on startups and building the state of the art data science tools that power Radicle’s future-focused
research and discovery products.
Disruption Discovery Platform™
NLP engines to identify novel areas of disruption and the companies competing for a market opportunity
Investor Cluster Score™
A mathematical measure of the signal produced by the investors in a startup’s capitalization table
Startup Anomaly Detection™
A statistical algorithm to estimate the plausibility that a startup will exit via an IPO or acquisition
An Empirical Perspective on Startup Valuations
In this paper, we explore post-money valuations by venture capital stage classifications. We find that valuations can be
described as being log-normally distributed, allowing us to think of them in terms of mean, median, and standard
deviation, as well as build classical statistical models.
We present an OLS log-log regression model as a tool to help practitioners approximate an undisclosed post-money
valuation with ease. Our results are statistically significant at the p < 0.001 level for all terms with an
adjusted R-squared of 89 percent.
We also describe the results of an equivalent Bayesian model to better understand the uncertainty of our OLS