Predicting public market behavior from private equity deals

TL;DR

This paper demonstrates that analyzing private equity transactions can effectively predict public market movements, with a model achieving up to 70% accuracy in certain sectors by leveraging private investors' insights.

Contribution

It introduces a logit model that uses private equity deal data to predict public market returns, revealing the predictive power of private investments.

Findings

Model outperforms null benchmarks

Achieves up to 70% accuracy in key sectors

Private equity signals contain valuable market information

Abstract

We process private equity transactions to predict public market behavior with a logit model. Specifically, we estimate our model to predict quarterly returns for both the broad market and for individual sectors. Our hypothesis is that private equity investments (in aggregate) carry predictive signal about publicly traded securities. The key source of such predictive signal is the fact that, during their diligence process, private equity fund managers are privy to valuable company information that may not yet be reflected in the public markets at the time of their investment. Thus, we posit that we can discover investors' collective near-term insight via detailed analysis of the timing and nature of the deals they execute. We evaluate the accuracy of the estimated model by applying it to test data where we know the correct output value. Remarkably, our model performs consistently better than a null model simply based on return statistics, while showing a predictive accuracy of up to 70% in sectors such as Consumer Services, Communications, and Non Energy Minerals.