Predicting public market behavior from private equity deals

Paolo Barucca, Flaviano Morone
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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.
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从私募股权交易预测公共市场行为
我们采用 logit 模型处理私募股权交易,以预测公开市场行为。具体来说,我们通过估计模型来预测大盘和个别行业的季度回报率。我们的假设是,私募股权投资(总体而言)带有对公开交易证券的预测信号。这种预测信号的主要来源是,私募股权基金经理在其勤勉尽责的过程中,有机会获得有价值的公司信息,而这些信息在其投资时可能尚未反映在公开市场上。因此,我们认为,通过对投资者执行交易的时机和性质进行详细分析,我们可以发现投资者的近期集体洞察力。我们将估计模型应用于已知正确输出值的测试数据,以此评估模型的准确性。值得注意的是,我们的模型在消费服务、通信和非能源矿产等行业的预测准确率高达 70%,表现始终优于单纯基于回报统计的无效模型。
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