performance

This paper focuses on funds of funds (FOFs) as a form of financial intermediation in private equity (both buyout and venture capital). After accounting for fees, FOFs provide returns equal to or above public market indices for both buyout and venture capital. While FOFs focusing on buyouts outperform public markets, they underperform direct fund investment strategies in buyout. In contrast, the average performance of FOFs in venture capital is on a par with results from direct venture fund investing.
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I conduct an investment screening performance benchmarking between 111 venture capital (VC) investment professionals and a supervised gradient boosted tree (or “XGBoost”) classification algorithm to create trust in machine learning (ML) -based screening approaches, accelerate the adoption thereof and ultimately enable the traditional VC model to scale. Using a comprehensive dataset of 77,279 European early-stage companies, I train a variety of ML algorithms to predict the success/failure outcome in a 3- to 5-year simulation window.
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We use investment-level data to study performance persistence in venture capital (VC). Consistent with prior studies, we find that each additional initial public offering (IPO) among a VC firm’s first ten investments predicts as much as an 8% higher IPO rate on its subsequent investments, though this effect erodes with time. In exploring its sources, we document several additional facts: successful outcomes stem in large part from investing in the right places at the right times; VC firms do not persist in their ability to choose the right places and times to invest; but early success does lead to investing in later rounds and in larger syndicates.
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Our study introduces venture capital (VC) investors’ personality as a new perspective on investment performance. We assemble a sample of 911 VC investors with 8,258 investments and apply novel text analysis methods to assess investors’ personality traits based on their Tweets. Drawing on interactionist perspectives of the personality– performance relationship, we develop and empirically test theory on the impact of VC investors’ personality traits on investment success. We find that extraversion relates positively, while agreeableness and conscientiousness relate negatively, to the likelihood of a successful exit.
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