Calculating Outperformance in Dollars: Introducing the Excess Value Method
提出超额价值法，用于计算私募市场投资相对于基准的美元超额收益，并基于直接阿尔法和Kaplan-Schoar公开市场等价指标进行算法调整，帮助投资者和基金管理人衡量价值创造并设计基于超额收益的绩效费用。
This article introduces the excess value method for calculating the dollar value that a private market investment generates relative to a benchmark. To the authors’ knowledge, this is the first published method of doing so. It is based on the commonly used direct alpha and Kaplan–Schoar public market equivalent (KS-PME) measures of private market relative performance as a rate and multiple. The article demonstrates that direct alpha and KS-PME cannot be directly translated into dollar terms for all but the simplest cash flow streams. It thus introduces adaptations that enable this translation to take place algorithmically. The authors believe that excess value can give investors and fund managers useful insights into the value creation of private market investments over time and can facilitate an alternative to traditional carried interest compensation. Unlike carried interest, which compensates managers for absolute performance regardless of public market behavior, excess value–based performance fees enable performance compensation to be paid only for outperformance versus a public market benchmark. <b>TOPICS:</b>Real assets/alternative investments/private equity, performance measurement <b>Key Findings</b> ▪ This article introduces the excess value method for calculating the dollar value a private market investment generates above or below a benchmark. It is based on the commonly used direct alpha and Kaplan–Schoar public market equivalent performance measures. ▪ The excess value method introduces adaptations that enable dollar outperformance to be calculated algorithmically even for complicated cash flow streams. ▪ Excess value can enable parties to measure dollar outperformance over time and to develop performance fee agreements that create better alignment by being based on a split of value in excess of an agreed benchmark rather than absolute returns.