Practical Applications of Valuation of Early-Stage Technology Ventures: An Approach to Derive the Discount Rate

C. Wessendorf, Schneider Schneider, Kai. Shen, O. Terzidis
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Abstract

In Valuation of Early-Stage Technology Ventures: An Approach to Derive the Discount Rate, from the Winter 2021 issue of The Journal of Alternative Investments, authors Christoph P. Wessendorf, Jared Schneider, Kai Shen, and Orestis Terzidis of Karlsruhe Institute of Technology (KIT) seek to develop an approach venture capitalists can use to derive the discount rate of technology ventures at their early stage. Traditional venture valuation methods rely on quantifiable financial history and data that often are unavailable in early-stage ventures. To compensate for the missing data, venture capitalists often use subjective, or nonfinancial, determinants to assess a venture’s value. The authors explore which nonfinancial valuation determinants have a meaningful impact on eventual value, weigh their relative importance, and use these factors to calculate a venture-specific valuation score. Next, the authors assess mathematical models that can be used with this score to calculate a suitable discount rate. They compare the empirical results of early-stage technology ventures with the values attained using these models to find high fidelity between the exponential discount rate structure and the real observed target return data. Ultimately, the authors propose that an exponential discount rate structure can be used in tandem with nonfinancial determinants to develop sound, venture-specific valuation. TOPICS: Real assets/alternative investments/private equity, security analysis and valuation, performance measurement
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早期科技企业估值的实际应用:一种推导贴现率的方法
《另类投资杂志》(the Journal of Alternative Investments) 2021年冬季号的《早期科技企业的估值:一种获得贴现率的方法》一文中,卡尔斯鲁厄理工学院(KIT)的作者Christoph P. Wessendorf、Jared Schneider、Kai Shen和Orestis Terzidis试图开发一种方法,风险资本家可以用它来计算早期科技企业的贴现率。传统的风险估值方法依赖于可量化的财务历史和数据,而这些在早期风险投资中往往是不可用的。为了弥补数据的缺失,风险投资家经常使用主观的或非财务的决定因素来评估风险投资的价值。作者探讨了哪些非财务估值决定因素对最终价值有意义的影响,权衡其相对重要性,并使用这些因素来计算风险特定的估值得分。接下来,作者评估数学模型,可以用这个分数来计算一个合适的贴现率。他们将早期技术企业的经验结果与使用这些模型获得的值进行比较,发现指数折现率结构与实际观察到的目标回报数据之间具有很高的保真度。最后,作者提出,指数折现率结构可以与非财务决定因素一起使用,以形成合理的、针对风险投资的估值。主题:实物资产/另类投资/私募股权,证券分析和估值,绩效评估
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