Research Reports

The private equity secondaries market has evolved from a niche segment into a crucial $100+ billion marketplace, representing approximately 10% of global private equity transactions. Yet, despite this growth, significant challenges remain in asset selection and pricing. This article demonstrates how artificial intelligence (AI) - particularly machine learning and natural language processing - is revolutionizing secondaries investing by uncovering predictive signals hidden in qualitative data that traditional metrics miss. Groundbreaking research examining thousands of GP reports across multiple funds reveals how the “tone” of management communications can predict future performance more accurately than conventional metrics alone. For investors navigating the complex secondaries market, embracing AI-driven approaches to augment human judgement is rapidly becoming not just an advantage but a necessity for sustainable competitive edge.

A new VC agenda for Germany and Europe - Why we need to mobilize private growth capital and how we can do it

In this study, we highlight the persistent major hurdles hindering access to venture capital, including a lack of private capital from institutional investors, internationally uncompetitive legal frameworks and a lack of opportunities for startup employees and citizens to participate in the value creation of startups and young companies.

Returns in Venture Capital (VC) are characterized by extreme outliers and a notable number of defaulted transactions. Building a well-diversified portfolio is pivotal for investors to achieve sufficient downside protection without disproportionately trimming upside potential. This report simulates VC returns to understand the impact of portfolio size on risk and return potential. The simulations are based on the semicontinuous log-normal model of Juergens et al. (2022).

The analysis is conducted with 10,000 Monte Carlo simulations, each with a universe of 900 VC funds in total, which are equally distributed in early-stage (pre-seed and seed), mid-stage (Series A to Series B), and later-stage (Series C or later). That is 300 funds per stage focus and 18,000 transactions in total across all funds. The portfolio composition assumes equally-weighted portfolios of funds with 30 transactions in early-stage funds, 20 transactions in mid-stage funds, and 10 transactions in later-stage funds.

Lack of capital for high-tech growth companies is a major weakness in Germany’s innovation system, becoming a critical competitive disadvantage especially during digital transformation. This transformation demands radical technological innovations, new business models, and rapid growth. Acatech, in collaboration with KfW and Deutsche Börse, brought together various stakeholders from the financial sector, high-tech growth companies, industry leaders, and academics to assess the situation and develop actionable strategies for policy, business, and academia.