with Marc Penkala, General Partner at āltitude
EUVC Academy · 1h · Fund Modelling
Part of Fund Modelling Series
Fund modelling in venture capital is about building a dynamic tool that links assumptions, portfolio construction and capital deployment into a coherent framework. It matters because it directly shapes how funds make decisions in real time and how strategy translates into outcomes.
In this session, we focus on moving away from static models towards tools that are integrated into day-to-day fund management and decision-making. We examine how portfolio construction, allocation and strategy choices materially impact fund performance and how different assumptions can lead to very different outcomes.
We also show how models should evolve over time as a “living organism” that adapts to changing realities rather than remaining fixed forecasts.
Key Learning Points
Fund models as decision systems
The core challenge is building a model that adapts to real-time portfolio and reserve decisions
The value of a model comes from being embedded in daily fund operations, not occasional use
Models are designed to diverge significantly from their initial state over the fund lifecycle
Fund size as the primary constraint
Fund size defines the feasible strategy, not just the scale of execution
Different fund sizes require fundamentally different paths to reach similar outcomes
Fund size simultaneously constrains ownership, portfolio size and follow-on capacity
Return mechanics: magnitude and ownership
Top-performing funds are differentiated by outlier magnitude rather than average performance
Ownership determines whether outliers translate into fund-level returns
Return concentration is structural, with most value generated by very few companies
Follow-ons as a probabilistic trade-off
Increasing capital per asset lowers required exit thresholds
Follow-on strategies only work if selection accuracy exceeds a defined threshold
Follow-on strategies are structurally constrained by access, not just conviction
