Foundations of Fund Modelling in VC

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This session introduces the core concepts behind venture capital fund modelling, with a focus on how fund models are structured, what they are meant to explain and how they support real investment and portfolio decisions over the life of a fund.

Rather than teaching spreadsheet construction or complex scenario modelling, the session concentrates on first principles. It reframes fund models as living steering tools, not static forecasts built for fundraising decks. Participants are guided through the fundamental drivers that shape fund outcomes, including fund size, portfolio construction, ownership, reserves, timing and the assumptions that underpin both alpha and beta outcomes. The emphasis is on understanding trade-offs and second-order effects, not optimising for theoretical precision.

The session also provides clear context on why fund models differ so materially across fund types and strategies. It explains why many emerging managers struggle with modelling by copying frameworks designed for much larger, more established funds and how misalignment between fund size, strategy and model logic can quietly undermine decision-making. Particular attention is given to early-stage primary funds, where ownership, follow-on discipline, exit timing and portfolio breadth have outsized impact on outcomes.

Overall, this session is designed to build a strong mental model for thinking about venture capital fund modelling. It works as a standalone introduction for advanced operators who want to sharpen their thinking, and as a foundation for deeper, more technical sessions within the broader EUVC curriculum.

Agenda

• Fund modelling first principles and what fund models are actually for

• From static forecasts to living portfolio and decision tools

• Fund size as strategy and its implications for portfolio construction

• Core drivers of returns: ownership, reserves, timing, and exit thresholds

• Portfolio strategy trade-offs: concentration vs diversification, entry vs follow-ons

• Assumptions, uncertainty, and why being “precise” is often misleading

Key Learning Points

• Fund model purpose: Understand what a fund model should explain, who it is for, and how it should be used in day-to-day GP decision-making.

• Strategy alignment: Learn why fund size, stage focus, and portfolio strategy must be reflected directly in the model, and why copying other funds’ models often leads to false confidence.

• Portfolio construction logic: Develop intuition for how portfolio size, check sizing, reserves, and ownership interact to shape return distributions and exit requirements.

• Follow-on discipline: Understand when follow-ons improve outcomes, when they increase risk, and why execution constraints matter as much as theory.

• Timing and outcomes: Learn how time impacts IRR, DPI, and fund perception, and how models can support better entry, hold, and exit decisions.

• Assumptions that matter: Build a clearer view of how alpha and beta assumptions drive outcomes, and why robust thinking beats fragile precision.

Meet the Instructor

​Marc Penkala, Co-Founding Partner of āltitude, is a seasoned venture capitalist with extensive experience and expertise in fund modelling. As a former Investment Director and active angel investor, his insights are invaluable for emerging VCs.