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Venture capital has long been shrouded in mystique, with success stories of concentrated bets turning into billion-dollar companies dominating the narrative. But what does the data actually suggest about optimal portfolio construction for investors? We've analysed 5,393 UK startups and over 300,000 investor records. Now, we’ve built an interactive simulator that suggests the mathematical reality behind early-stage investing.
The conventional wisdom suggests that venture capitalists should maintain small, concentrated portfolios of 8-10 high-conviction investments. Our research challenges this assumption, particularly for investors deploying smaller ticket sizes where the mathematics appear to tell a different story.
What the simulator suggests
Our interactive tool allows investors to explore how five critical variables may affect portfolio performance.
Through Monte Carlo simulations based on real UK startup valuations from 2012-2025, we discovered that portfolios of 30+ companies may achieve more consistent outcomes while maintaining attractive return profiles. While this approach may reduce exposure to extreme outlier returns, it appears to significantly improve the probability of achieving 3x returns—a crucial threshold for many investors.
The simulator demonstrates this visually: as an investor increases portfolio size, the probability curves can be observed to shift. Investors may notice that while the chance of achieving 5x+ returns could decrease with larger portfolios, the likelihood of achieving 2-3x returns seems to improve up to a certain point before stabilising.
Perhaps our most striking finding concerns what we call the "Access Probability Factor". In venture capital, investors can't simply buy shares of any company; investors need to be invited to invest. The best opportunities are often accessible only to investors with strong networks, proven track records, and established reputations.
Our quality-correlated access model indicates the dramatic impact of this constraint. When an investor adjusts the access probability slider in the simulator from 10% to 90%, they can observe median portfolio returns increase eight-fold. This finding suggests a new way of thinking about venture capital strategy: improving investor access to quality deals may matter more than perfecting an investor's selection criteria.
The mathematics are sobering. With only 10% access to top-tier opportunities, even a 30-company portfolio has a probability approaching zero of achieving 3x returns. But with 90% access, the same portfolio size yields a 62% probability of reaching that target.
For UK investors, the Enterprise Investment Scheme provides a unique mathematical advantage that the simulator appears to demonstrate. The combination of 30% upfront income tax relief and 45% loss relief on failed investments creates an asymmetric risk profile that seems to fundamentally alter optimal portfolio construction. Though do note that tax benefits are subject to individual circumstances, and can change.
By toggling between standard and EIS-enhanced returns in the simulator, an investor can see this effect in action. Investors may notice that while standard portfolios show declining 3x return probabilities beyond 40-50 companies, EIS portfolios appear to continue improving with size. This is because the tax relief effectively lowers the return hurdle—investors only need to achieve approximately 2.1x gross returns to realise 3x net returns on their actual cost basis.
The simulator is freely available. It has been designed to be both educational for those new to venture capital and useful for experienced investors looking to validate or refine their strategies. Each simulation runs thousands of scenarios based on real UK startup data, aiming to provide statistically meaningful insights into potential portfolio performance.
The tool is designed to be intuitive while providing deep insights:
Start with the basics: Set the maximum ROI expectation (the tool defaults to 100x, though our data suggests only 0.4% of all companies achieve this level of return).
Choose an access model: "Perfect Access" assumes an investor can invest in any company, while "Quality-Correlated" reflects the real-world challenge of accessing top opportunities.
Adjust access probability: If using the Quality-Correlated model, an investor can experiment with different access levels to see how network effects may impact returns.
Run the simulation: The tool can be observed as it processes thousands of portfolio scenarios based on actual UK startup performance data.
Compare the charts: The dual visualisation of standard versus EIS returns suggests how tax policy can dramatically influence investment strategy.
The venture capital landscape continues to evolve, and successful investing requires adapting to changing market conditions. This tool should be used as one input among many in an investor's investment decision-making process. No simulation or forecast can be a reliable indicator of future results.
After running millions of portfolio simulations calibrated against real-world data, several principles appear to emerge:
Diversification does have an effect in Venture Capital. Diversification in venture capital appears to reduce risk based on the simulations, although there are limits to this effect depending on market access and too much can reduce your odds of outsized returns.
Access may be more critical than selection. The ability to get into the right deals appears to matter more than the ability to pick them. This may help explain why successful venture capitalists spend so much time building networks and reputation—it's not just about deal flow volume, but about accessing the highest quality opportunities.
Funding momentum appears to matter. Our analysis of the underlying data suggests that companies maintaining consistent funding velocity (raising rounds every 18-24 months) show dramatically higher success rates. Companies raising small rounds years after their initial funding rarely appear to deliver outsized returns.
Time horizons may be longer than expected. Among UK startups that successfully exited, 55% took more than seven years from first funding to exit, with the median at eight years. This reinforces the potential importance of patient capital and diversification to manage the inherent timing uncertainty.
You can read more about the research in the detailed white paper available here.
While this simulator provides powerful insights into the mathematics of venture capital, it is important to remember that investing in startups involves more than optimisation algorithms. The relationships an investor builds, the value they provide to founders, and their ability to identify and support exceptional teams remain crucial elements that no model can fully capture.
Note: This simulator is based on UK startup data from 2012-2025 and focuses on investments of £100k-£5m at valuations of £2m-£20m. Tax relief calculations assume current UK EIS rates, which are subject to change and individual circumstances. Always consult with qualified financial and tax advisors before making investment decisions.
