Beating the Dragons:
How radical diversification can outperform VCs

Contrary to conventional wisdom, the study reveals that investing at random in at least 30 startups that have raised capital could beat the returns of not only the infamous TV Dragons, but also most professional venture capitalists (VCs).

Turns out Nobel Prize winner Harry Markowitz had it right when he said 'diversification is the only free lunch in finance'.

Startling startup growth

VCs are risk-takers by nature. Each follows their own investing ethos to zero in on the next unicorn, often with specific sectors, regions or types of company in mind. After taking a stake in a company, they lend their expertise to help drive it to success. The conclusions drawn from our research are not for VCs; they're for investors who want to take part in the early-stage asset class with a view to optimise their returns in the long term.

The study tracked every UK startup that raised seed or venture equity finance in 2011, for which reliable data was available: that's 506 startups in total. The same cohort was analysed in our 2017 report Rise of the Growth Hunters and 2018's Early-Stage Equities: A Long-Term Study. This includes now-household names like TransferWise, The Culture Trip, Swiftkey and Nutmeg. Over the years, we've found that startups can provide unexpectedly high levels of returns.

In 2011, the cohort represented 506 fledgling businesses eager to prove themselves in the wild. Here's what the cohort looks like seven years down the line.

The 2011 cohort in 2018

2011 cohort performance

Had you invested £10,000 in the entire cohort back in 2011, by the start of this year your portfolio would have been worth £72,800. Here's a more detailed breakdown of the cohort's performance since 2011:

Full cohort valuation growth 2011–18

cohort valuation growth

Using the same dataset, we looked at the VCs and Dragons that invested in the cohort to determine their 2011 startup portfolios. Comparing the performance of these portfolios with that of the cohort as a whole, we discovered that radical diversification can help you outperform VCs.

So, if a large and broad cohort of startups outperforms the Dragons and most VCs, this begs the question…

Is it time for a startup index fund?

Overall, the cohort of 506 startups grew in value at an average rate of 28% per year between 2011 and 2018 (compound annual growth rate, or CAGR). By comparison, publicly reported investments made by the Dragons in 2011 and 2012 grew at an average rate of 16% up to 2019. Our data also followed the 2011 portfolios of 479 VCs, which together grew at 19% CAGR.

Average annual growth of 2011 portfolios (2018)

average annual portfolio growth

Indeed, based on investments made in 2011, only 38% of UK venture capitalists were able to outperform the full startup cohort as a whole. This means that most venture capitalists would be better off picking their investments at random, rather than trying to pick the ones they think will be successes.

Of course, most doesn't mean all. Some VCs are seeing up to 90% CAGR on their 2011 investments; one way to bolster your portfolio may be to access the networks of VCs whose portfolio growth outperforms that of our cohort.

Radical diversification

After carrying out repeat simulations of various investment strategies (100,000 simulations per strategy), we found that one of the most successful was to spread your risk among as many companies as possible. We dubbed the strategy 'radical diversification'; here's how it works.

Radical diversification focuses on making at least 30 investments into companies raising between £500,000 and £5m. These simulations assume that a fixed amount is invested into a single round of each company, with no follow-on investments being made.

On average, such a portfolio returned 3.7x of the initial investment in total over a seven-year period; when diversifying even more dramatically into 80 companies, this figure returned 4.7x.

Average total returns over seven-year period

When investing in £500,000–£5m rounds
average total returns by portfolio size average total returns by portfolio size average total returns by portfolio size

This strategy allows investors a much higher chance of backing massive success stories like Funding Circle, which more than pay for any failures in the portfolio (according to Companies House filings, Funding Circle’s 2011 investors saw a staggering 231x return on investment from its 2018 IPO).

Radical diversification continues to hold true when applied to smaller rounds of early-stage companies (£150,000–£2m), though the rate of return slows once the portfolio reaches around 30 investments.

The assertion that higher returns are more likely when investing in larger, later-stage rounds is nothing new, since the businesses raising these larger rounds have already undergone the smaller fundraises and survived to raise again.

Average total returns over seven-year period

When investing in £150,000–£2m rounds
average total returns by portfolio size average total returns by portfolio size average total returns by portfolio size

The above visualisations show the average total cash returns achievable in a seven-year period according to cohort data. The ten, 30 and 80 companies used for the examples were picked at random from the cohort.

Are your biases damaging your portfolio?

But it isn't only the size of your portfolio that impacts on potential returns – it's diversification. If your investment strategy employs biases that lead to certain opportunities being excluded from your portfolio, you may be shooting yourself – and your returns – in the foot.

As the above summaries demonstrate, when constructing a highly diversified portfolio, random selection can be a credible investment strategy and one that outperforms most VCs. Practically speaking, however, randomness can be difficult to achieve because of biases.

As human beings, we're all subject to countless biases. For our purposes, let's focus on two adjustable types of bias that directly affect how you diversify: conscious bias, such as choosing to invest locally or in sectors with which you're more comfortable, and unconscious bias, such as what networks you draw your investments from.

Local pride is bleeding your returns

Let's try an illustration of well-intentioned conscious bias.

Being a supporter of local business, or perhaps knowing that certain regions of the UK get more startup support than others and wanting to help even the playing field, you decide to invest exclusively in businesses in the North East.

A noble idea, but one that might cost you a lot of money: of the full startup cohort, businesses based in the North East grew at a CAGR of just 7% since 2011; those in London hit 32% CAGR.

In fact, when looking at the number of exited companies and total cash returns achieved since 2011, the top places to invest in are – you guessed it:

  • LONDON | 28 exits | £2,155,579,762 cash returns
  • EAST OF ENGLAND | 14 exits | £673,585,427 cash returns
  • SOUTH EAST | 11 exits | £1,581,577,512 cash returns

These are the only regions to hit double figures when it comes to cohort company exits. In stark contrast, the North East achieved four exits (£39,840,239 cash returns) in the same time frame; Highlands and Islands, Tayside and South of Scotland had none at all.

Total cash returns and exits by region (2018)

total cash returns by UK region
total cash returns by UK region

Fair? Of course not – few things ever are. Unfortunately, until the government does more to support the entrepreneurial infrastructure outside the Golden Triangle, investors hunting financial returns are better off sticking to East of England, South East and London.

It's not just geography; anything that limits your exposure to potentially high-growth businesses could hobble your returns.

The impact of adverse selection

In order to demonstrate the impact adverse selection can have on your portfolio, we plotted out the range of returns and average returns generated by the full cohort from 2011 to 2018. Then we cut out the 10% top-performing companies. This simulates the risk of adverse selection – any set of criteria or bias that leads you to curtail the degree of diversification of your portfolio.

Average and range of returns (£150,000–£2m rounds)

The yellow area in the first graph shows the range of returns possible when investing in the full cohort of startups, with the dotted line demonstrating the average returns. You can clearly see that the likelihood of getting back more than you invested increases the more businesses you back, with the most pronounced increase peaking at 30 investments. A portfolio of ten investments averages 1.2x average returns, 30 averages 2.3x and 80 averages 2.5x.

In the second graph, the orange area shows the same information for the cohort when disregarding the top-performing 10% of investments. Without that top 10% of businesses, your average returns don't even hit the amount you initially invested, basically flatlining at around 0.86x whether you invested in ten companies or 80.

Average and range of returns (£500,000–£5m rounds)

The trend is similar for bigger early-stage rounds (£500,000–£5m), only without the peak at 30 investments; basically, with these larger rounds, the more companies you invest in, the better.

Without the top 10%, the average returns are around 1.74x across the board. Not bad, but if you invest in the full cohort, you could make 4.7x (portfolio of 80 investments).

The lesson is that if your investment criteria causes you to unintentionally disqualify even a small proportion of your potential portfolio, the knock-on effects on your returns could be massive.

Diversifying well

Ok, so the numbers seem pretty conclusive – diversify into more young businesses and achieve a higher likelihood of returns. The problem? Unless you have a significant amount of wealth at your disposal, your options are to make a significant investment in a few businesses, or a small investment in many businesses, leaving you with a tiny amount of equity in each. Additionally, since many investment rounds will have a minimum amount you must invest, this could further limit the number of businesses you can back.

And that's before you remember that many businesses will approach angel groups and VCs first, meaning they're the ones who get first dibs – and the lion's share – of the equity.

There are two things you can do to bolster your odds of building a strong startup portfolio.

1. Gain access to angel networks

Many promising investment rounds get taken up by big angels and VCs, and never make it down to retail investors, who by definition offer businesses smaller sums of capital. This can lock you out of their rounds completely and thereby limit the performance of your portfolio (remember those -10% range of returns graphs above?).

We used the 2011 portfolios of 479 VCs to work out their average compound annual growth rate (CAGR): 19%. While this figure falls short of the 28% CAGR demonstrated by the full startup cohort, it is worth noting that the spread of VC performance is very wide.

These VCs had the best-performing 2011 portfolios:

  5. FUSION IP | 70% CAGR

That's some impressive growth! What's more, the combined 2011 portfolios of business angels came to an average 35% CAGR. To combat your own network bias, get access to the networks of these VCs and angels, and diversify.

2. Invest in 30 startups or more

As demonstrated in the Range of Returns visualisations above, optimal portfolio size does depend on the type of round you're investing in. If looking at smaller rounds (£150,000–£2m), a spread of 30 investments will give you the biggest jump in returns. For bigger rounds (£500,000–£5m), the upward trend maintains velocity past 30 companies, so the more businesses you invest in, the greater your likelihood of higher returns.

Happily for us, the data supports SyndicateRoom's 'investor-led' investment strategy and, to a greater degree, that of Fund Twenty8, which seeks to back no fewer than 28 businesses per fund (the last two funds closed at a portfolio of 32). (If you want to watch a short video explaining how the fund works and the research it's built on, visit the Fund Twenty8 page.)

The three golden rules

While the 2011 cohort has performed better than the oft-cited statistic that nine out of ten startups fail by year five, you must remember that the nature of early-stage companies makes this asset class super high-risk. Diversification isn't a new antidote, but it is one hitherto untested in this space – particularly to the degree suggested in this study.

To achieve radical diversification, start with three objectives:

invest in 30+ startups

Invest in 30+ startups
especially when backing larger rounds

avoid adverse selection

Avoid adverse selection
of any sort

combat network bias

Combat network bias
by getting into top VC networks

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The cohort data used above was commissioned from Beauhurst, an independent research agency. Beauhurst monitors and tracks every equity investment into private UK companies and has been doing so since mid-2010. Wherever possible, Beauhurst calculates the valuation of the company at the time of the investment.

This dataset has enabled Beauhurst to analyse the growth in valuation of a cohort of UK companies from 2011 to present.

Cohort selection

Beauhurst selected a cohort of 676 companies that received equity investment in 2011 and for which Beauhurst has been able to calculate a valuation at the time of investment.

Beauhurst has been sector-agnostic in selecting this cohort. Beauhurst further refined this cohort by limiting it to companies that were seed or venture-stage at the time of their 2011 raise. Where a company has exited or died, it remains part of the cohort and is valued on the basis below.

Note: for the study outlined on this page, a subset of 506 companies was used to draw a comparison between valuation data from 2011 to 2018. The subset (referred to here as ‘the cohort’) was chosen based on which companies had reliable data available for all of these years.


All Beauhurst’s valuations are transactional valuations based on the price paid per share in the round and the total number of shares in the company.

In some instances, valuations cannot be reliably calculated, because of the use preference/deferred shares, and these companies have been excluded from the cohort. All valuations are based on data that are in the public domain.


Each member of the cohort’s starting valuation is based on the pre-money valuation of the company at the time of the first fundraising they completed in 2011 (where they completed more than one). Subsequent valuations are based on the last fundraising completed in that year.


To analyse the change in valuation of the full cohort of companies (676 businesses) between 2011 and 2018, Beauhurst determined the fair value of each company as at the end of 2018.

This process takes into account the following:

  1. Where the company has ceased trading or wound up, it has been valued at zero
  2. Where the company has had a successful IPO, the company has been valued based on the share price at the point of listing
  3. Where the company has been acquired, the company has been valued at either the sale price, where disclosed; or a. the value of the latest known valuation, b. where the sale price is undisclosed
  4. Where the company has raised subsequent round(s) of investment, the company has been valued at the valuation of the most recent investment
  5. Where the company has not raised any subsequent investment, but has not ceased trading or wound up, the company has been valued at the same value as its initial round of investment

The Monte Carlo method

Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. Their essential idea is using randomness to solve problems that might be deterministic in principle.

For each investment strategy tested, SyndicateRoom ran 100,000 Monte Carlo simulations.


These materials are written and provided for general information purposes only. It is worth remembering that while a significant study for the industry as a whole, this report nevertheless uses a small sample size which limits the reliability of assertions drawn from the data.

The content is solely the opinion of SyndicateRoom and/or other contributors and research from third parties. It should not therefore be relied upon in making any investment decisions.

You should not invest in any investment product unless you understand the nature of it, along with the extent of your exposure to risk. You should be satisfied that any product or service is suitable for you given your financial position and investment objectives. Where appropriate, you should seek advice from a financial advisor in advance of making investment decisions.

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You might like to read the 2017 report or the 2018 report.