Should you raise VC money?

There is a constant dance between technology and capital. Technology improves and disrupts, and capital chases the latest and greatest innovation that provides yield. I recently returned to Sweden from an extended stay in the Bay Area. My focus was to learn as much as I could about the fundraising landscape. To build successful, valuable companies you need to understand how financial markets work. Building great products is still the most value-generating work a founder can spend time on, but it isn’t the only piece of the puzzle. Here are some reflections based on my recent experiences talking to investors. A major question for me is “What businesses are a good fit for venture capital?”, and I’ll try and establish that towards the end.

First of all: There are massive amounts of capital in the world that need to be allocated. According to SIFMA, the global equity market will be around US$106 trillion dollars in 2023. US$45.5 trillion dollars of that is in the US, EU US$11.8 trillion dollars, and China US$11 trillion dollars. According to St. Louise Feb, the US M3 money supply (cash, etc) was US$20+ trillion dollars.

There are around 41,000 listed companies in the world with a combined market value of about US$106 trillion, according to the OECD. The 10,000 largest companies make up 90% of the combined market value. The 10 largest companies make up 10% of the combined market value. That means there is a massive value concentration in the world’s largest companies.

Where is the money that makes up global equity markets coming from? According to the OECD, there are four main categories of owners: Institutional investors (like mutual funds, banking institutions, hedge funds, insurance companies, venture capital funds, and pension providers), public sector owners (central or local government), private corporations (other companies) and strategic individual investors (rich people). About 41% of the global stock market cap is held by institutional investors, making them the largest category. In the West, their ownership is even higher.

What do these people want? More money. One way to get more money is to buy an asset that provides yield. The yield on a security is a measure of the ex-ante return to a holder of the security. Some assets, like fixed-income securities like bonds, provide yield in the form of coupon rates. The yield for “risk-free” assets (i.e. securities with virtually zero risk of loss) set the “risk-free rate”. Most people consider 10-year US Treasury bonds (US10Y) to set the risk-free rate. If you buy a US10Y you receive a fixed interest payment every 6 months. The government pays you for locking up money with them for 10 years. Right now, that rate is ~4.4%. Different securities have different ways of providing yield (cash dividends etc) but the principle is the same as for coupon rates.

The risk-free rate has been declining since the 1980s. This has encouraged investors to take more and more risk. The period from 2008 to 2021 offered an extraordinarily low cost of capital. Looking back, risk-free rates are now back to pre-2008 levels of interest rates, and the curve has shot up for the first time in decades. For the last 15 years, governments have stimulated the economy to first recover from the 2008 meltdown, and then the 2020 Covid lockdown. They did not want people to deposit their money into savings, so they turned down the yield on government-backed securities, thereby stimulating the economy. But those times are over now, and investors now get a 4.4% return on their money without taking any risk at all. Assuming all other assets have more risk, money managers will benchmark assets against the risk-free rate.

Why does this matter for a startup? Well, one way to get yield is to seek riskier investments. And startups are incredibly risky. I wrote a lot about this last winter. While returns can be high, the variance of return is high.

When the risk-free rate increases, less money is invested in higher-risk assets. At the peak of the “bull market” (2020-2021) investors struggled to get yield, so they chased riskier and riskier investments. This resulted in higher and higher private valuations of not only startups but also public companies. And much more money became available to startups. According to Meritech public market software-as-a-service valuations reached stratospheric levels during Covid. At one point, you had to pay almost 40 times the next twelve-month sales forecast to buy shares in top-performing software companies. That’s a lot considering many of these companies do not pay dividends. Some aren’t even profitable.

The price of an asset should be proportional to its Sharpe ratio, i.e. the (return minus the risk-free rate) / (variance of return). Of course, you don’t know this number upfront for a specific investment. The job of e.g. venture capitalists is to estimate the return and risk. To do that, they pattern match. They will say they don’t, but they do. They look at as many things as they can and try to conclude what the common denominators are between successful companies. When they set valuations, they will benchmark against similar companies with known valuations. In private markets, this becomes a sort of circular argument that is ultimately anchored in the public market. Public markets provide clear prices, as opposed to private companies that aren’t traded regularly (or at all). So when you sell shares in a private company, investors need to determine: What is the potential of this investment compared to other possible investments I could make, and what is the risk that I lose my money?

Let’s create a specific example. To better explain how valuations work, we will cheat and assume we know all the variables (which you never do). Here comes a ton of numbers:

Let’s assume, for the sake of argument, that our company ends up in a glorious $500M exit. Such exits are extraordinarily rare. As a seed investor, we have a few things to consider: At what valuation am I investing, what is a possible exit valuation, and what is the probability of success? Let’s say we are one of the world’s best seed investors, so 1/20 tickets end up generating a rare exit (I don’t know if anyone can deliver such good odds, but let’s pretend). Considering the dilution from Series A, B, and C, our share of $1M could be worth as much as $24M. Holy moly, that’s a lot of money. But, let’s remember, we only think this happens in 1/20 cases. If we only invested in this one company, the expected annual return is just 2.4%, i.e. much worse than the risk-free rate and NASDAQ. If we placed 20 bets like this, assuming 19 of them will go to zero, we’d have to invest $20M to get one $24M outcome. That’s $4M net value in 9 years, or 2% annually. Also worse than the risk-free rate and NASDAQ. But, let’s change an important variable: let’s pretend we can get a $1B outcome instead. Unicorns. How many companies become dollar unicorns? Very, very, very, very few. Decacorns? Like 10 in a decade maybe?

Babam. Now, all of a sudden, we can get one $48.7M windfall instead. That means we’ve made $28.7M on our seed portfolio of 20 companies, or a 43% gain. That’s 4.1% annually. So now we are basically on par with the risk-free rate. But we need a company that can swallow almost $200M and generate enough revenue to support a $1B valuation. Venture is about finding outliners that can deliver extraordinary returns in a very short amount of time. If we doubled the number of years it takes to reach the outcome valuation, we cut the expected annualized return in half. Venture capital works with short timelines (<10y) and most huge companies take decades to build.

When interest rates change, this presents a triple whammy to these sorts of spreadsheets. On the one hand, it increases the risk-free rate, so companies need to perform better to deliver competitive returns. It also lowers the expected multiples of public companies, thereby lowering the expected market capitalization. Finally, it also means less money from the trillions of capital that need to be allocated is steered towards venture investments, so raising a fund gets harder. The following chart from Battery Venture shows the US10Y vs SaaS multiples. Pretty strong correlation as you can see.

What this means is that right now, there are a lot of very highly valued startups that probably aren’t worth the price put on them in their latest funding round. Another chart from Battery shows a very crowded box for $1B+ startups that soon need to start providing liquidity to venture funds. Venture funds are typically close-ended, i.e. investors lock their money up for 10 years. But after that, they expect to get their money back again. If a VC has a portfolio of companies that they cannot sell, they cannot return money to their investors. That creates a sort of Mexican standoff. If investors in a VC fund push for liquidity, VCs are forced to “mark to market”, i.e. put a price on their assets. Another interesting tidbit: turns out investing in a fund doesn’t mean you have to give them money right away. The VC fund instead calls on capital when needed. Right now, some investors might not be able to honor such a cash call, since they haven’t gotten money back from previous investments. If the IPO market is dead, there is limited liquidity in the secondary market, and the company does not provide revenue enough to defend its valuation, you have a toxic cocktail. This is the state of the current market.

How do venture firms make sure they make money in a market like this? Well, they only invest in truly extraordinary companies. For Series B, we’re talking:

Minimum $5-10M ARR
Minimum 2-3x YoY growth
Burn multiple of max 1-2x (burn / net new ARR)
“Rule of 40” needs to be over 40, i.e. EBIT margin + growth = 40

Very few companies can deliver such metrics. You can be an extraordinary operator and still not have a chance. It takes a certain market, and a certain sort of business, to reach such stratospheric growth levels. As a result, VCs will look for companies that have:

Huge, huge markets. SMEs and consumer products have this. Sometimes enterprise.
Low friction sales motion. This is why everyone loves product-led growth (PLG). No sales team! 🎉
Experienced team. There are a lot of ways to fuck up.

Here is where VCs and founders (can) have conflicting priorities. Investors seeking extraordinary outcomes are not interested in “safe bets”. If the probability of success is 10%, 20%, or 30% doesn’t change the math as much as looking for companies with a possible $10B outcome instead of a $100M. The 100x difference in potential outcome far exceeds the impact of better odds of survival. And, in the end, most startups fail anyway, so they assume there aren’t any “sure things”.

Tier 1 investors are called Tier 1 because they deliver the best returns to their investors. The best provide 20-30%+ net IRR (after fees etc). Some even more. Their business is not to foster innovation, or to fund your science project. They are looking to make tons of money. You should only take on an investment from a Tier 1 VC if you understand what you’re doing.

VC money is like powering your car with an unstable nuclear reactor. You will fly fast as fuck, but the most likely outcome is a meltdown.

I’m starting to understand that the best investors seek a mutual fit between the founder, the company, and their investment. You have to establish shared expectations: How much risk are we taking? What sort of returns are we expecting? What sort of company are you building? How comfortable are you “going for broke”? Can you provide $100M in returns to a fund? $1B? Does the business you envision support such an outcome? Does the market? Difficult questions you have to deal with before you raise money.

Personally, I think it takes years of experience running a startup before you can honestly reason about these things. First-time founders have no idea what they are getting into, for better or worse. Second-time founders who had a moderately successful first try, understand how things work, and are still determined to take VC money - those are the ones who probably should. It doesn’t mean they will succeed, but I’m certain their odds are way better.