A proposed solution for early-stage investors and startup founders to drive actionable insights.
Industry reports miss essential actionable insight for most of the industry participants, i.e., early-stage founders and investors; The early-stage venture index could be a viable solution.
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As we eagerly await VC industry reports for 2022 from our favorite sources, if you are an early-stage investor like me, you've probably wondered how these new reports will impact the ecosystem. As a "Micro VC" who manages less than $50M in assets, I belong to the largest group of funds by number constituting over 50% of the funds. Did you know over 70% of startups that have raised capital in the last 7 years have raised less than $5Min total funding, while more than 50% of startups have raised less than $3M in the same period? Most industry reports tend to inadvertently ignore these majority groups.
Some of the well-known and tracked KPIs, such as pre-money valuation per stage, median rounds sizes per stage, and available dry powder are great indicators of the state of the VC market, but as we dug into the raw data, it became more apparent that the data sets that included these lines were not representative of the larger universe(we will dig into this more), but in turn skewed towards larger rounds and larger funds that are the minority of the raw data set.
While round size ranges for various stages, fundraising statistics by region, sector, etc., are great for policy makers and economic development agencies, these statistics provide little insight into early startup founder sand investors. I came to realize that Industry reports usually aren’t structured to provide actionable insights to this group.
I believe there is an evident need for a useful metric for the early-stage VCs, angels, and founders who make up most of the industry, a metric that will help funds and founders understand risk and impacts of the changing macroenvironments, how these are changing incentives for investors at later stages, and how we should better position ourselves. I will explain the index and its various attributes and components using a problem-solution approach.
The best industry reports are usually provided by data providers such as Pitchbook; I have used the raw data derived from Pitchbook to conduct this analysis. I will refrain from analyzing reports from groups such as attorney firms, cap-table software providers, and other service providers, which not only have a far smaller data set but also don’t make their data available for scrutiny.
From the perspective of early-stage investors and founders, the current industry reporting structure, along with the KPIs that are tracked and highlighted, is deeply flawed, providing very little actionable insight for early-stage founders and investors.
As you may know, most of the VC industry reports are generated using self-reported data and SEC filings (in most cases, exempt filings such as Form D, which don’t contain accurate data or have missing fields.) When looking at raw datasets, I found that more than 80% of early-stage deal information (which constitutes more than 80% of deal volume)lacks essential details such as pre-money valuation, revenue range at investment, and round size. Since most of the industry reports are reporting on the whole data set/population-wide (i.e. every deal in a particular quarter per stage) and since the data sets that contain early-stage startup rounds aren’t always complete, the reports and the subsequent analysis are not necessarily derived from a representative subset of the larger VC investment universe that contains all the essential attributes such round size, pre-money valuations, etc. The errors are usually exaggerated and generally skewed toward well-publicized, larger-than-average rounds of funding, especially in the angel, pre-seed, and seed rounds.
The Stout Street team developed a core fundamental (supply-demand economics based) index* that tracks VC activity such as new fund formation rates, ratio of startups seeking VC funding vs. startups receiving VC funding, and relative deal count growth rates in one index. This index is similar to any public market index; the goal is to mimic the performance/sentiment of a specific financial sector and reflect systemic risk. The index was built from the last 14 years of raw VC deal data sourced from Pitchbook.
The product derived from the fundamental data sets allows us to craft an index that not only gives a quick overview of the VC industry but also provides actionable insights (we will dig into this below).
The index and the numbers associated with the year act very similarly to a public market index; they try to mimic growth/reduction in value of underlying assets. But unlike public market indices, we are not tracking the change in value of companies but are only tracking the perception of change in value based on supply and demand characteristics.
What we see in the chart is a steady increase in venture activity from the last down cycle in 2008 and a peaking in 2015 and plateauing for the last seven years, which is not necessarily a terrible thing; this stable early-stage environment allowed early-stage investors to price fairly and invest with confidence. While this activity had another soft peak in2021, we see a precipitous drop in 2022 indicating a dramatic shift the early-stage perception of risk and growing pessimism in the early-stage VC market. I will discuss the hypothesis, potential implications, and factors that may be causing these variations.
We derived the index from four fundamental supply-demand components.
The above chart shows the individual components. The value each of these components contributes toward the early-stage VC activity index.
The ratio of the startups seeking funding to startups receiving funding from VCs is a great indicator for quantifying the demand or the difficulty in fundraising for early-stage founders. Not only does this indicate the supply-demand dynamics, it also provides the risk perception of early-stage investors when making investments. To ensure we are making an apples-to-apples comparison and deriving a truly representative dataset, we calculate this ratio by only tracking the yearly cohorts of accelerators/incubators globally and their venture funding post-graduation.
This chart is derived from over 100K data points over the last 14 years and shows the 2022 cohort seeing a significant fall in funding rates; while this number is subject to change as more 2022 cohort startups could get funded in H1 2023, historically this number improves by less than 30% in the subsequent years, making the adjusted ratio- 19% for 2022, which is closer to 2014 levels.
This indicator tracks the quantum of new VC fund formation and since the overwhelmingly large number of new funds formed are <$50M in size, this indicator is overweighted toward early-stage fund formation and indicates the macro perception of early-stage investment opportunity. The hypothesis here is simple: more funds form if investors/fund managers perceive the early stage investing to be lucrative and fund formation declines as this perception shifts to a more pessimistic view.
This chart shows the quanta of new VC funds formed each year; 2022, for context, has lower fund formation rates than even 2009, while the VC fundraising data shows only marginal reduction in 2022. This is primarily offset because of the higher-than-normal number of massive VC funds with 1B+ fund sizes being raised in this period.
This is probably the easiest metric to track but also one of the most misleading. While deal counts offer a great view of the activity in the VC market, as an aggregate data set, it misses some of the nuances (for example, which cohorts (year founded) are doing better or worse) and very rarely offers any actionable insight. We used this metric in the index not just because it provides a useful measure of activity in the industry but also because of how accurate this data set is.
The above chart shows the reported deal counts (in blue) each year growing steadily. Even a systemic shock like COVID doesn’t register on the chart; to address some of the deficiencies in this metric, we derived another variable that tracks deal count per cohort (year the startup was founded) instead of yearly aggregate deal count across all cohorts and stages. The data is a combination of actual cohort-based deals data and projected deals data for startups formed post 2015. We built a more sensitive version to accentuate the effects of systemic shocks.
The cohort-based deal count was derived from deal activity based on when startups were founded instead of the aggregate deal activity per year; as one can imagine, these cohort-based deal counts change every year for each cohort, but over long time horizons, the deal activity diminishes for older cohorts and only increases marginally. Analyzing the last 24 year of cohort based deal data, we see that inflection point is around 9 years, after which the deal activity increases are only marginal. This also allows us to statistically project future deal activity in each cohort, giving valuable insight into future activity.
As you can see in the above chart, cohort-based deal count (in orange) numbers are far more sensitive and show the impacts to the early-stage VC market more accurately. As you can also see, the projected line (orange) shows a decline in deal activity for cohorts 2016-2022. We can infer from this projected reduction in deal activity that startups founded in these years may experience a combination of higher likelihood of early exits*, larger round sizes*, and higher unicorn formation rates* but also higher failure rate*, which means that the winners will be substantial and losers will be many. This conclusion is in line with multiple Pitchbook analyst reports, which predict demand for funding outstripping supply, even with all the excess dry powder sitting on the sidelines.
*assuming the capital deployed in this period is stable (at 2019 levels), and these outcomes are zero-sum, larger round sizes and lower deal counts would cause higher failure and/or higher early exit rates for startups; on the other hand, larger round sizes can lead to higher unicorn formation rates; refer analysis by Elya Strebulaev at Stanford business school, see chart below
Macro impacts and commentary
The systemic shocks in the public markets and trickle-down effect of failed IPOs and SPACs resulted in a grinding halt in activity in the early-stage market in 2022. Now, investors are struggling to accurately price startups with the new realities, which include mega funds that over-raised and overinvested in 2021 without any pipeline for liquidity events to provide their LPs with meaningful returns in the near term.
Some growth-stage and later-stage investors could stress early-stage investors by offering cash-strapped startups aggressive terms that include 2x+ liquidation preferences, lower multiples, participating preferences, much higher revenue thresholds, and carelessly wiping out early-investor and founder equity in the process. While most of the industry reports paint a rosy picture because the round sizes are getting bigger and bigger, funds are sitting on huge piles of dry powder. However, the reality is that the next few years will see fewer startups are finding funding; the early-stage investment activity index shows a 30% drop-in activity in 2022. The current VC market conditions indicate growing pessimism, leading early-stage investors to demand higher risk premiums from founders leading to depressed valuations and lower multiples in the early stages of the venture industry for the near future.
While it’s not news for early-stage founders on the fundraising trail that it has become increasingly difficult to raise capital, for founders who are looking to raise capital in 2023, the 30% drop in early-stage activity 2022 means investors are becoming more selective in investing and the growing pessimism in the index indicates investors might be looking for lower valuations or better terms to offset the increased risk. The ratio of VC-funded startups to startups seeking capital suggests that early-stage investors are twice as likely to say no this year than last; even early-stage investors are preferring to invest in larger funding rounds to avoid aggressive later-stage investors with hostile terms. Counter-intuitively raising a larger round might be easier than raising a bridge or <$1M round.
The precipitous drop in early-stage activity shows growing pessimism in the near-short term. It also means that the book value of your portfolio might be lower than you expect, especially considering that later-stage investors are in pursuit of returns and will be ruthless when investing in growth and later-stage rounds. This may be a suitable time to recalibrate the entry points and means/instruments of investment to ensure good ROI and protection from hostile investors for yourself, your portfolio founders, and your LPs. The index could offer a quick insight into the mark to market (MTM) adjustments/corrections needed for GP estimates for your funds to accurately reflect the market/systemic risk for each vintage.
Based on the fund vintages, the respective four-year moving average (blue line) offers a baseline index value for each vintage year. To make the adjustments to the GP estimates of book value, use the rate of change in the current index value (orange line) w.r.t the baseline index values for the respective vintages in the early-stage VC index chart.
John Francis is a founding partner at Stout Street Capital. He specializes in quant-based models and analysis and started his career as a high-frequency quant trader in oil and gas derivatives. John has a master’s degree in trading and finance from Tulane University,
As General Partner at Stout Street, he focuses on investment opportunities in the IT software-serving sectors such as construction, government, energy, cleantech, media, advertising, HR, healthcare, and cloud services. John works actively on several portfolio company boards, including Schola, Fluent Forever, Botco.ai and AdFontes. He previously served on the boards of Popwallet (acquired by Snapchat(Nasdaq: SNAP)) and has made investments in companies such as Left-Hand Robotics (Acquired by TORO (NYSE: TTS))
