Investing in the private markets after peak valuations: The Risk-Adjusted Approach
Private market investing after the peak valuations
Peak Multiples in the private capital cycle occurred in 2016.
Overpaying in the private markets is more problematic than in the public markets because of liquidity constraints and dilution from future financings.
Private security value is based on future earnings of the company (DCF), preferences, and future dilution.
Traditionally, investors have defaulted into a ‘betting’ strategy where the one winner pays for the many losers.
Without the ability to assess risk based on the drivers of value, the investor defaults into momentum. investing in the early private capital life cycle where getting into the ‘hot’ deal is higher priority, leaving himself exposed when the cycle turns.
As multiples contract post peak of the cycle, understanding investment value, risk, and volatility will become a higher priority for meeting return objectives.
Portfolio values are risk-adjusted based on the aggregate of the private investments, providing expected return and volatility. At the Portfolio level, the capital for new investments and existing investments is risk-adjusted to allow the investor to rebalance the portfolio to maintain risk/return targets.
Due to advancements in technology and evolution of the market, modern day private capital Investment Management provides on-demand decision support to apply risk-adjusted strategies, allowing investors to assess value, risk and return at all stages of the cycle.
As investors learned in February 2018, eventually valuations matter. In the public markets, it took a mere three days for the markets to decline 12%. The private capital markets have been in valuation decline for more than a year since peak valuations in 2016 and inevitably the exuberance to invest in the ‘hot new sectors’ at any price will give way to investing based on supportable value. As the valuations based on multiples of forecasted revenue contract and revert to the mean, investors need to protect downside risk. Determining the returns based on reasonable growth assumptions, understanding future dilution, and payout breakpoints will become more important to investors in the post-peak portion of the cycle. Objective valuation methods will become more relevant going forward as momentum investing gives way to the private capital world’s version of value investing.
Private investing has a history of boom and bust cycles wherein the price volatility can be dramatic. Exacerbating the price volatility are issues specific to private securities, including ever increasing dilution with time, lack of liquidity, and preference payouts. In the early part of the cycle, when funds raise new capital, investors invest in story momentum stocks where concerns for high multiples are less important than seeding the new emerging markets (e.g. autonomous vehicles, Bitcoin, AI, Hyperloop).
During this early phase in the cycle, the multiples expand as investors want to get into the hot companies for Fear of Missing Out (“FOMO”). From 2011 to 2016, the private market valuations as a multiple of forecasts expanded to a point where the implied growth rates were difficult to achieve. Since the peak, the mispricing of private market valuations were realized as many former private companies witnessed the valuations contract in the public aftermarket (APRN, SNAP). In addition, as high profile private companies falter (e.g. Theranos, Jawbone, Fab.com, Zenefits), the realities of negative cash flow businesses that require more capital reinforce the need to look at investments with finer scrutiny. Private assets will go through multiple contractions which directly impact values that are multiples of revenue. The current point in the private capital cycle is analogous to the post peak valuation period after the first internet wave that ended in 2000.
Perhaps the highest profile case is the bellwether, Uber, which closed the Series H in January 2018 at a 27% decline since the Series G in 2016. The institutional investors, such as Trowe Price, began marking the ‘unicorn’ positions down in 2016 at the peak valuation multiples.
During this post peak period, investing will require more attention to risk/return analysis since investors cannot rely on the momentum of increasing valuation multiples to offset future dilution and lack of liquidity. In addition, investors will need to evaluate the impact of new investments on the overall return and volatility of the existing portfolio to achieve target returns. Determining when to liquidate, when to invest, when to re-invest, and when to convert are just a few of the decisions to make when managing the modern day private capital portfolio.
As the market moves past the supercharged valuation environment the investor can not rely on momentum to drive returns higher. Managing returns in the contracting valuation cycle is critical to optimizing the portfolio and maximizing returns.
Rethinking the 1 in 10 lottery ticket approach to investing in private capital
The common wisdom in the private markets is the investor will sprinkle around 10-20 bets and the one winner will more than pay for the losers. The investment approach is essentially to find a company that you think will return 7-15x your investment and that will pay for the other 9 investments where little or no return is achieved. While it is true that a company which generates 7-15x return usually pays for the other ten losers, finding an investment that can achieve 7-15x returns is difficult and the 1 in 10 investment theory breaks down when the revenue multiples contract.
However, the idea that the investor must settle for 1 in 10 winning outcomes does not reflect modern day portfolio theory that investors adopt in other markets. This investing approach explains why the fund returns are unpredictable.
What if investors rethought their approach to private investing, from betting for 1 in 10 to applying the analytical strategies commonplace in other markets? As it relates to the private markets, maximizing portfolio risk-adjusted returns would be based on evaluating the investments when (1) investing in new opportunities, (2) reinvesting into existing portfolio companies, and (3) exiting existing investments.
In a portfolio approach, the expectations shifts from 1 in 10 odds to a more diversified set of outcomes. An investor might expect 2 winners (100%-1000%+), 3 returns of principal (0%- 100%) and 5 dissolutions (principal loss). This 2/3/5 strategy would still generate high returns but provide a lower beta (volatility). This risk-adjusted return investment strategy maximizes return while minimizing volatility at each investment decision using valuation, payout models, and market pricing. At key decision points in an investment cycle, the investor can use the analysis of risk-adjusted pricing based on company capitalization, financial operations, and expected cash flow/payout models to assess risk and future value. This risk-adjusted investment approach requires upside/downside analysis for new investments and existing portfolio holdings.
To be effective in this quantitative portfolio investment approach, the value of each investment at each investment decision must be assessed. As described above, there are investment decisions related to acquiring new investments, commiting more capital to existing investments, and exiting investments. Each of these decisions is based on a current value assessment, an expected return (“alpha”), and the volatility (“beta”). Understanding the alpha and beta of each investment and how that investment impacts the alpha/beta of the portfolio is the key to risk-adjusted investing in the private markets.
Risk Adjusted Private Investing Strategy
What does risk-adjusted investing mean in private capital when the companies have losses and have not begun generating revenue? In the private markets, the common approach to company valuations is to take next year’s forecasted revenue and multiply the revenue times a comparable multiple to get a valuation. This comparable multiple is the multiple determined by dividing the forecasted revenue of a similar company in the industry by the valuation. For example, if Company A is forecasting $1M in revenue next year and a similar Company B raised money at a $10M valuation on $2M in forecasted revenue, Company A’s value using the revenue multiplier approach would be calculated as follows: (Comparable Multiple of Series A) x (Forecasted Revenue of Company A) = (10M/2M) x 1M = 5. Applying the 5 times comparable multiple on forecasted revenue implies a 5 x $1M = $5M value for Company A.
The problem with the comparable multiple approach is that comparable companies will have different growth rates, operating metrics, dilution events, cash flow profiles, costs of equity, balance sheet profiles, and time to liquidity. As a result, the comparable multiples from one company to the next can have large ranges. Moreover, multiples change over time so a comparable multiple from another time period may not be relevant in the current evaluation period.
During market exuberance, momentum investing dominates the landscape. In the early part of the private market cycle, investors often want to invest into the market leaders. Reasonable valuations are often not the main consideration and multiples often expand beyond what is reasonably achievable by the companies. While some companies will achieve and exceed growth expectation implied by the expanding multiples, the vast majority will not.
Determining the Enterprise Value of a Private Company
Valuation and comparable multiples are based on the future discounted cash flows of the company. Understanding the drivers of the Discounted Cash Flow model (“DCF”) and analyzing value makes sense in the public markets, but in the private markets companies can go years without any revenue—so is a DCF approach still valid?
Yes, because ultimately the stock price is still based on the future discounted cash flows, just as it is in the public market securities:
Though revenue and positive cash flow in private companies may be years out into the future, it does not change what investors are paying for when they purchase stock in such companies. At some point in the future the company must make money, otherwise the future value of the stock price would be $0.
As an example to understanding the DCF model in a private company setting, it makes sense to use the private market bellwether, Uber. The table below shows valuations at various financing stages, annual growth rates, revenues, and EBITDA. Based on the DCF, the enterprise value of Uber is calculated and shown below (Table 1).
Given that Uber shares are not liquid, a discount for lack of marketability (“DLOM”) is applied against the Enterprise Value. The DLOM used in valuation will depend upon a number of factors, including the stage of the company and time to liquidity. Using the DLOM table (Table 2 in the appendix) and assuming Uber’s IPO as planned in 2019, one could justify using a 9% DLOM since the time to liquidity is 1.5 years and the company is in its growth phase.
The cost of equity is determined by the risk free rate plus the risk premium associated with the financing stage of the company as shown in the table below. The discount is understandably highest at the start-up phase since revenues and positive EBITDA cash flows occur in future years once the product is developed and sold (see Table 3 in the appendix).
For Uber, the last valuation was May 2018 with a secondary transaction with a $62B valuation. The valuation graph above highlights the point of peak valuation that occurred about a year ago. In that time, the Valuation/forward revenue multiples contracted from 7.3X to 4.3X. As one would expect, investing in companies with high multiples of forward revenues is very risky; investors in the Series F & G have not seen share appreciation. Understanding the upside and downside value provides important information about the likely range of outcomes.
An observation of the DCF model is that the high growth period for the company accounts for a small percentage of the valuation. The majority of the value is the terminal value which is determined by the cash flows into perpetuity in the future expected time period of stability. The high growth trajectory, however, is critical in determining the ultimate stable growth EBITDA. The high growth rate creates the value inflation as the future cash flows and stock price will be ‘juiced’ by the trajectory of the growth rate.
Determining Upside/Downside valuation range
The Discounted Cash Flow (DCF) approach combined with comparable multiple on revenue provide the basis for triangulating around a valuation range when evaluating an investment. However, determining fair market value of the enterprise is only part of the analysis. Understanding the range of likely outcomes which incorporates the future dilution provides the basis for determining the likely investment volatility. To assess the upside and downside of potential future security value, the investor needs to determine the expected future values at liquidity based upon various scenarios: IPO, Merger/Acquisition, remaining private, or dissolution. Each of these scenarios will be impacted by future dilution as companies raise capital and issue more shares. All things being equal, given two companies valued at $20M, investors would rather own stock of a company with an upside/downside profile of $100M/$15M versus $40M/$10M upside/downside range.
So how does an investor predict with an accuracy future value of a company pre-revenue company that is facing several future financings?
The same way investors do it in the public markets: they make growth rate assumptions and apply the valuation techniques of DCF and comparables to triangulate. Like any private company, Uber’s possible exits include IPO High (high multiple), IPO Low (low multiple), Merger/Acquisition (High Multiple), Merger/Acquisition (Low Multiple), Stay Private, or Dissolution. Doing the math, in an IPO scenario the value of the underwriting price next year would be $64B in 2019 based on DCF Model with growth assumptions, cost of equity, and discount for lack of marketability would have a revenue multiple of 3.41x.
As shown in the table below, the revenue growth is the driver of value. As part of the DCF analysis it is assumed that the management will slow down the expenses as it prepares for a 2019 IPO.
In the event that Uber should go public with an expanded multiple an investor might assume 4x revenue based on 2020 forecasts of $19B. In this IPO High scenario, the valuation would be $75-$80B ($19B in 2020 * 4x multiple). For the IPO Low scenario, the investor might assume that the multiple is 3X. Other liquidity scenarios for Uber are the possibility that Uber is acquired or remains private.
As part of exit scenario analysis, the investor would need to incorporate the potential dilution that occurs as companies issue shares through future financings. Those future financings will have valuation and preferential terms. For instance, Uber’s IPO may be delayed to 2020; at their current burn rate the company will need to raise a Series I at future valuation (based on application of the DCF valuation at time of Series I issuance).
These scenarios provide the basis for determining upside and downside valuations as shown in the table.
The scenarios are probability weighted based on the likelihood of that outcome. The illustration of scenarios by year is reminiscent of spanning tree that is used in the Binomial Pricing and Black Scholes used in the public markets. This relationship is why the GAAP 409a valuations are based on the options pricing method.
Calculating the Upside Valuation
For Upside valuation, investors will select the scenarios that are the most optimistic: IPO High, M&A, and Private. To get the expected value based on these high multiple exit scenarios, we apply probabilities to each scenario. Based on management's recent comments we would predict that the IPO is the most likely outcome and therefore weight it more than the M&A or staying private scenarios.
Running the expected value for the scenarios IPO High, M&A High, and Private, we get a probability weighted value for Uber’s likely IPO in 2019. The weighting of the IPO High is greater than the other scenarios to reflect the scenario as the most likely. The value and returns for each class of securities for the upside case is shown below.
Calculating Downside Valuation
The Uber downside scenarios would be affected by future financings and terms, especially if the growth of the company slowed leading to extended negative cash flow. The IPO Low downside case may require the IPO timing to be 2020, which would require another financing of a Series I based on future value in 2109. If the Series I was issued in 2019, the valuation would be based on the forecasted numbers of the next year’s DCF. In this case, assuming another $1B is raised in a Series I at the $55B pre-money value, the valuation would be calculated incorporating this Series I. In the payout analysis, the investor evaluates the three downside cases—IPO Low Multiple, M&A Low, and Dissolution—and weights each of these scenarios based on the likeliness of their occurrence.
The IPO Low scenario has a lower valuation at the 2020 IPO and assumes that a Series I would be raised in 2019. In this downside scenario, the investor would incorporate the worst case M&A and Dissolution case. If things went terribly wrong at Uber, Dissolution is a real possibility because of the $4B+ in losses. The dissolution case may not large but it is not 0%.
Similar to the upside valuation, one assigns weighted probabilities to each of the scenarios as we did with the upside valuation scenarios. With the upside valuation ($78B) and downside valuation ($45B) calculated—representing the range of likely outcomes of exit values—the Series G investor will yield an IRR of 2.42% based on the $68B investment made in 2015 and allocations amongst the various security classes. Each of these securities have different terms that affect the total value allocated based on liquidation preferences, conversions, participation, and payout order. The payout to each of these securities is determined by the payout waterfall.
The Payout Waterfall: Valuing individual securities based on preference terms
Private securities are illiquid and susceptible to dilution as the company issues more shares over time to fund growth. In addition, private securities have economic terms associated with them that affect payout order and protect downside. The following are terms that affect security value.
Below is a representation of the payout ‘waterfall’ that shows the distribution of value paid out to securities as the value of the company increases. In the case below, the seniority of preference is in order of: Convertible Debt, Series A, Series B. In addition to seniority, these security classes have different economic terms (e.g. Series A has participation rights whereas Series B does not). From the payout waterfall we determine the value that each security class would be paid in a liquidity event.
The illustration below highlights how value is distributed at different valuation points for a company. The preference terms described above create three distinct payout ranges: the liquidation preference, the participation range, and the conversion phase. In the liquidation phase (pink, purple areas), securities receive value until a threshold share price is reached. In the participation phase (orange and yellow area), the preferred securities participate in value allocation after after the preference payments are paid without converting to common stock. Finally, once thresholds are met, the preferred securities convert to common stock (the green area). As the value of the enterprise goes up in value, different securities will be allocated different percentages at each payout tranche as the value of the enterprise increases.
Putting together the upside and downside scenario analysis and the payout waterfall based on the preferential terms, the investor can determine the likely range of outcomes. For example, based on the analysis, the Uber Series G has a likely range of outcome of $52 - 68/share. At a cost per share of $48 the internal rate of return is 1% - 8% which is not the rate of return that one would expect from a private investment given the risk of bankruptcy and dilution and the lack of liquidity.
As the Uber example illustrates, an investor would benefit from the risk adjusted analysis in determining if an investment is worthwhile. Price matters and the analysis can elucidate the likelihood of an investment achieving the expected returns given the risks inherent in the private markets.
Risk-Adjusted Private Investing in practice
Though the analysis above makes the process look simple, investors are still faced with a glaring problem: how can they actually implement this risk adjusted strategy given all the complexity of the analysis and all the data that is needed to input?
As one of the most famous and successful venture capitalist once said about understanding the private security analytics, “They [private investors] should care [about the analytics] but don’t care.” The issue is not that investors should care about the analysis and do not, but more that they do care but can not gain access to it in a timely manner without significant work and an army of analysts. All markets, including the private capital markets, evolve as technology evolves. Current private investment management platforms provide limited on-demand decision support to allow investors to evaluate risk and return at the individual investment and portfolio level., The next-generation private capital investment platforms bring public market analytics and transactions platforms to the private markets. These platforms, such as AllRounds, have the computational power to scale with the massive data sets that comprise capitalization tables, financial statements, and transactional data.
Next-generation platforms such as AllRounds are designed specifically to enable investors to manage assets by applying risk adjusted strategies at the portfolio and investment level. They also provide the capabilities to manage future rounds of financing as companies grow toward liquidity events. With the access to critical investment insight, investors can manage risk adjusted returns and better control performance. Technological advancements in on-demand platforms combine critical transaction platforms, analytics, collaboration, security, and interoperability with other data services and exchanges. These systems also scale and provide easy access to complex and comprehensive analytics, eliminating the need for inefficient and error-prone spreadsheets and point tool solutions.
Any investor who invests in private securities has the right to the company’s capitalization and financials which form the basis of valuation and other economic terms. For the private investor who does not know the valuation, the actuals and forecasts, and the capitalization information before investing in a private security…caveat emptor.
The risk of devaluation or loss of capital is much higher with private companies, which is why the success rate is so low. Understanding how the valuation and share price is affected by the company’s performance as well as the impact on future dilution and preference payments is critical in risk adjusted investing.
The method of determining value and managing a portfolio in the private markets is based on the same methodologies as in the public markets. Risk adjusted investing is common place in the public markets and the result is less volatility and more predictability. In these times when investors’ multiples are contracting, the private investor will be well-served understanding the risk/reward of investments going forward. Understanding how to make risk adjusted investment decisions will provide insight in the portfolio and at the individual investment throughout the private capital cycles.
The risk adjusted approach is time-agnostic. At each point in the private investing cycle, whether multiples are contracting or expanding, the investor applies risk adjusted investing techniques to determine the likely outcomes incorporating future dilution assumptions and preferential terms.
Using the risk adjusted investing techniques, investors are actively managing the return and risk of the portfolio. Investors can make decisions that allow for return to be captured while lowering the risk of the portfolio by rebalancing. The investment process evolves mitigating and diversifying risk, maximizing return, minimizing volatility, and rebalancing portfolios. With the accurate information accessible to investors in real time and the ability to measure risk and value based on financials, investors can evaluate investments and portfolio with an entirely new prism.
About the Author
Jamie Cohan is the Founder/CEO of AllRounds, an advanced private investment and company finance management system. AllRounds provides the most advanced investment management systems for the private capital markets to facilitate primary and secondary transactions. Prior to AllRounds, he was Founder/CFO of Andromedia, a web analytics and direct marketing company acquired by Adobe for $400M . He has had several successful early stage investments, including Penumbra (PEN) and Telltale Games. As an active investor utilizing the power of AllRounds, he has consistently achieved 7X returns on his investments while diversifying his portfolio risk. Please direct any further questions or interest to:
CEO/Founder AllRounds, Inc.
The table below displays the discounted cash flows for Uber from 2018-2024 . The rows of the table:
Row 1: Revenue growth year over year
Row 2: Forecasted revenue for the next year (i.e in 2016 next years forecasted revenue is $12B)
Row 3: The actual revenue reported in the year
Row 5: Ebitda for the year
Row 6: Discount for lack of liquidity - Based on the entries in Table2 a discount is applied based on the estimated time before a liquidity event occurs. This table is based on empirical evidence (such as the Longstaff study from 1995)
Row 7: has the cost of equity based on the stage of the company in Table 3
Uber’s Dividend Cash Model:
Discounted Cash Flows for Uber, 2018-2024
The Discount for Lack of Marketability represented by the table below is the discount based on the years until liquidity (IPO, M&A, Dissolution). In Uber’s case, the plan is to go public in 2019 (1 year from now), so the DLOM for a 30% growth company is 7%.
Finnerty Sensitivity Analysis
The Scherlis and Sahlman table displays the discounts applied to different finance stage companies.