Valuing Early Stage Equity: An Optimism-Weighted Approach

Yan-David (Yanda) Erlich
Yanda’s Blog
Published in
8 min readAug 27, 2020


If you’re looking for the worksheet and want to skip reading the associated post, you can find it here.

Who Is This For?

If you’re reading this, you may already have an offer from an early-stage startup and are looking to understand the value of the equity portion of your comp package. For simplicity, let’s call this prospective employer Early Inc. You may even have multiple offers, including one from a later-stage company (Later Corp) that you’re comparing it with.

Let’s start with three things you should NOT do at this juncture:

  1. Discount the value of the equity to zero and focus solely on the base/cash portion of the package. If you choose your startup correctly, the equity will be the most significant portion of your compensation, possibly by orders of magnitude of your cash comp.
  2. Choose to work at a later-stage or public company strictly because their equity is easier to value. There are many reasons to choose a specific later-stage company over a specific earlier stage one, but ease of equity calculation shouldn’t be one of them.
  3. Multiply the shares you’d be granted by either the price-per-share (PPS) of the most recent round of financing or the most recent 409A valuation. Both of these calculations will provide you with the current value of the equity, essentially the value at which you’re “buying” the equity, but they won’t give you the value at exit, which is when the equity would be “equivalent to cash.” It’s the latter you’re looking to understand.

Estimating the value of startup equity at exit is hard work. An early-stage company faces a long and arduous journey prior to an exit that could take a number of forms, e.g. an acquihire, a medium-sized sale for product and technology, a larger acquisition, or an IPO in addition to a shutdown in the worst case or, on the flip side, the moonshot scenario of becoming a deca-billion-dollar category-defining disruptor.

The best way to account for all of these variables is by performing an optimism-weighted calculation.

Why Does This Matter?

Let me first tell you about a mistake I made many years ago.

In 2005, I had an offer from Google, a tech giant fresh off of its IPO. I also had an offer from Facebook, which was a tiny early-stage startup at the time. The value of Google’s equity in “2005 value” was 10x that of Facebook’s. I joined Google.

When Facebook went public seven years later, the value of both equity offers in “2012 dollars” (when Facebook’s equity was finally “equivalent to cash”) flipped dramatically — Facebook’s equity offer was all of a sudden 50x greater than Google’s.

Now, don’t get me wrong. I had a great time at Google and met many of my closest friends there, but I wish I had known to perform my own optimism-weighted calculation for both companies before making my final choice.

I want to help you avoid this mistake.

How Does It Work?

First, you’ll need to get some data from the company:

  1. The number of shares they are granting you (this should be in the offer)
  2. The latest valuation
  3. The latest price per share (PPS)

If they are unwilling to share this data, don’t join! It’s a massive red flag for a company to withhold any important materials you might need to make an informed decision about the next decade of your life.

Second, you need to forecast a series of scenarios that the company could ultimately wind up in. At the very least, I would propose sketching out the following:

  • A shutdown whereby the company ends up being worth $0
  • A small acquihire
  • A modest sale to a competitor
  • A meaningful sale to a large private company or a public one
  • An IPO
  • Becoming a category-defining public company

Next to each scenario, you should estimate the probability of the outcome as well as the amount the company would be worth.

One thing you absolutely do NOT want to do is ask the founders or hiring managers to provide these forecasts. You can and should do your own due diligence regarding the company’s thought process on the grander vision, the opportunities that lie ahead, the pitfalls, etc. But you need to fill in the outcomes and probabilities yourself because you want your optimism reflected back, not theirs.

There are three questions I like to ask the company representatives to help me think through the possible outcomes and their probabilities:

  1. In your wildest dreams what does this company look like? And what needs to go right for that outcome to be realized?
  2. The company hasn’t achieved your wildest dreams. What happened and what does it look like instead?
  3. Tell me about the worst-case scenario, i.e. the company failed. What happened and why?

You should end up with a table that looks like this, but with your own scenarios and numbers:

Next Steps:

  1. For each scenario, compute the price per share for that scenario using the following formula:

2. Compute the optimism-probability weighted average PPS

3. Multiply that PPS by the number of shares you are being offered

This calculation is incredibly informative as it’s a reflection of your own view of the future potential of Early Inc. The more excited you are about it being a big category-defining company, the more you will see that reflected back in the optimism-weighted value of your shares and vice versa.

To make this interactive, I’ve set up a worksheet that you can copy and play around with here.

What Are Reasonable Probabilities?

What is a reasonable expectation for the probability of a company shutting down or going public? Base rates can inform your judgment. For the cohort of startups founded since 1995, the histogram of the probability of outcomes looks like this:


That said, if you’re relying exclusively on the base rates above, you’re essentially telling yourself that Early Inc is an “average company,” and that could end up dramatically underestimating the outlier outcomes that you’re so carefully attempting to factor-in. So you should use these base rates as a sanity check rather than a replacement for your own probability projections.

Advanced: Additional Dilution

In an effort to increase the accuracy of your final projections, albeit slightly, you could also estimate how much additional dilution the company will incur from future rounds of financing. I wouldn’t worry too much about getting this 100% correct as the effects from additional dilution will likely be subsumed by the margin of error of your probability estimations anyway. But the general adage here is that the bigger the exit valuation (as a multiple of today’s valuation), the more rounds of financing (and dilution) the company is likely to incur along the way.

To incorporate this, you’d have to make a small tweak to the PPS calculation in the algorithm above:

This variable is reflected in the linked worksheet. If you want to ignore additional dilution, just set it to 0% for every scenario.

Comparing Offers

The optimism-weighted approach is also incredibly useful if you want to compare two companies against each other. Fill in the values for each entity and see how the weighted average differs. This approach affords the ability to do an “apples-to-apples” comparison between an early-stage opportunity with a later-stage one, which the more commonly used approach of multiplying the granted shares by the latest valuation PPS does not.

For illustration purposes, let’s look at two hypothetical scenarios:

1. Versus another Early Stage Offer

First, let’s compare Early Inc to OtherEarly Corp. To showcase the importance of the optimism-weighted probabilities, I’ve made the values equal across the board for both companies except for the P(Outcome) columns (Columns C and K in the worksheet). Notice how this impacts the end result: Early Inc’s optimism-weighted value for your shares is more than 40% greater than for OtherEarly Corp. Also compare the (useless) value today to the optimism-weighted average: the latter is 120x greater.

2. Versus a Later Stage Offer

Now, let’s compare Early Inc to a later-stage company (Later Corp) with a current valuation that’s 20x greater. In this case, Later Corp’s valuation today is $200M to Early Inc’s $10M, and the today value of Later Corp’s equity grant is 5x that of Early Inc’s.

The probability of worse outcomes for Later Corp is also lower, given that the mortality rate of startups tends to decrease as they raise more money. Nevertheless, since we have a more optimistic view for Early Inc over the long run, the optimism-weighted average reveals that Early Inc shares are worth more than 3x those of Later Corp.


Is the optimism-weighted value the correct one? The only way to find out is to work at Early Inc for the next few years, or decades. If your own optimism for the company suggests that you should take the offer, you hopefully won’t regret it, even if your calculations are a little off.

About the Author

Yanda Erlich is a General Partner at Coatue Management (“Coatue”), where he leads the enterprise software practice for Coatue’s venture fund, which invests in pre-Seed to Series B companies. Yanda led Coatue’s investments in Weights & Biases, Impira, Fin, and, among others. The opinions contained herein are his own and are not the opinions or views of Coatue. Moreover, the opinions expressed in this blog should not be considered employment, investment, tax or other advice from Coatue and Coatue may or may not hold positions in the in the companies referenced in this article.

Prior to joining Coatue, Yanda founded four venture-backed B2B companies: two were acquired (Mogad and ChoiceVendor), one failed (Happiness Engines), and one is still going. The latter is Parsable, which he founded with colleagues Ryan Junee and Chase Feiger and ran as CEO for the first 5 years before Lawrence Whittle, then CRO, was promoted to CEO.

Before becoming a professional investor, he was an active angel and an early investor in Mixer Labs (acq. Twitter), Thumbtack, MasterClass, CircleUp, and Buddybuild (acq. Apple). Yanda started his career with software engineering and product management roles at both Microsoft and Google.



Yan-David (Yanda) Erlich
Yanda’s Blog

COO @weights_biases. Formerly GP @ Coatue and 4x Founder/CEO incl @ParsableHQ. Angel @thumbtack @masterclass