This is a bonus addition to the series of three articles exploring how we can improve the odds for future valuation multiples by Quantifying Our Stories in Scenarios:
Step 1: For Future Events
Step 2: For Long-Term Cash Accumulation
Step 3 illustrated that future investment returns through any investment horizon shorter than Warren Buffett’s “forever” are typically dominated by expectations at that horizon for a company’s long-term cash flows. Step 2 illustrated that cases for future company cash flow are influenced by the cases for business drivers that Step 1 illustrated.
But we’re still missing something. Now we are relying on cases for long-term cash flows expectations at earlier horizons, and those are influenced by expectations at earlier horizons for the events that drive those long-term cash flows.
Expectations for events can drive what investors put into their price-setting rationale at an investment horizon. Typically these expectations are not certain but probabilistic. While investors typically hesitate to write probabilistic expectations explicitly because that is impractical without tools like the Bullet Point Network Platform, some investors are indeed explicit in specific domains where it is more practical because investments are dominated by only a few probabilities.
Two of these domains are event-driven investing and biotechnology, so let’s start by looking at them and then considering how investors generalize this approach into areas with more uncertainties.
BPN’s co-founders cut their teeth at Goldman Sachs while its Senior Partner was Robert Rubin, who expanded the firm’s merger arbitrage business into a broader “event-driven investing” style before becoming US Treasury Secretary. Interviewed in Goldman Sachs; The Culture of Success, Rubin said of this investing style:
You had to stick to your discipline and try to reduce everything to plusses and minuses and to probabilities . . . It was a high-risk business, but I’ll tell you, it did teach you to think of life in terms of probabilities instead of absolutes. You couldn’t be in that business and not internalize that probabilistic approach to life.
Event-driven investors try to pay prices explicitly based on their probability of different outcomes to uncertainties like the closing of a merger deal:
Rubin was known for his focus on how future stories might change his reduction of stories to probabilities. His Deputy Treasury Secretary Larry Summers, who later became President of Harvard University, described this focus:
Rubin ends half the meetings with, 'So we don't have to make a decision on this today, do we?' New information will evolve.
We can see this ongoing re-pricing in stock price charts of merger targets as new stories change investors’ reduction to probabilities:
Like event-driven investors, some biotech investors write price targets explicitly based on their probability of the success of future events. Below, the “Probability-adjustment” of 18% is for the odds of regulatory approval of a company’s drug:
Certainly, to set these probabilities, investors can unpack them into probabilities for earlier events that influence regulatory approval, such as clinical trial phases. There is even abundant historical data on the frequencies of success in each phase conditional on success in the previous phase:
But each new drug is different from the average drug in its class, so investors seek to apply experience in reducing stories to probabilities as they read and listen to the views of researchers, regulators, insurers, doctors, and patients.
Generalizing this Approach
As illustrated in the first three articles, the Bullet Point Network Platform makes it practical to apply this approach to an investment in any company, estimating how changes in investors’ odds for events may affect the price they will pay for the company’s securities.
But in practice, how can we anticipate ahead of time how investors’ odds for events may evolve over time so we can anticipate how their price may evolve?
Calling Odds on How Odds will Evolve
With the Bi-Temporal Model of Future Horizons that we described in the previous article, we can produce cases for how prospective investors in virtualgoods.shop, for example, may change their expected odds of outcomes and the timing of those outcomes.
To do this realistically in practice, there are nuances to consider, including what billionaire investor George Soros terms, in his 1989 masterwork The Alchemy of Finance: Reading the Mind of the Market, the “reflexivity” between expectations and “actuals” over time, with self-reinforcing and self-defeating cycles between them.
Atop the Bullet Point Network Platform, we have built an Event Model that considers that nuance and others, making it practical for us all to focus on our views about the eventual odds, applying the best practices detailed in our first article, and then the Event Model will help us explore cases for how expectations may change over time between what is priced in now and what eventually happens.
Below, click on one of the best cases for expected revenue in the lower right to see how it is driven by a case for the change over time in investors’ odds for value proposition strength in each of virtualgoods.shop’s target markets (if you are reading on a smartphone, flipping to landscape mode helps with the interactive charts below):
Together with the Platform’s models for company long-term cash flows and valuation, as illustrated in the previous article, this Event Model enables us all to translate our insights on future events, from product launches to politics, into cases for company cash flow and valuation.
This can enable managers, and the investors who back them, to make better decisions about how much money to raise and to spend based on how and when valuation might change in the future as cash balance changes. Doing this better repeatedly can make a major improvement in managers’ and investors' career success.
As billionaire investor Peter Thiel writes in his estimable book Zero to One:
You can have agency not just over your own life, but over a small and important part of the world. It begins by rejecting the unjust tyranny of chance. You are not a lottery ticket.
This all starts with organizing stories continually, as illustrated in Step 1, to help us all use our human insight to question and enhance our quantitative scenarios continually. It results in quantification that can help us lean into the home runs and sidestep the train wrecks.
Bullet Point Network serves a client base of elite managers and investors who bring to our team companies and investments to work on together confidentially, Quantifying their Stories in Scenarios via these 3 steps to amplify their long-term returns.
They bring to the BPN team a business plan or investment thesis, plus their research and models that support it. Our team identifies templates in our Platform that suit the plan or thesis and responds within 5 business days with an Initial Underwriting that Quantifies their Stories in Scenarios to amplify the client's work into more scenarios for more confident strategy and investment decisions.
After the client provides ideas to improve this Initial Underwriting, she works iteratively with the BPN team to produce a Final Underwriting that supports high-confidence decisions.
Then with the Final Underwriting in our Platform, it continues to live and breathe. As the environment changes and the client accumulates information, such as around quarterly board meetings, the client and BPN's team can attach research and change judgments regularly to producing Reunderwritings that update the investment's outlook regularly and sincerely, without the enormous work that it would have taken to retrieve a slide deck, memo, and spreadsheet from a folder and rewrite them.
If you might like to try an Initial Underwriting with us, please tell us why below.