Why Accepting That There Are Things You Can't Know Gives You An Advantage

{ Euclidean Q3 2009 Letter }

Certain information from this letter relating to individual positions has been redacted

We launched our fund fourteen months ago. The date was August 7th 2008, and the S&P opened at 1286. Little did we know that, just weeks from then, the extinction period for many funds would begin and the markets would bottom in March 2009 after a brutally swift 48% decline from our date of inception.

You could say that our launch date proves we have no basis for timing the market!

Fortunately for our investors, our strategy is not dependent on market timing. Euclidean has both survived this historic time and delivered positive returns to our investors. As of September 30th 2009, our investors at inception have realized net positive returns of +32.8% whereas if they had been indexed to the S&P, their assets would have declined in value by -15.6%.

Last month we met with a potential investor. We explained that while we expect to perform well over long periods of time, we feel that our first year was unusual and that we are unlikely to outperform the S&P by such a margin again in the future. He accepted that point and then asked what caused our strong start. Perhaps being caught off guard, we answered, “We have done well because we accept there are things we cannot know.”

Surprised, he followed up with, “What do you mean? How can not knowing be an advantage?”

We answered, “Because it forces us to focus on evaluating companies based solely on the few things that we can know for certain and frees us to capitalize on things other investors think they know but sometimes really don’t know.”

Here is some color for this point. 

  • Do you ever read Barron’s or watch CNBC? If you do, you may notice that there is no shortage of pedigreed experts ready to share their opinions on what individual companies, the overall market, and the broader economy will do in the quarters to come. Investors (both professional and individual) often seem greatly influenced by these expert predictions. Given this, it seems that many investors believe other people can predict the future. 
  • Or, do you notice the extent of qualitative (or difficult to quantify) factors that many analysts rely on when determining whether to recommend a company’s stock? An analyst might visit with the CEO to evaluate the strength of company management, go to conferences to determine how the company’s industry is evolving, and talk with customers to evaluate the likely acceptance of the company’s new products. The idea seems to be that, by searching for more information, perhaps one can better predict a company’s future. 

At Euclidean, we do not believe we – or anyone – can consistently and accurately predict the future.

Our skepticism comes in part from seeing experts repeatedly fail to foresee major shifts, such as what the markets experienced during the past year. Our skepticism comes also in part from evidence that analysts are not very good at predicting the future of individual companies. To this point, at the end of this letter, we provide some references to thoughtful works on the futility of trying to forecast the future that include findings such as: [a]

  1. The average margin of error in analyst estimates of companies’ earnings exceeds 40%.

  2. As experts have access to more information, their confidence in forecasting rises, but their accuracy stays similarly low.

  3. Analysts have a strong tendency to predict that recent trends will continue into the future.

  4. Experts on the whole barely outperform a coin toss in predicting the future.

Instead of replicating further what others have covered in detail, our purpose is to clarify our beliefs and assumptions so that you can understand how we approach things at Euclidean. So, now you have a view into why we do not believe it is possible to consistently and accurately predict the future. Where does that leave us given that our success is tied to finding companies today that will earn higher valuations in the future?

It leaves us looking to the past for answers.

Most students of valuation accept that the intrinsic value of a company is the value of the future cash flows, discounted to present value, that can be pocketed by a full owner for the remainder of the company's life. Where students of valuation diverge is how they go about estimating what those future cash flows are likely to be.

Since we operate assuming it is impossible to predict a company’s future cash flows – regardless of how many CEO discussions, industry conferences, and customer checks one does – we instead look to the facts that are available to us. These facts come in the form of companies’ publicly filed financial statements.

By digesting their operating histories, our systems are able to view today’s companies in the context of firms from the past that resemble them. By evaluating how those similarly situated companies from the past evolved both operationally and from a market value perspective, our models have a fact-based context for evaluating the current company at hand. This evaluation occurs without succumbing to the temptation of trying to predict the future. Here is an example of how this works:

{redacted text}

When you think about Euclidean and this example, please always remember the following things:

  1. We do not believe we, or anyone, can consistently predict the future with accuracy.

  2. Our models look for companies selling for substantially less than what companies with similar operating histories have sold for in the past. 

  3. We will typically find these kinds of opportunities, {redacted text}, when the marketplace is predicting very difficult times for a particular industry.

  4. Our approach puts great emphasis on finding companies that are conservatively financed so that they can preserve value even in particularly difficult times.


Please let us know if you have any thoughts or comments on this letter. We look forward to connecting with you in the weeks ahead.

Best Regards,

John & Mike

[a] To explore some of the data regarding the futility of forecasting, we refer you to following sources: