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Disconfirming Evidence and the Feedback Mechanism

How to develop a system of seeking contrary information

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Nov 20, 2019
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When Charles Darwin found something that was contrary to his established conclusions, he quickly wrote it down so he would not forget or incorrectly interpret the new information.

This simple and powerful habit has two huge implications for investors:

  • Paying special attention to disconfirming evidences.
  • Building a feedback mechanism to avoid fooling yourself.

Disconfirming evidence

When explaining the scientific method to students, American physicist Richard Feynman said the following:

“In general we look for a new law by following the following process. First we guess it. Then we compute the consequences of the guess to see what would be implied if this law that we guessed is right.

Then we compare the result of the computation to nature with experiment or experience, compare it directly with observation, to see if it works. If it disagrees with experiment it is wrong. In that simple statement is the key to science. It does not make a difference how beautiful your guess is. It does not make a difference how smart you are, who made the guess, or what his name is – if it disagrees with experiment it is wrong.

Investing is a combination of art and science. With the science part, we better follow Darwin and Feynman. With any investment decisions, we have to develop the key hypothesis and assumptions. Then we need to “compute the consequences” of the hypothesis if we are right. Then we collect evidence and evaluate whether our hypothesis is valid or not.

While all this sounds good, few can do it in practice.

First of all, the quality and relevance of a hypothesis is hard to define. In the investing world, a common practice is to use an arbitrary valuation multiple as one of the key foundations of the hypothesis. For example, Disney (

DIS, Financial) should trade at 20 times earnings because its peers are trading at 18 times and Disney deserves a premium. Another common practice is to project earnings based on past experiences – the business should be able to earn X if we assume growth is Y and margin is Z. Combining the two practices, we get a common investment hypothesis:

If the business can earn this much next year, it should trade at this multiple and the price today doesn’t reflect that.

The problem with the multiple hypothesis is you can’t prove it wrong unless you add a time frame. But then you have to make assumptions on why the time frame is appropriate. Let’s say you think Wells Fargo (

WFC, Financial) will be worth 18 times earnings in five years. The economic growth, interests rates, regulatory environment and many other factors are all important in whether it’s appropriate to use the next five years as well as a multiple of 18. Baked into this assumption are many more key metrics involving many variables. It is the same with the earnings growth assumption.

What hypothesis should investors use then? I don’t have a perfect answer, but the hypothesis on competitive advantages sounds like a good one for me. Again, using Wells Fargo as an example. One of the bank's competitive advantages is the low cost of deposits. This is totally verifiable. You have all the dates you need from both Wells Fargo (

WFC, Financial) and its competitors to validate whether this key assumption is true or not. You then develop a hypothesis as to why Wells Fargo has a lower cost of deposits. Again, you can validate the assumption by gathering data and speaking to people in the industry. The important thing is, you have to have a non-vague verifiable hypothesis so you can develop a system to monitor whether you are right or wrong.

Building a feedback mechanism

Let’s say you have developed a good system of hypothesizing, how do you stay true to yourself? We all know human beings are very good at interpreting new information in a way that prior conclusions remain intact. This is a built-in mechanism. So we have to come up with counter-mechanisms.

Fortunately, we can stand on the shoulders of the giants.

Warren Buffett (Trades, Portfolio) offered two great mechanisms: writing an annual report and having a logical partner who is not subservient. Darwin had another one – an instant feedback mechanism in which he immediately wrote down conflicting evidence.

If we combine Buffett and Darwin, we can develop a feedback system that has two key elements:

  • Both instant and periodic feedback.
  • Outside oversight.

Of the two, I think finding a logical and outspoken partner is much harder because both qualities are rare. But building an instant and periodic feedback system is something you can pick up immediately.

Disclosure: No positions in Wells Fargo or Disney.

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