The Benefits of Dynamic Value Investing

Recently I had an “aha” moment that made me realize a consistent mistake that is hurting the results of many value investors.

Recently I had an “aha” moment that made me realize a consistent mistake that is hurting the results of many value investors. I was talking to a friend about how it would have been near-impossible to predict the long-term success of some of the companies that have produced the best 20- and 30-year stock market returns in advance. Then it hit me: that statement was only true at the beginning of that time period.

What do I mean? If you were sitting at your desk 30 years ago and were asked to look out 30 years into the future, your likelihood of predicting either the business or the stock-market success of these top performers would be almost nil:

However, does that really mean that you couldn’t predict any of it? After all, many of the companies on this list aren’t some one-hit wonders or beneficiaries of new technological breakthroughs. A number are in boring, mature industries that have experienced relatively modest changes. What’s more, many of these continued their amazing stock return trajectories over most of the 30 year period rather than a brief spike in the stock price which, if missed, would have caused you to forego most of the excess return.

So what is the mistake that so many value investors make? And how can we improve our process to avoid it?

Value investors have caught on to the need to assess the quality of the business and management. The excess returns due to simple statistical cheapness have at best greatly diminished and more likely have been largely eliminated. However, for most practitioners this tends to be a rather static assessment.

At the beginning of the research process, they make a qualitative judgement about the business. That judgement is rarely updated, if at all, barring some catastrophic developments that make the impairment in quality obvious.

The intrinsic value estimate is updated more frequently, but changes are still usually small. Furthermore, I have observed that value investors are more on guard against negative development in business value than they are attuned to those that should increase their value estimates.

Here is what’s happening:

• Investors heavily anchor on their initial value estimate and appraisal of company quality

• They under-react to new developments, or in geek-speak, they don’t properly perform Bayesian updating by giving way too much weight to the prior and not enough to the new evidence

• They are more on guard against negative developments that could lead to losses, so they particularly under-update their value estimates when the evidence suggests it should increase

This all makes sense. Young value investors are taught to have conviction in their work and discipline in selling the stock once it approaches their appraisal value. They look down on Wall Street analysts who move their price targets around willy-nilly, seemingly just as a way of rationalizing whatever conclusion they want to reach rather than as the driver of that conclusion.

This same discipline that value investors pride themselves on has a hidden downside – it causes a great deal of rigidity. Because of this, they:

• Underreact to negative developments and hold losing stocks for too long

• Sell their winners too soon because they fail to sufficiently increase their value estimates in response to positive news

The last point needs to be emphasized: it’s very hard for most value investors to increase their value estimate meaningfully after a favorable company result that also causes the market to bid up the price of the stock. This would go against the grain – it would feel like giving in to the temptation to switch to a momentum approach that so many value investors despise.

I will share a personal story to illustrate the point. One of my best and worst investments was Microsoft. I correctly identified the pessimism reflected in the price of around $25 in 2013 as unwarranted and purchased the shares. Over the next couple of years the stock doubled, and I happily sold and patted myself on the back. I never looked back as the stock reached the current levels of $400+. Oops.

Most likely I wouldn’t have been able to hold on for the whole ride, even with a much better process. However, had I not been so rigid in my assessment of value and so anchored on my initial estimate I would have surely made a higher return. Furthermore, the extra effort required would have been a fraction of the original research needed to properly assess and value the business.

So what is a better approach? How can we reconcile being disciplined value investors and yet appropriately update our value estimates, up or down, based on new evidence?

I suggest the following:

• Focus on the end points of the range of values rather than the point estimate that represents the most likely scenario

• Categorize each new piece of evidence, at a minimum each reported result, as either consistent with, better than or worse than your current investment thesis

• Have automatic “trip wire” actions in place if the new evidence is either better than or worse than your long-term expectations for more than one reporting period in a row

• Have rules in place that prevent you from automatically selling investments based on your prior value estimates if the “trip wire” has been activated for positive reasons or from automatically adding to your position if it has been activated for negative reasons

The current mental model that many value investors use is of a fixed estimate of value they deem to be most likely, with a range sometimes thrown in to measure risk/reward and acknowledge business uncertainty. Instead, we should recognize that the point estimate we believe to be the most likely intrinsic value is one that is the least stable and the most susceptible to change based on new evidence. On the other hand, the end points of our range of values, if properly estimated, should be much more robust. So we should invert our process – rather than anchoring on the most likely value, we should constantly be thinking about the low and high end of the value range and using new evidence to decide in which direction reality is moving.

For example, let’s say we have a retailer that has 100 units, and we think it could get to anywhere between 200 and 400 units in 10 years with 300 as our most likely scenario. We should give very little weight to the mid-point of 300 and put much more emphasis on thinking whether new evidence provides more support for an outcome closer to 200 or to one closer to 400. If in the first year the company successfully opens 40 units, that is clearly a piece of evidence making the 400 outcome in 10 years more likely than it was prior to that information being available.

Is all of this going to allow us to find and stick with all the 30-year winners like the one in the earlier table? Probably not. Finding and sticking with even one would be an amazing accomplishment. However, it should allow us to be more accurate in our estimates of value, cut our losses appropriately when evidence suggests we were wrong and capture more of the multi-year upside for those companies that are consistently exceeding our estimates.

Change your focus from the level of quality and intrinsic value to how both of those are changing. That’s the best way to get your mind to mark your estimates to reality.

If you liked this article, please “like” and share this article. If you are interested in learning more about the investment process at Silver Ring Value Partners, you can request an Owner’s Manual here.

About the author

Gary Mishuris, CFA is the Managing Partner and Chief Investment Officer of Silver Ring Value Partners, an investment firm that seeks to apply its intrinsic value approach to safely compound capital over the long-term. He also teaches the Value Investing Seminar at the F.W. Olin Graduate School of Business.