Deep value investing is about buying companies that other investors don’t want. It is about investing in companies where the current situation doesn’t look great — actually in many cases it looks horrible, asserts Jack Forehand, co-founder and president at Validea Capital and partner at Validea.
On average, investors tend to overestimate the problems in these types of businesses and as a result, stocks of these companies get cheap.
Value investors historically have been able to profit when those very low expectations are exceeded. So the fact that value strategies typically buy low quality companies isn’t a bad thing. It is part of why value investing works.
Although value stocks have produced an excess return on average, there will always be a group of companies where the market has not overestimated how bad things are and that are fairly priced.
There will also be companies where things are actually much worse than market expectations. That last group are commonly referred to as “value traps” and weeding them out is a big focus for all value investors, whether they run quantitative strategies or not.
In this article, I wanted to look at some of the ways we have found that can be helpful in trying to avoid value traps. But before I do that, it is important to understand what is possible, and what is not. There is no method I have seen that can eliminate value traps in a value strategy. Even reducing them in any significant way is very difficult.
The reason goes back to what I talked about before. Value investing involves buying companies with low expectations that are out of favor. The market is very smart, and when its collective wisdom thinks that a company deserves to be cheap, much of the time it does. There is no way around that.
Negative Quality Screens and Value Strategies
When it comes to reducing the impact of value traps, we have found that negative quality screens work better than positive ones. A negative screen is simply an approach that filters out bad companies using the criteria you select instead of looking for good ones.
High quality companies can certainly be good investments, but they typically aren’t cheap. So adding a high quality filter tends to reduce a strategy’s exposure to value. Negative quality screens have the advantage of filtering out bad companies while keeping a similar value exposure.
What we are trying to accomplish with the negative screens we use for value traps is not to eliminate them, or even dramatically reduce them. We are just trying to make improvements around the edges that can reduce them enough that we produce positive effects (reducing value traps) that exceed the negative effects (eliminating companies that end up doing well).
When we do this, we like to look at it from a practical standpoint and to focus on criteria that might help us identify situations where the historical data we rely on to select value stocks might not fully reflect the reality of the business we are looking at.
Here are some criteria we have found helpful:
1) Earnings That Are Expected to Fall
Analyst estimates are notoriously unreliable. But despite that, they are usually directionally correct when large deviations are forecast. If something has dramatically changed between the past results we use in our valuation ratios and what is likely to happen in the future, estimates usually reflect that.
2) Cash Flows Not Keeping Up With Earnings
Cash flows are more difficult to manipulate than earnings. We filter out situations where cash flows paint a significantly worse picture of the business than earnings do.
3) High Debt
Debt magnifies everything. If a company has problems, and most value companies do, debt makes them more difficult to overcome. We screen out the companies with the highest debt using a composite of different metrics.
4) Deteriorating Fundamentals
We have a Twin Momentum strategy we run for our website that is based on a paper by Dashan Huang. The strategy uses seven variables (earnings, return on equity, return on assets, accrual operating profitability to equity, cash operating profitability to assets, gross profit to assets, and net payout ratio) to calculate a firm’s fundamental momentum. We have found that inverting that and excluding the companies with the absolute worst fundamental momentum can help to reduce value traps.
5) Poor Economic Margin
For a company to be a viable entity, it should earn a return on capital that exceeds its cost of capital. If the reverse is true, providing a company with more capital doesn’t make sense. We filter out the companies with the biggest gap.
6) Low Relative Strength
We use this as a catch-all criterion to try to pick up companies that the other screens missed. If a company is at the absolute bottom of the market in terms of relative strength, often there is something very negative going on, even if it isn’t reflected in the other fundamental screens.
Once we have ranked our universe using these six criteria, we then create a combined ranking that combines all of them, and the worst 10% of all stocks are eliminated.
Our approach is just one of many ways this can be done and we have seen other approaches that do it very differently that are also very sensible. Our goal is to try to reduce exposure to situations where the fundamental data we rely on may reflect a very different picture than reality.
Value traps will never be eliminated, and any attempt to eliminate them will likely come with the consequence of also reducing exposure to companies that go on to perform well. But negative screens can help reduce their impact on a value portfolio. We have found that using these criteria can help to do that.