The Rare Rational Asset Manager — Value Stock Guide

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Shailesh Kumar
The Rare Rational Asset Manager — Value Stock Guide


Let’s imagine an asset that you are considering acquiring. You know that there is a high likelihood that the price of the asset will be lower in the near future, than it is today.

Will you go ahead and invest today, or would you wait until the price is lower?

Or perhaps the asset is expensive but comes highly recommended. Will you go ahead and buy it believing “so many experts can’t be wrong”? Or would you rather look for something else that gives you a better value for your dollars?

In most real world situations, a rational person weighs different options and comes to a decision. The decision matrix for buying a car may look something like this

A Sample Decision Matrix for Buying a Car

The buyer has certain attributes that he considers very important. Some attributes are more important than the others. For example, cost and safety are the most important attributes valued by the buyer, power and fuel efficiency may not be as important. For our buyer, comfort is important and could be a tie-breaker, but he may not really be going after comfort as a primary quality.

Sports cars don’t really work for our buyer. He is very cost conscious. A used sports car makes it a little better, but then other attributes do improve the value proposition too much. It is clear that the choice is between an Entry Level Car, a Middle of the Road Car and a Luxury Car.

In this case, even if the buyer considers cost to be the most important factor in choosing the car, he may still end up buying a Luxury Car as other qualities he considers important may more than makeup for the cost disadvantage.

This is rational decision making. We all engage in this in our daily lives. Perhaps we end up buying a bigger house than we were looking for, but there were reasons to pay up. We valued those things the more expensive house offered.

Please note that in the above example, if our buyer gets a very nice deal on the Middle of the Road Car, such as the cost rating is 5, the value proposition for the Middle of the Road Car becomes better than the Luxury Car and the decision might very well be different.

If the buyer wanted to be able to sell the car later on, then Resale Value would be another attribute added to the decision matrix. In that case, the purchase decision could very well be very different.

We are able to be rational about these types of decisions as we spend time considering the pros and cons of various factors.

The same rational person acts very differently when it comes to investing.

What accounts for the fact that investors are more likely to buy stocks that have already risen and sell the stocks that have already fallen?

Or looking at this another way, a typical investor’s portfolio is more likely to be fully invested during the times of elevated market valuations, while most investors are likely to be in cash after the markets have fallen significantly.

There is significant herding behavior among investors, including the asset managers today. For example, many decision matrices today among retail and professional investors may look something like this

A Typical Investor Decision Matrix

Here FOMO stands for Fear or Missing Out. Safety in Number implies investing in assets where others are investing as well a.k.a the herding behavior.

During the times of market exuberance, the factors considered by investors become skewed. Rationality goes for a toss. This creates bubbles.

A recent joint study done by State Street and MIT Sloan School of Business looks at the crowded trades and how it can be a predictor of asset bubbles.

To quote from the paper

We show that investors could have profited by overweighting sectors within the U.S. equity market that were crowded but not overvalued and by underweighting sectors that were crowded and simultaneously overvalued. This result extends as well to other equity markets that we tested. We also produce results showing that investors could have profited by deploying the same strategy to manage exposure to well-known equity factors.

We begin by describing asset centrality, and we offer conjectures about why it may be associated with crowded trading. We then describe a relative value measure that we use to separate crowding that occurs during a bubble’s run-up from crowding that occurs during its sell-off. Next, we examine some well-known bubbles, and we show how our centrality and valuation measures evolved over the course of these bubbles. Then we apply our measures out of sample to identify bubbles among sectors within the U.S. stock market. We also apply our methodology to other equity markets and to well-known factors in the U.S. equity market. We present persuasive evidence of the efficacy of our methodology.

The authors define crowded trades based on a measure of asset centrality defined by price movements. Therefore, highly correlated assets imply high asset centrality. FAANG stocks will fit this definition. Index funds of all kinds meet this definition as well.

Valuation is being defined simply as price to book value.

Bubbles arise in sectors that show high asset centrality and overvaluation. The sell offs are more brutal than the rise.

The decision matrix for a rational asset manager does not recognize FOMO and Safety in Numbers as a factor in evaluating assets for investment dollars. Once you assign 0 values to these weights, Undervalued Assets and Quality Assets become the most attractive destinations for investment. Fundamentals become important.

As we sit here in the Summer of 2019, the market valuations are high, momentum is where investors are putting their money and asset centrality is increased with significant crowding in selected stocks and indexes.

Anecdotally, this year the most popular article on VSG has to do with buying IPO stocks. I was hesitant to post that article as it goes against everything I believe in as a value investor — but it provides me with an excellent barometer of the investment climate today.

I think we should worry about a market crash. There are many additional reasons why.

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