To Buy or To Sell, That is the Question

I was reading a recent article by Bloomberg news about Todd Combs, Warren Buffett’s new right-hand man on stock picking. The article illustrates how Combs consistently buys when prices fall. This buy-low/sell-high strategy is the counter-strategy of riding winners/paring losers which I’ve seen recommended by many traders, behavioral economists, technicians, and statisticians. So where is the truth? Like most disputed questions, the answer lies somewhere in between. Technicians, traders, and statisticians cite the fact that stocks that are down have a better than average chance of going down more and that the market probably knows something that you do not. Behavioral economists cite our tendency for loss aversion which causes humans to hold onto losers too long because of the aversion to realizing those losses and our tendency to sell winners too early because of a desire to “lock-in” profit. The problem with these arguments is that they ignore the crux of any rational investment decision.  Specifically, they should simply ask, “What is the value of the company? “

As can be seen in Todd Combs’ strategy (which just so happens to be the philosophy of Buffett as well), a true sense of business value is the driver of buy and sell decisions. When a stock price falls, all else being equal, the risk-reward has become more favorable. When the stock rises, the risk-reward becomes less favorable. This reason alone should be the driving force behind buy and sell decisions for those who actually fundamentally research companies and stocks. Clearly, if the stock is down, the market could be signaling something that the analyst has missed. It serves as a notice to question one’s research, to find the devil’s advocate. But after doing so, if the analyst finds that the facts have not changed, then the improved risk-reward created by a lower price gives the value investor an opportunity that other investors are willing to let slip by.

So what makes the value investor so special? Due diligence. Investors that lack the in-depth research required to understand the company, its financials, and its valuation are subject to the pressures of the market because they do not have the anchor of their conviction. Investors that do not have a calculated potential downside risk and a calculated potential reward, do not have the triggers that allow them to buy and sell with confidence. While clearly, these price objectives are only subjective estimates, they are rooted in concrete research and serve as the critical focal point in any conversation about buying and selling. So, if we want to answer the “To Buy or To Sell” question, the first question an investor must ask is “what is this thing I’m buying or selling worth?”  Even though most investors do ask this question, very few actually answer it with a number.  Doesn’t that seem odd?

The Role of Diversity in a Better Future

The future is like a complex algorithm with virtually infinite variables. Mankind does not know the optimal inputs for the variables. Nature controls a large number of the most powerful variables, but mankind can shape many others. One way to think of the future is that mankind is in a constant search for the optimal set of inputs to determine the future. This is not a conscious goal, but if you think about it, each individual, in their own tiny part of the world, is influencing the future by making decisions every day. Each decision affects a variable in the algorithm that results in our future. To determine the optimal set of variables, mankind uses a crude genetic algorithm (of course without knowing it) to search for the optimal set of inputs.

From Wikipedia: “A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection and crossover." 

A genetic algorithm (GA) is pretty much a fine-tuned method of making educated guesses, analyzing the results, and then using that information to make more guesses until a final set of “optimal” results is found. Each variable has a range of possible inputs. The GA will randomly mutate variables to make sure it isn’t going down a sub-optimal path. Mankind is similar in that its seemingly chaotic nature allows for a wide range of inputs. This wide range (diversity) and chaos (mutations) allows for more optimal results without getting stuck in rut (local minima). With diversity and chaos, the world is able to keep variables from falling into ruts and settling on sub-optimal solutions. This is why it is important to have Type As and Type Bs, OCDs and slobs, democrats and republicans. Each play their part in making the range of inputs as wide as possible.

Without differing opinions, the algorithm has no method to optimize the final results. It takes extreme inputs with sometimes horrific results for the system to purge sub-optimal paths (slavery, eugenics). Just like it also requires extreme inputs to find sea-change pulls towards optimality (democracy, language). So next time you get frustrated by an extremist pundit you don’t agree with, realize that they serve an important purpose in society. Without them and everyone else, the future would be sub-optimal. And if you still want to call them a name, call them what they probably are, a mutation.

The Cup is Half Full – Kahneman Style

After suggesting a solution and getting no negative feedback - “Gentlemen, I take it we are all in complete agreement on the decision here…Then I propose we postpone further discussion of this matter until our next meeting to give ourselves time to develop disagreement and perhaps gain some understanding of what the decision is all about.” – Alfred P. Sloan, former Chairman of General Motors

 

Alpha Theory revolves around questioning our own decision making. Much of the proof that decision making is fraught with foibles comes from Nobel Prize winning work done by Daniel Kahneman and the late Amos Tversky. Kahneman has an article out on Bloomberg.com about the Optimistic Bias called “Bias, Blindness and How We Truly Think” that is an important read for anyone managing money. Actually, it’s a good read for anyone that ever makes important decisions.

One of my favorite parts of the article is actually an idea from an “adversarial collaborator” of Kahneman’s named Gary Klein. His idea is the premortem:

When the organization has almost come to an important decision but hasn’t committed itself, it should gather a group of people knowledgeable about the decision to listen to a brief speech: “Imagine that we are a year into the future. We implemented the plan as it now exists. The outcome has been a disaster. Please take 5 to 10 minutes to write a brief history of that disaster.”

As a team converges on a decision, public doubts about the wisdom of the planned move are gradually suppressed and eventually come to be treated as evidence of flawed loyalty. The suppression of doubt contributes to overconfidence in a group where only supporters of the decision have a voice. The main virtue of the premortem is that it legitimizes doubts.

Furthermore, it encourages even supporters of the decision to search for possible threats not considered earlier. The premortem isn’t a panacea and doesn’t provide complete protection against nasty surprises, but it goes some way toward reducing the damage of plans that are subject to the biases of uncritical optimism.

This concept is very similar to the risk target required in each Alpha Theory analysis. The evaluation of downside is critical and it is important to create a process to make sure that an optimistic bias does not overwhelm logical decision making.

Capitalizing on the Random Walk

Just how volatile have the markets been the last two months? Would you be surprised to know that August and September 2011 rank amongst the top 5 most volatile periods in the last 50 years? I was. I knew things were bumpy but I didn’t realize they were Top 5 bumpy.

 

Volatile markets with high correlation can be the bane of the stock picker’s existence (Correlation article) because it is difficult to monetize idiosyncratic value when everything is moving wildly in the same direction. Many of the clients I’ve spoken to over the last couple of months have reduced exposure by lowering gross and net exposure. In fact, I was recently working with a client and developed a heuristic method to suggest gross exposure based on a few general factors:

 

A portfolio manager uses this rubric by defining the minimum and maximum gross exposure for their portfolio, defines a combination of external and internal factors to determine exposure, then creates Risk-On and Risk-Off parameters for each factor. The external factors like volatility, correlation, and S&P PE Multiple help highlight when the markets are difficult for fundamental portfolio managers to navigate. The counterbalance is the internal factors (Portfolio RAR and Downside Risk) that highlight the current opportunities derived from the firm’s investment process. Is the Portfolio Risk-Adjusted Return high and is the Portfolio Downside Risk low? If so, a portfolio manager may be willing to wade into the chop of the market to harvest the opportunities.

As volatile as this market is today, it doesn’t come close to the bouncy house in a tornado we went through in Oct 08-May 09 (6.4% average intraday change versus 3.0% today). Additionally, the direction of the market was pointedly up or down during ‘08/’09 (mostly down) versus the current market which is more mean-reverting. This creates an environment for Capitalizing on the Random Walk. If you look at the oscillation in the example below, you will see that while a stock increases in value, the position size increases (because the total number of shares stayed constant) but the Risk-Adjusted Return falls. The dynamic of increasing exposure when return falls is counter to sound portfolio management. Continuing the example the stock falls to $27 then rises back to $30, no trading has occurred and the resultant trading profit is $0.

 

But for fundamental investors that have a sense of long-term value, the gyrations create opportunity. See in the example below that as the price rises, the risk-adjusted return falls, and the position is reduced. The counter occurs as the stock decreases. In both examples, the beginning and ending share count is identical but “Capitalizing on the Random Walk” below creates 50bps of additional return net of commission. This is one stock out of dozens in the portfolio that have moved like this over the past two months.

Taking advantage of market volatility certainly isn’t top of the list when describing value investors but if expected return changes then the disciplined investor should react. A firm should create a disciplined method to highlight disparities between position size and risk-adjusted return. This is critical to Capitalizing on the Random Walk.

Here are a few quotes that lend credence to the strategy:

“When the facts change, I change my mind. What do you do, sir?” – John Maynard Keynes

“Our trading models tend to buy stocks that are recently out of favor and sell those recently in favor. Thus, to some extent, our actions have the effect of dampening extreme moves in either direction, and,  as a result,  reducing volatility in those stocks.” – James Simons, Renaissance Technologies (testimony to Congress 11/13/08)

“We as a firm are always going to buy too soon and sell too soon.  And I’m very at peace with that.” – Seth Klarman, Baupost Group

“When JP Morgan was asked how he had become so rich?  He replied, “I sold too early.” – JP Morgan, famous financier

“The riskiest moment is when you’re right.  That’s when you’re in the most trouble, because you tend to overstay the good decisions.” – Peter Bernstein, legendary investor

“Make a rule:  Whenever an investment doubles in price, find out who has the most negative view of it and give this devil’s advocate a full hearing.” – Jason Zweig, author of Your Money and Your Brain

Multiple’s Personality Disorder

The pervasive use of PE multiples (Price-to-Earnings) to value stocks has always been perplexing to me. What do we use Multiples for? To help us make a more informed investment decision. Well let’s put that to the test and say that I’m evaluating Google. I determine that the PE multiple is 20x Earnings Per Share (EPS). What does that really tell me? It tells me that if Google’s EPS remains flat in the future, I will double my money in 20 years. Sure, that’s informative, but wouldn’t a better perspective be to say that Google has an earnings yield of 5%? I know it is just the reciprocal (1 / 20) but it seems so much more informative. Just like 60 miles per hour is more informative than 0.02 hours per mile.

If I were running a fund, I would require my analyst to speak in terms of yield instead of multiples. When you tell me that Google is trading at 20x and Citigroup is trading at 10x, I understand that Citi is cheaper on a pure multiple basis. But it seems much more informative to know that Google is yielding 5% while Citigroup is yielding 10%. This makes the appropriate asset class comparison more obvious. I can get a money market yielding 1%, a treasury yielding 2.5%, a muni yielding 4% or Google yielding 5%. This seems like a more proper framing of the equation.

In addition, a small change in low multiple stocks can have a large impact in yield but have the opposite impact on higher multiple stocks. In the chart below, a multiple expansion from 6.5x to 10x lowers the yield from 15% to 10%. Clearly an investor would prefer to pay 6.5x instead of 10x, but understanding the yield has decreased to 10% makes decision making more exact. For a more profound reason to use Yield, see the top end of the scale (Assets #1-#5). A large multiple shift from 50x to 75x barely nudges the earnings yield.

A savvy investor will quickly point out that all of these arguments are flawed because we’re not including growth. I agree. I may be willing to buy stock trading at 75x if it’s growing 75% a year. The problem is that both multiples and yields are point in time snapshots. The PE-to-Growth (PEG) multiple is an attempt to account for growth, but it doesn’t do a great job (see the chart below). If we divide PE by growth, we get a series of 1.0x PEG assets. I would argue that their identical PEG does not equal identical investments. Assuming you would rather have a dollar today than tomorrow, you would prefer Asset #13 with a 100% yield and 1% growth more than Asset #1 with a 1% yield and 100% growth, but the PEG doesn’t differentiate between the two. A better method is to use a Forward Yield (Current Yield * Growth) which gives an advantage to current dollars versus future dollars.

The idea of favoring current dollars (higher yield) rings empirically true when the analysis is stretched beyond one year to look at the cumulative yield over 5 and 10 years. However, growth starts to catch up with yield quickly in the 10 year analysis. Asset #1 had the lowest Forward Yield above (2%), but after 5 years, its Forward Yield (31%) is better than Asset #2 (27%) and #3 (26%). After 10 years, Asset #1 (1023%) is better than all assets except Asset #13 (1046%). Of course, this assumes that Asset #1 can actually grow earnings by 100% a year for 10 years, but the conundrum is still apparent. How do I use Multiple or Yield to measure the investment qualities of an asset?

The answer is that you cannot use point in time valuations like Multiple or Yield to correctly assess an assets value. They are good heuristics when doing a superficial initial analysis, but fall short when compared to a discounted cash flow analysis (DCF). A DCF allows for varying degrees of growth, expenses, and time value. All of which are necessary to properly characterize the investment value of an asset. So in the pecking order of valuation methods, the Multiple gets bottom billing but, for some reason, is still the most used metric in the industry. Going forward, remember this simple equation: DCF > Yield > Multiple. It’ll help prevent you from Multiple’s Personality Disorder.

SuperFreakonomics on the Macro Economy

“Freakonomics” is a New York Times best-seller written by Steven Levitt, a professor of Economics at Chicago, and Stephen Dubner, New York Times writer, that discusses how our common assumptions about what are true are many times wrong. The book was a smash hit and was followed up by “SuperFreakonomics.” In “SuperFreakonimics”, Levitt, an economist, explains why they do not discuss macroeconomics in the book:

“Mainly because the macroeconomy and its multitude of complex, moving parts is simply not our domain. After recent events, one might wonder if the macroeconomy is the domain of any economist. Most economists the public encounters are presented as oracles who can tell you, with alluring certainty, where the stock market or inflation or interest rates are heading. But as we’ve seen lately, such predictions are generally worthless. Economists have a hard enough time explaining the past, much less predicting the future. (They are still arguing over whether Franklin Delano Roosevelt’s policy moves quelled the Great Depression or exacerbated it!) They are not alone, of course. It seems to be part of the human condition to believe in our own predictive abilities-and, just as well, to quickly forget how bad our predictions turned out to be.”

This is a good reminder for investors to focus on their core competencies. As a stock picker, macro forecasting is probably not a productive use of energy. It seems more manageable to properly gauge the prospects of an individual company and not those of the overall economy. As Bill Ackman of Pershing Square says:

"We spend little time trying to outguess market prognosticators about the short-term future of the markets or the economy for the purpose of deciding whether or not to invest.  Since we believe that short-term market and economic prognostication is largely a fool's errand, we invest according to a strategy that makes the need to rely on short-term market or economic assessments largely irrelevant."

Of course the macroeconomy is critical to the success of any individual company. It’s just that the market and economic direction are multi-variable equations with thousands of inputs.  You can find two Nobel Laureate economists with well-defended theses for divergent directions of the US economy.  If they cannot figure it out, why should you try?  Mental capacity is a precious commodity and should be directed to what is knowable. This does not mean we ignore where we currently stand economically. Just be mindful to redirect your energy if you slip towards macro forecasting.