Why Sustainable Active Investing Fails

October 09, 2015

The logic of passive investing is undeniable. For many, the debate between passive and active ended long ago, with passive the unquestioned winner.

We recognize this reality. This article is not meant to convert a passive investor into an active investor. However, we do explore why we believe some active investing approaches can beat passive strategies over a reasonably long time horizon.

Clearly, outperformance can’t work forever and active management is certainly a zero-sum game (negative sum after costs), so you might reasonably ask: Why bother to get involved in the debate?

Our framework is meant to help investors decipher the so-called factor zoo to determine if an active strategy may be sustainable or is likely a pipe dream. More broadly, this piece can be thought of as merely an introduction to the argument for the possibility that active management can work. For an in-depth look at our sustainable active investing framework, you can view the extended version of this piece here.

Measuring Success

How do we determine if an active investor will be successful? We believe that having superior stock-picking skills, amassing an army of Ph.D.s to crunch data or simply being smart are not, by themselves, sufficient to ensure active investing success. We need something more.

We propose that to achieve sustainable success as an active investor, analytical skills are less important than: 1) an understanding of human psychology; and 2) an appreciation of market incentives (behavioral finance), which, when combined, give rise to the possibility of beating a passive approach. We start our discussion with one of the original minds in the “emerging” field of behavioral finance—John Maynard Keynes.

John Maynard Keynes, a shrewd observer of financial markets and a successful investor, highlights the paradox that behavioral finance represents. At one point, Keynes was nearly wiped out while speculating on leveraged currencies (despite being a highly successful investor). This downfall led him to share one of the greatest investing mantras of all time:

“Markets can remain irrational longer than you can remain solvent.”

attributed to John Maynard Keynes

Keynes’ quip highlights two key elements of real-world markets that the efficient market hypothesis doesn’t consider: Investors can be irrational, and arbitrage is risky.

In academic parlance, “investors can be irrational” boils down to the recognition of a role for psychology in markets. “Arbitrage is risky” boils down to what academics call “limits to arbitrage,” or market frictions. These two elements—psychology and market frictions—are the building blocks for behavioral finance (depicted in Figure 1, below).

Figure 1: The 2 Pillars Of Behavioral Finance

Limits To Arbitrage

The efficient market hypothesis predicts that prices reflect fundamental value. Why? People are greedy, and any mispricings are immediately corrected by those smart, savvy investors who can make a quick profit.

But in today’s world of instant information, supercomputers and interconnected markets, true arbitrage—profits earned with zero risk after all possible costs—rarely, if ever, exists. Most arbitrage has limits in the form of some cost or risk.

Let’s look at a simple example.

Arbitraging oranges:

Oranges in Florida cost $1 each.

  • Oranges in California cost $2 each.
  • The fundamental value of an orange is $1 (assumption for the example).
  • The efficient market hypothesis suggests arbitrageurs will buy in Florida and sell in California until California oranges cost $1.

But what if it costs $1 to ship oranges from Florida to California? Prices are decidedly not correct—the fundamental value of an orange is $1. But there is no free lunch since the frictional costs (of shipping an orange) are a limit to arbitrage. In short, the smart, savvy arbitrageurs are prevented from exploiting the opportunity (in this case, due to frictional costs).


News flash: Humans beings are not rational 100 percent of the time. To anyone who has been married, driven without wearing a seat belt, or hit the snooze button on their alarm clock, this should be pretty clear. And the literature from top psychologists is overwhelming for remaining naysayers. Daniel Kahneman, the Nobel-prize winning psychologist, and author of the New York Times best-seller, Thinking, Fast and Slow, tells a story of two modes of thinking: System 1 and System 2.

System 1 is the “think fast, survive in the jungle” portion of the human brain. When you start to run away from a poisonous snake (even if later on, it turns out to be a stick), you are relying on your trusty System 1.

System 2 is the analytic and calculating portion of the brain that is slower, but 100 percent rational. When you are comparing the cost benefits of refinancing your mortgage, you are likely using System 2. Importantly, we do not always use System 2, even when we should; for instance, when making investment decisions.

Now, let’s combine our wacky investors (System 1 types) with the limits of arbitrage that we discussed above (it is costly in some way for smart people to take advantage of wacky investors). Combining price-influencing bad behaviors with costly arbitrage restrictions creates an interesting field of study that academics refer to as “behavioral finance.”

And while this working definition of behavioral finance may seem simple, the debate surrounding behavioral finance is far from settled. In one corner, the efficient market clergy claims that behavioral finance is heresy, reserved for those economists who have lost their way from the “truth.” They point to the evidence that active managers can’t beat the market and incorrectly conclude that prices are always efficient as a result.

In the other corner, practitioners who leverage “behavioral bias” suggest that they have an edge because they exploit investors who are acting irrationally. Yet practitioners who make this claim often have terrible performance.

What gives?

Like Poker: Pick The Right Table

Behavioral finance outlines a framework for being a successful active investor:

  1. Identify market situations where behavioral bias is driving prices from fundamentals (e.g., identify market opportunity)
  2. Identify the actions/incentives of the smartest market participants (e.g., identify market competition and what they are doing or not doing)
  3. Find situations where mispricing is high and competition is low

In the context of poker, a similar strategy is critical for success:

  1. Know the fish at a given table (opportunity is high)
  2. Know the sharks at a given table (competition is low)
  3. Find a table with a lot of fish and few sharks

In Figure 2 below, the graphic outlines the questions we must ask as an active investor in the marketplace.

  1. Who is the worst poker player at the table?
  2. Who is the best poker player at the table?

To be successful over the long haul, an active investor needs to be good at identifying market opportunities created by poor investors, but also skilled at identifying situations where savvy market participants are unable or unwilling to act.

Figure 2: Identifying Opportunity In The Market

Understanding The Best Poker Players

In our orange arbitrage example above, transport costs impeded the arbitrage opportunity. In the stock market, there are similar direct cost frictions such as short selling, commissions and so forth. However, these costs are unimportant compared with perhaps the biggest market friction imposed on most of the smart poker players in the stock market: agency costs created by short-horizon performance expectations.

Consider the pressures produced by “tracking error,” or the tendency of returns to deviate from a benchmark. Say you are the smartest investor in the world and your job is to invest the pensions of 100,000 firefighters. You have a choice of investment strategies. You can invest in either A or B (summarized in Table 1):

  • Strategy A: A 250-stock portfolio that will beat the market by 1 percent per year over 25 years. This strategy will never underperform the index by more than 1 percent in a given year;


  • Strategy B: A 50-stock portfolio strategy that will outperform the market by 5 percent per year over the next 25 years. This strategy also guarantees a five-year period of 5 percent per year underperformance.

Table 1: Summary Of Investment Options

Strategy Alpha Career Risk
A Low Low
B Extremely High Extremely High

Which strategy do you choose? If you are a professional money manager, the choice is obvious: choose A and avoid getting fired. But why choose A? It’s a bad long-term strategy for the firefighters relative to strategy B! Note that for the manager in this case, career risk is a more important consideration than alpha generation—the reverse of the priorities for the investor who owns the capital.

What is going on? Well, the incentives of an investment manager are complex. Fund managers are not the owners of the capital, but work on behalf of someone who owns the capital. Financial mercenaries, if you will.

These managers sometimes make decisions that ensure they maintain a job, but not necessarily maximize risk-adjusted returns for their investors. For these managers, relative performance is everything and tracking error is dangerous. In the example above, the tracking error on strategy B is just too painful to digest. Those firefighters are going to start screaming bloody murder during the five years of underperformance, and the manager won’t be around long enough to see the rebound when it occurs after year five.

But if the manager follows strategy A, he can avoid career risk and the fireman’s pension will not endure the stress of a prolonged downturn. While performance and returns for the firemen will suffer, the manager’s job will be safe.

Of course, the problem outlined above is not new. The dynamics of this problem are explored in an esoteric 1997 Journal of Finance paper by Andrei Shleifer and Robert Vishny, appropriately called, “The Limits of Arbitrage.” Moreover, recent research by Jason Hsu and Vivek Viswanathan highlights that active strategies are prone to investor fatigue, which leads to outflows when short-term relative performance is poor, and inflows when short-term relative performance is strong.

Why Long-Term Alpha Is Avoided

Bottom line: Pro investors avoid long-term alpha opportunities when their investors are focused on short-term relative performance.

And can you blame them? Asset managers are compared with a benchmark every month, quarter, year or even three years, and short-run relative performance has serious consequences. Whether the asset manager is proactively protecting his/her job, or the client is actively driving the conversation around near-sighted metrics, the end result is the same—few pros want to engage in active investing, and prefer a closet-indexing approach, since it is safer from a career perspective.


We’ve outlined a few elements of the marketplace. First, prices aren’t always efficient, and second, exploiting inefficient prices is difficult, because professional investors rationally prefer employment versus unemployment. We encapsulate these simple ideas in Figure 3.

Figure 3: The Long-Term Performance Equation

The long-term performance equation has two core elements that help us identify a true “alpha” opportunity. First, sustainable alpha. By sustainable alpha, we mean a process that systematically exploits mispricings caused by behavioral bias in the marketplace (i.e., find the worst poker players).

Next, sustainable clients—which are important, because many of the best poker players in the game (think large asset managers with a majority of the capital)—are unable to pursue long-term opportunities because their client base is too focused on the short term (i.e., understand the best poker players). Without sustainable clients, there is no opportunity to pursue sustainable long-term performance.

Based on the equation, if one could identify processes with an edge (e.g., sustainable alpha) that require long-term discipline to exploit (e.g., sustainable clients), it is likely that this process will serve as a promising long-term strategy.

Of course, identifying a reasonable process is not too challenging, but identifying sustainable clients with long-term focus is almost impossible.

Hence, sustainable active investing is almost impossible.

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