Coyle, The Culture Code

Daniel Coyle, author of the bestselling The Talent Code, has, in my opinion, topped that book with The Culture Code: The Secrets of Highly Successful Groups (Bantam Books, 2017). He explores three skills that he believes are critical to group success. They might seem a bit vapid at first, but Coyle develops and illustrates them convincingly. First, build safety: “signals of connection generate bonds of belonging and identity.” Second, share vulnerability: “habits of mutual risk drive trusting cooperation.” And third, establish purpose: “narratives create shared goals and values.”

As one of many examples of building safety, Coyle describes an experiment consisting of two scenarios and a question. First, you’re standing in the rain at a train station. A stranger approaches and politely asks, “Can I borrow your cellphone?” Second, in the same setting, the stranger politely says, “I’m so sorry about the rain. Can I borrow your cellphone?” To which stranger are you more likely to hand over your cellphone? Staggeringly, the second scenario caused the response rate to jump 422 percent.

When it comes to the efficacy of sharing vulnerability, Coyle recalls Steve Jobs’s penchant for starting conversations with “Here’s a dopey idea.” (And some of his ideas really were dopey.) And then there was the MIT team that won the $40,000 DARPA red balloon challenge, which consisted of locating ten large red balloons deployed at secret locations throughout the United States. The team found out about the challenge only four days before launch, so they had no time to craft an organized approach. Instead, they built a website that invited people to join the team and have all their friends sign up as well. And they promised to give $2000 per balloon to the first person to send the correct coordinates, $1000 to the person who invited them, $500 to whoever invited the inviter, etc. As Coyle writes, “This wasn’t a well-equipped team; it was closer to a hastily scrawled plea shoved into a bottle and lobbed into the ocean of the Internet: ‘If you find this, please help!’” Thousands of teams competed in the DARPA challenge, which organizers figured would take up to a week to complete. But in less than eight hours, the MIT team had found all ten balloons, with the help of 4,665 people. They had created “a fast, deep wave of motivated teamwork and cooperation.”

As for the third skill, establishing purpose, Coyle argues that “creating engagement around a clear, simple set of priorities can function as a lighthouse, orienting behavior and providing a path toward a goal.” Coyle recounts the Tylenol disaster, which Johnson & Johnson handled brilliantly by hewing to the company credo. Or, for me a more local example is the men’s hockey team at Quinnipiac University in Hamden, CT. The coach built a culture around a behavior he calls “Forty for Forty,” which refers to back-checking (“rushing back to the defensive end in response to the other team’s attack”). Back-checking happens around forty times a game, and the coach’s goal is that his players go all-out on each one. “Back-checking is exhausting, requires keen attentiveness, and—here’s the key—rarely makes a difference in the game.” But the perhaps one in forty times it makes a difference, it can change a game.

If you’re on a team or lead a team, this book may just change your game too.

Muller, The Tyranny of Metrics

We’re fixated on metrics, in part because we have come to embrace two dictums: “If you cannot measure it, you cannot improve it” (Lord Kelvin) and “What gets measured gets done” (Tom Peters).

Jerry Z. Muller, in The Tyranny of Metrics (Princeton University Press, 2018), sets out to show “the unintended negative consequences of trying to substitute standardized measures of performance for personal judgment based on experience. The problem is not measurement, but excessive measurement and inappropriate measurement—not metrics, but metric fixation.”

Metric dysfunction manifests itself in multiple ways. Problems that fall under the general heading of distortion of information include: (1) measuring the most easily measurable, (2) measuring the simple when the desired outcome is complex, (3) measuring inputs rather than outcomes, and (4) degrading information quality through standardization. Then there are the inevitable attempts to game the metrics. This gaming can manifest itself in (1) creaming, (2) improving numbers by lowering standards, (3) improving numbers through omission or distortion of data, and, when all else fails, (4) cheating.

We are deluged with quantitative data that are viewed as the answer; we just have to come up with the right question. But these data rarely give the full answer to a meaningful question. For instance, back when spreadsheets were becoming “a worldview—reality by the numbers,” Seth Klarman warned (in 1991) that “spreadsheets created the illusion of depth of analysis.” By now, at least in certain quarters, that illusion has been transformed into accepted dogma.

In a chapter titled “The Mismeasure of All Things?” Muller analyzes case studies from the fields of education, medicine, policing, the military, business and finance (especially pay-for-performance schemes and short-termism), and philanthropy and foreign aid.

The Tyranny of Metrics may not break a lot of new ground, but it shows how metric fixation permeates, and often creates hazards for, so many aspects of our society. And it does so in a thoroughly convincing way. As Muller concludes, “Ultimately, the issue is not one of metrics versus judgment, but metrics as informing judgment, which includes knowing how much weight to give to metrics, recognizing their characteristic distortions, and appreciating what can’t be measured.”

Marston, Type R

Mother and daughter Stephanie and Ama Marston have teamed up to write Type R: Transformative Resilience for Thriving in a Turbulent World (PublicAffairs/Hachette, 2018). The authors specifically reject the model of “bouncing back” from misfortune, arguing that “there’s no going back to who or where we were before challenging times.” Instead, they focus on how to grow and create opportunity from adversity, to “leverage change and hardship into opportunity as individuals and carry that progress into the world as a contribution to the collective.”

The authors share stories of people who have demonstrated transformative resilience. They also analyze the six common characteristics and skills that allow for transformative resilience: adaptability, healthy relationship to control, continual learning, purpose, leveraging support, and active engagement. Most of these characteristics are pretty straightforward. I’ll look at only one, which often trips people up: a healthy relationship to control.

The Marstons begin by saying that “believing that we control the outcomes of our lives and our successes isn’t only empowering but also a starting point for creating Transformative Resilience. Yet, focusing too intensely on an internal locus of control and our ability to control has significant downsides.” If we believe that we alone are responsible for what happens to us, this belief can be “a huge source of stress.” And so, Type Rs learn “to assess what’s within our sphere of influence and what’s not. We realize that strength isn’t always determined by triumph over the outside world but sometimes by changing our inner world. As a result, we can respond appropriately, investing energy in areas where we have influence, acknowledging and shifting focus away from areas where we don’t, and redirecting our energy into cultivating Transformative Resilience.”

The authors apply their model first to individuals, then to organizations and leaders, and finally to families.

Lo, Adaptive Markets

Andrew W. Lo first proposed the adaptive markets hypothesis (AMH) in 2004 as an alternative to the efficient markets hypothesis (EMH). Four years later, in Hedge Funds: An Analytic Perspective, he reiterated his hypothesis. Few people did cartwheels over it. This past year he wrote a more popular, though nearly 500-page, book to advance his view, Adaptive Markets: Financial Evolution at the Speed of Thought (Princeton University Press).

The first third of the book—dare I say the best third of the book?—is a stroll through, and critique of, competing hypotheses and an introduction to evolution, with the mantra “It’s the environment, stupid!” emerging as a dominant motif and the notion of evolution at the speed of thought becoming an organizing principle. (“We can use our brains to test our ideas in mental models, and to reshape them if they’re found lacking. This is still a form of evolution, but it’s evolution at the speed of thought.”)

As Lo repeats more than once, it takes a theory to beat a theory. His hypothesis is, he suggests, “the new contender. But these are still early days for the challenger—the incumbent has had a five-decade head start—and a great deal more research is needed before these ideas become as immediately useful as the existing models of quantitative finance.” This is indeed the problem for the AMH. It’s just not immediately obvious how to use it in a way that is neither trivial (e.g., market regimes change) nor supportive of far too many alternatives.

According to the AMH, “market behavior adapts to a given financial environment.” The EMH, in Lo’s view, describes an abstraction, an idealized market. “An efficient market is simply the steady-state limit of a market in an unchanging financial environment.”

Lo offers a new investment paradigm to replace or modify the five principles of the traditional investment paradigm.

1. The risk/reward trade-off. Although during normal market conditions there’s a positive association between risk and reward, “when the population of investors is dominated by individuals facing extreme financial threats, they can act in concert and irrationally, in which case risk will be punished.”

2. Alpha, beta, and the CAPM. “Knowing the environment and population dynamics of market participants may be more important than any single factor model.”

3. Portfolio optimization and passive investing. “Portfolio optimization tools are only useful if the assumptions of stationarity and rationality are good approximations to reality.” As for passive investing, “risk management should be a higher priority.”

4. Asset allocation. “The boundaries between asset classes are becoming blurred.”

5. Stocks for the long run. “Over more realistic investment horizons, … investors need to be more proactive about managing their risk.”

Lo is a good enough scientist to realize that “between theory, data, and experiment, the Adaptive Markets Hypothesis will survive, perhaps be replaced with an even more compelling theory in the future, or fall short and be forgotten.” I hope it’s not the last alternative because, even though I have my doubts about its efficacy, the hypothesis has some very attractive features.

Cochrane & Moskowitz, eds. The Fama Portfolio

I’m going to start 2018 on a high note, with The Fama Portfolio: Selected Papers of Eugene F. Fama (University of Chicago Press, 2017), edited by John H. Cochrane and Tobias J. Moskowitz. The subtitle is a tad misleading because, although this volume, over 800 pages in length, contains 20 papers that Fama either authored or co-authored, it also includes papers and commentaries by colleagues and former students.

Eugene Fama is best known, of course, for the efficient market hypothesis—that, as he succinctly described its strong version, “security prices fully reflect all available information.” But since a precondition for this version of the hypothesis is that there are no information and trading costs, it is, he readily admitted in his second paper on the EMH, “surely false. Its advantage, however, is that it is a clean benchmark that allows me to sidestep the messy problem of deciding what are reasonable information and trading costs. I can focus instead on the more interesting task of laying out the evidence on the adjustment of prices to various kinds of information. Each reader is then free to judge the scenarios where market efficiency is a good approximation (that is, deviations from the extreme version of the efficiency hypothesis are within information and trading costs) and those where some other model is a better simplifying view of the world.”

I quote this passage because I believe it illustrates Fama’s dedication to empiricism. He was no “so much the worse for the facts” theorist. As Kenneth French wrote in “Things I’ve Learned from Gene Fama,” “Gene is arguably the best empiricist in finance.”

In addition to his papers on efficient markets, which includes one he coauthored with French on “Luck versus Skill in the Cross-Section of Mutual Fund Returns,” this volume contains papers on risk and return, return forecasts and time-varying risk premiums, and corporate finance and banking. Especially notable are the Fama and French papers on “Common Risk Factors in the Returns on Stocks and Bonds” and “Multifactor Explanations of Asset Pricing Anomalies.”

As long as the reader has a basic grasp of statistical principles, Fama’s papers are eminently comprehensible. And, despite all the criticism of the EMH, they should still be studied with care, both as case studies in how to do first-rate financial research and for the insights they provide into financial markets. I laud the editors for gathering such important work into a single volume. It’s a book every student of finance and financial professional should have in his library.