Meta-Strategy in Uncertain Environments (Part II: Markets)
A recent survey of 500 business executives at companies with revenue of $1 billion or more by the Economic Intelligence Unit found that roughly 90% of corporate strategic plans had failed to meet their own objectives. Active managers experience a similar failure rate in the growth predictions they make in their discounted cash flow models.
Yet corporate executives and active managers cannot resist the temptation to plan. And sometimes, it seems, the smarter the person the greater the temptation to react to uncertain environments with ever more complex plans and frameworks. The tendency of smart people to become seduced into thinking their intellects can overcome the uncertainty of the future is one of the most recurring but unsung tragic poems of human history.
My opinion that business and financial thinking fall prey to the same Soviet-Harvard Delusion as the COIN manual was strengthened by my time at Stanford’s Graduate School of Business. There I noted a doctrine of certainty being taught by the faculty in most all of the introductory finance courses. My skepticism of this pedagogy was heightened after I met Verdad’s founder and my classmate at the time, Dan Rasmussen, who introduced me the most recent literature on excess volatility and risk in financial markets (not assigned by the business school).
The certainty of my professors clashed with the warfighting philosophy I learned at Quantico: “It is precisely those actions that seem improbable that often have the greatest impact on the outcome.” A freak weather pattern, an unsolicited informant, or the sudden death of a high-profile player can impact the course of a campaign more substantially than elements we would think to include on a list of risks and tailwinds. Likewise, a sharp turn in commodity prices, an unexpected new market opening up, or a big new customer will often make or break the fortunes of a company but elude even the most prescient analyst’s model.
I also learned at Quantico that complex linear planning fails in warfare because the profession involves “the shock of two hostile bodies in collision, not the action of a living power upon an inanimate mass,” as Clausewitz reminds us. In the military-industrial exuberance of the post–Cold War decades, we invested heavily in exotic platforms such as drones, cyber capabilities, and billion-dollar strike fighters. Our low-tech but moderately street-savvy opponents in this millennium decided to fight us precisely where and how these assets were near useless. With few exceptions, the most useful equipment for this environment came from the Vietnam era and the most enduring lessons from the time of the Spartans.
Financial markets, made up of people competing for an edge, are precisely the type of environment designed to bedevil static planning. The financial environment is one where valuation multiples persistently mean revert, where income statement growth is not persistent or predictable, where GDP growth does not correlate with equity returns, where market share and moats do not lead to competitive advantage or price return.
So what are we to do in such an environment where outcomes are determined not so much by the very little we can foresee but by what might unexpectedly happen relative to the expectations embedded in the price at which the security is bought? How would we affirmatively strategize and operate differently as investors if all of our most cherished and marketed crystal balls for forecasting price returns are shattered? How should we operate amidst the chaos without operating chaotically?
In Afghanistan, I found that the most consequential assets on our side were the most robust and persistent throughout the history of warfare. An asymmetric but intelligent adversary had refused to engage us on any terms but those where war devolved to a competition of wills, where discipline, resolve, adaptability, and habituated combat-arms tactics dictated the victor, not drones or robot pack mules. Our own persistent behavioral biases were our worst enemy.
In the financial environment, we might learn from long-term history rather than the exuberance of strategic futurology. We might turn to the most persistent and proven foundation of the buy low, sell high equation: buy low. We might devise risk control rules based on long-term evidence that helps us combat our most persistent behavioral biases. Facing uncertainty in individual security forecasting, we might, as the Quantico doctrine suggests, attempt humbly “to determine possibilities and probabilities.”
By popular analogy, we might think more like the evidence-based, analytical baseball manager of the Oakland A’s, Billy Beane from Michael Lewis’s book, Moneyball. The Moneyball manager at least has a plausible hypothesis about how to thrive in either a relatively uncertain or certain world. Meanwhile the manager marketing the tools of certainty for a perceived-certain future has a much higher intellectual burden of proof to inspire confidence of probable price return, and his strategy and tools for an uncertain world are inappropriate at best.
The well-trained student of today’s academy has been assessed by the perfection of his linear algebra and the well-trained Wall Street analyst has been praised for the precision of his Microsoft Excel forecasts. The philosophy and training of today’s academia may be precisely the appropriate one for those entering environments predicated on proven predictability.
We seem to be seduced en masse by planning complexity under assumptions of certainty time and time again in various environments of human endeavor that empirically seem more closely to resemble chaos than Cartesian coordinates. Perhaps in warfare, we want to believe the promise that we can wage a kinder, gentler form of it with innovative new strategic planning doctrines such as the COIN manual. Perhaps we want to believe that with more sophisticated planning we can tame the chaos.
Perhaps in socio-economic planning we want to believe that the evolution of history is deterministic and inevitably progressive toward some evolutionary synthesis and preferable utopian higher plane. It may be more appealing to craft our understanding of history around assumptions akin to “structural power dynamics define all history and socioeconomic relations,” as a neo-Marxist might, or the idea that democracy is the “End of History,” as Francis Fukuyama argued in the 90s.
Perhaps in finance as well, we have been seduced en masse by planning complexity under assumptions of certainty. But the consequences of such elaborate linear planning under the assumption of certainty in complex and dynamic environments have been among the most catastrophic in human history. Such mass delusions have occurred in other fields of human endeavor. And in finance, the track record of conventional stock pickers today suggests the theories aren’t working in reality.