Question

Thinking back over what you have read in the newspapers or seen on television, what are some very bad investment decisions made by managers? Why were these mistakes made?

Answer 1

the financial industry uses technology to deal with enormous amounts of data and manage trade execution and strategy on an ongoing basis. But computers are also now taking an active role in the decision process behind those trades. With advances in artificial intelligence, some computers are now teaching humans how to improve the investment decision process.

Humans should take note of this, since one area where humans can close the gap with the machines is in the decision process, where a host of hidden cognitive biases and heuristics plague even the most experienced humans, robbing them of optimal investment performance. Overcoming this negative alpha may offer managers a level of performance improvement that rivals what they might squeeze out of their strategies themselves.

The time is thus at hand for investment managers to turn at least some of their attention from the outward influences of economics, markets, news, fundamentals, and macro trends to the inward influences of the subliminal cognitive factors that impact almost every decision they make, yet which are virtually invisible to them. A number of pioneering managers who have engaged behavioral coaches or who use software to help reveal their decision biases are already seeing measurable progress.

Decision science is of course an entirely different animal from economic science. The extensive financial training required of investment managers has seldom included behavioral psychology until the last five years or so.

Nonetheless, decision science is far from a trivial matter in investment management. Studies of both individual and professional investment performance are beginning to quantify the effects of behavioral biases on investment performance. While individual investors show an even more pronounced effect, professional managers may be exhibiting up to 200-300 basis points of negative alpha from biases that are influencing their decisions. Given that most managers underperform the major indexes by less than that amount, cognitive improvements may at least be worth some exploration.

the strategy itself or the rules accompanying that strategy. It is the mechanism by which individual decisions are made when executing that strategy. Without considering the decision process, a manager can’t accurately determine whether the strategy is even working properly.

A strategic rule might stipulate, for example, that an inverted yield curve leads to a more defensive allocation. That still leaves a number of implementation decisions at the manager’s discretion. How many times does a strategic rule specify the circumstances that warrant action by the manager, without saying specifically what the manager should do in that situation? In short, even many disciplined rules-based approaches leave some discretion to the manager at the time the rule dictates that a decision is warranted.

The decision process is the means by which one reaches a specific conclusion on which to act. One manager might have a de facto decision process for selecting a stock that involves identifying candidate stocks by industry and fundamental screens, ranking them, and then selecting the one at the top of the list. Another might arrive at a selection by a rejection process—whittling down to a final selection by eliminating stocks from the bottom up. Another might create a short list of candidates that are acceptable and then expect to make the final call from judgment. Each of these approaches is different, but at least the first two have an audit trail to analyze.

To illustrate why outcome is an improper way to determine the validity of a decision, just recall the highly publicized experiment carried out by The Wall Street Journal years ago when closing stock prices were printed in the edition. Each week the paper asked a professional investment manager for their best short-term stock pick, using different managers each time. Then they posted the paper’s stock listings on the wall and had a junior staffer throw a dart. The selections were noted and monitored. Over the course of many months, the tally went back and forth in favor of either the managers or the darts.

Chronic occurrence of poor operational decisions by midlevel managers is eroding margins and costing firms upward of 3 percent of profits, according to Gartner, Inc. As digital and other business transformations (such as merger and acquisition [M&A]) drive a greater volume and variety of operational decisions, it is vital to the organization’s bottom line that CFOs ensure those decisions are financially sound.

CFOs seeking to better support these managers should redefine the role of their finance business partners — those assigned to support decisions from business unit managers — to more specialized positions focused on individual decision types.

“Managers tell us that they have faced a significantly higher volume of financial decisions over the past three years,” said Randeep Rathindran, research vice president at Gartner. “This increased volume has exposed the lack of rigor employed by most midlevel managers in reaching material decisions that impact the bottom line.”

Gartner surveyed 469 business decision makers and 128 senior finance executives globally across various industries as part of its 2018 study. Sixty-one percent of respondents noted an increase in operational decision volume, with 57 percent indicating that these types of decisions materially impact business profitability. In summary, the volume of decisions with material business impact has grown, and those decisions are being made with a high rate of exceptions to operational decision rules put in place by finance

• The field of economics is muddled and imprecise, and there’s good reason it’s called “the dismal science.” Unlike a "real" science like physics, in economics there are no rules that one can count on to consistently produce a given outcome, as in “if a, then b.” There are only patterns that tend to repeat, and while they may be historical, logical and often-observed, they’re still only tendencies.

• In some recent memos, I’ve mentioned Marc Lipsitch, Professor of Epidemiology at Harvard’s T.H. Chan School of Public Health. In my version of hierarchy, there are (a) facts, (b) logical inferences from past experience and (c) guesses. Because of the imprecision of economics, there certainly are no facts about the economic future. Economists and investors make inferences from past patterns, but these are unreliable at best, and I think in many cases their judgments fall under the heading of "guesses."

• These days, I’m often asked questions like "Will the recovery be V-shaped, or a U, W or L?" and "Which of the crises you’ve lived through does this one most resemble?" Answering questions like those requires a historical perspective.

• Given the exceptional developments enumerated above, however, there’s little or no history that’s relevant to today. That means we don’t have past patterns to fall back on or to extrapolate from. As I’ve said, if you’ve never experienced something before, you can’t say you know how it’s going to turn out.

• While unique developments like those of today make forecasting unusually difficult, the presence of all four elements at once probably renders it impossible. In addition to the difficulty of understanding each of the four individually, we can’t be sure how they’ll interact. For example:

  • Will the massive, multi-faceted Fed/Treasury program of loans, grants, stimulus and bond buying be sufficient to offset the unparalleled damage done to the economy by the fight against Covid-19?

  • To what extent will the reopening bring back economic activity, and to what extent will that cause the spread of the disease to resume, and the renewal of lock-downs?

For investors, the future is determined by thousands of factors, such as the internal workings of economies, the participants’ psyches, exogenous events, governmental action, weather and other forms of randomness. Thus the problem is enormously multi-variate. Take the current situation with its four major components (Covid-19, the economy, oil and Fed), and consider just one: the disease. Now think about all the questions surrounding it:

Growing Decision Volume Exposes Broken Model

The analysis also revealed that most business managers responsible for making such exceptions are operating in a vacuum. Twenty-two percent don’t consider a single financial implication when making such a decision. These factors translate to a company with $5 billion in revenue sacrificing upward of 3 percent of earnings through poor decision making across the thousands of material business decisions it will face each year.

“The current model of financial business partners aligning to stakeholders lacks the level of expertise needed to provide support on the specific decision types faced by midlevel managers,” said Mr. Rathindran. “Unfortunately, 77 percent of companies we surveyed are still aligned to the stakeholder-based model.”

Redefinition, Not Reorganization

In order to plug the leakage of margin and profits associated with poor financial decisions, Mr. Rathindran outlined a new model that provides managers support tailored to each specific type of financial decision they encounter. The transformation to a decision-expert model can be phased in with as little as 20 percent of a company’s financial planning and analysis team. It requires no additional placement of finance team members with business units compared with a traditional approach.

“Focusing on changing behaviors of finance business partners is the most effective and fastest route at providing the type of support managers need to make effective financial decisions,” said Mr. Rathindran. “Finance departments can start small and see an immediate impact. When they evolve to a decision-support model these finance organizations can more than double their effectiveness in making appropriate financial decisions.