Decision Economics: does more data equal better investment decisions?

As investors, we’re expected to follow virtually everything that may impact our—or our clients’—portfolios, from world events to the market’s daily ups and downs. Staying on top of so much information is no easy task, and the amount of time it can consume can even rival the time our kids spend on social media. 


The obvious question is whether all of this data improves our ability to make good investment decisions or ultimately leads us to drown in the noise. In the second of a series of articles on how human behavior can affect investment decisions, we look at the benefits of managing our focus more effectively, including the data we choose to monitor most closely.

Herbert Simon, a noted cognitive psychologist specializing in decision-making and a Nobel Prize winner in Economic Sciences in 1978, recognized the obvious: Our challenge isn’t a lack of information but a lack of attention. Simon coined a term called “bounded rationality” to describe the challenge of making optimal decisions given the vast quantities of information available to us, the time constraints we face, and our brain’s ability to process it all. He posited that these challenges would lead us to a decision process called “satisficing,” where we would attempt to find optimal answers, but would quickly give up the search and default to making decisions that were “good enough” under the circumstances. Often these “good enough” decisions would be based on our preferences or past experiences rather than probabilities, which are so critical in investment decision-making.

“What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
Herbert Simon

Worse still, numerous studies have shown that as the amount of data that we consume increases, so too can our confidence—but not necessarily our accuracy. In one famous study by Paul Slovic, a clinical psychologist in Toronto, he interviewed horse race handicappers on the most important criteria to forecast race results. The handicappers ranked the data in order of importance (40 pieces of information in all) and were then asked to make predictions. In round one, the 5 most important pieces of data were used to forecast a total of 10 races. In round two, 10 pieces of data were given, followed by rounds three and four with 20 and 40 pieces of data. As you might expect, confidence continued to rise as more information was consumed, but accuracy quickly flatlined and gradually declined.¹ The implications for investing should be obvious, especially given the inherent uncertainty of the investment domain.


The signals dashboard

One technique increasingly adopted by institutional managers is the use of a “dashboard” or market indicators. Much like the dashboard in your car, the goal is to monitor the most critical market gauges, enabling you to keep your eyes on the road ahead. The dashboard can play a central role in the investment committee meeting by centering the deliberations on data with empirical value to impact markets or the economy, thereby avoiding the distractions of data subject to short-term emotion or revision. The test for whether data has signal value is:

  • Is there either a behavioral or economic reason why it should have signal value?
  • Can I reliably link it to the performance of an asset class?

One example for equities would be high-yield credit spreads versus the S&P 500. High yield sits just above equities in the capital structure and as credit spreads widen, equities historically have acted negatively and the reverse has been true when credit spreads are narrowing – a reflection of improving credit conditions.

Note the crossover points when spreads are widening or falling through the moving averages and how equities behave

ICE BofA High Yield Index option-adjusted spread vs. S&P 500 Index

Source: FactSet. Time period is March 31, 2000 through March 31, 2021. Vertical lines represent dates where crossover points were confirmed by a minimum 25 basis- point move in same direction for two consecutive months. Past performance is not indicative of future results.


It should be emphasized that the goal of a market dashboard isn’t to engage in day trading, but rather to help make less frequent, more strategic decisions as part of a definable, defendable, and repeatable process. A dashboard can also be an effective tool for educating clients on the data that’s most important to managing their wealth, helping them keep their emotions in check, and further differentiating your approach from the competition.

The investment consulting group at John Hancock is here to help and offers a range of services,  from formal model reviews to manager selection to investment decision process. For more information on building your own signals dashboard, contact us today.

1 “Behavioral Problems of Adhering to a Decision Policy,” Paul Slovic, May 1, 1973.