Bringing an End to Errors: Part 1

  • Thursday, August 31, 2017

This is the 1st part of a 6 part series on how cutting-edge text analysis technology is helping investors mitigate the detrimental effects cognitive biases can have on their decision-making.

One year ago, the Brexit vote had just passed, and all signs pointed to a BOE rate cut on July 14, 2016. The economy was in turmoil, experts were calling for easing, and the market was pricing in a 75% chance of a cut.

One problem: the BOE held.

For many, BOE Governor Mark Carney’s July 5 speech was confirmation of the cut to come. Analysts honed in on words like, “vulnerable,” “slowed,” and “uncertainty,” pushing their cut forecast from probable to predetermined. “Governor Mark Carney sent a clear signal two weeks ago that stimulus was on the way,” wrote William Schomberg of Reuters.

Not everyone interpreted Carney’s tone this way. In stark contrast to consensus, one assessment based on algorithmic analysis contended that Carney “touted stability” in his speech—and that the BOE would hold rates at its meeting. In the aftermath of the decision to hold, many could only scratch their heads. How could so many brilliant investors and analysts get it so wrong? And what sort of tech was behind right call? The short answers:

1. Cognitive bias

2. Textual analysis  

Cognitive Bias and Finance

Humans are rational animals. Whether from Aristotle or your freshman macroeconomics class, we’ve all heard this schtick somewhere along the line, and, for many of us, the schtick stuck. At first, the assertion seems fully reasonable. From pyramids to particle accelerators, testaments to human intelligence abound. But as impressive as our intellect can be, the “rational animal” angle just doesn’t paint the full picture of what’s going in our heads.

For every outstanding feat of science, one can always find a comparably outstanding feat of miscalculation.

This, in part, is due to the fact that our brains (despite what we might like to think) did not evolve to become perfect data-crunching, logic-loving machines. Instead, selection favored cooperation over calculation:

Humans’ biggest advantage over other species is our ability to cooperate. Cooperation is difficult to establish and almost as difficult to sustain. For any individual, freeloading is always the best course of action. Reason developed not to enable us to solve abstract, logical problems or even to help us draw conclusions from unfamiliar data; rather, it developed to resolve the problems posed by living in collaborative groups.

Because of this—and many other selection pressures—the human mind contains a veritable storehouse of cognitive biases that it constantly calls upon during the decision-making process.

In many situations, these biases can help us. Biases focus our line of thought, often directing us towards a safe bet and always cutting down the time it takes to come to a conclusion. Biases can also help us make up for our ignorance, encouraging us to rely on the opinions others when information is scarce and action is needed. While beneficial or benign the majority of the time, there are more than a few spaces of human activity that cannot abide the shortcuts biases offer. While scientific research is probably the first example that comes to mind, finance is equally (if not more) unforgiving of the mistakes our biases can cause.

Just ask those who traded on the assumption of a BOE cut.

We’ll dig into why the market missed the call and technology didn’t in part 2 of this series.

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