Tuesday, November 12, 2019

The problem of distraction and overload - Filter the noise and stay focused

Every investor seems to know about and discuss behavioral biases in finance. There is a cottage industry trying to find new biases and measure old ones; however, there is a core explanation for why investment mistakes are made, distraction. Investors may not make the best decisions because their attention has been misplaced. One can classify this as a behavioral bias or flaw, but it is aa broader reason for decision failure. Models and rules-based decision-making can help cure distraction problems.

Investors become distracted for any number of reasons and the results are poorer decisions. There are number of forms of distractions. There can be sensory distraction from too much stimulus or information. There can be emotional distraction when we get bad news. The mind can wander and not be focused, and the there can be distraction from following habits. Neuroscience has actually measured our tendency for distraction through MRI images. Even strong professionals can have periods of distraction. Some environments with a lot of sensory information are more prone to creating distractions.

Human error is often used as the reason for failure when the more specific reason is distraction. For example, warning lights or bells in a cockpit or car can actual create distraction through potentially refocusing our attention away from where it should be. The accident may be classified as human error but there was likely a first cause for the error distraction. Investment errors could be classified as biases but they are likely driven by distraction.

One clear distraction that is especially present in financial markets is information overload. There are old studies of flawed "locally rational" decision-making. When there is the mere presence of new information, it is often used even though it may not be necessary. Good traders are able to focus their attention in order to minimize distraction. They may not be smarter than others, but they are able to focus better than most. 

One key advantage of quantitative models is eliminating distractions and reducing sensory overload from too much information. Models focus only on a limited set of preselected information in order to reduce the impact of insignificant data. Level of significance sets the threshold for distraction. If there are some data that have high predictive ability, it is better to focus on this information and exclude data less relevant. 

Trend-followers attempt to solve the distraction problem through only looking at price information. Prices may already embody information from other sources, so attempting to find a signal in price is efficient and reduces the distraction problem. There are cases of some trend-followers actually blocking non-price information like news reports so as not to be distracted from this perceived noise. 

There is not a single solution to the distraction problem other than to understand that it is real and can affect judgment. Good investment decisions are based on filtering noise. There is value in simplicity and following the adage that less is more. Just because there is a new piece of information does not mean it has to be used. The decision to use all information all of the time can generate biases that will reduce forecasting skill. Pick your information wisely.


Anonymous said...

Better decision making methods are effective only in realms of human activity that are "statistically stationary," or "predictable."

Since markets are not predictable, not statistically stationary, tools for better decision making do not help us become more successful investors. Look at the success that passive indices have achieved!

Sure, distraction may hinder decision making. That much is true. But such insight is applicable only in activities in which better decision making can be relied on to produce better results. There is no evidence that investing is such an activity.

Mark Rzepczynski said...

I do not disagree with the low predictability, yet there are some clear factors that can help forecast rates and the market. Unfortunately, their explanatory power is low and investors get distracted with noise.