Loss aversion, stocks & weight loss

I was first introduced to the concept of loss aversion during some followup research after reading Predictably Irrational by Dan Ariely. While I’ve written previously about how his writings about an experiment on late fees influenced my thoughts on no-show fees in the fitness industry, I find myself returning to the book yet again, spurred by my interest in both finances and physique development.

Loss aversion, irrationality in action

If you decide to check out the original papers, set some time aside because there doesn’t seem to be any publication limits in the behavioural economics world; one of these papers is a 33-page monster (2-5). For those in a rush, the theory boils down to the fact that someone who loses $100 will lose disproportionately more satisfaction than someone gains from receiving $100 (2-5). In a rationale world because the dollar amounts are equivalent between the gain and loss condition, we’d expect that the associated but inverse feelings (sad/loss, happy/gain) should be of equivalent magnitude.

This is one of those concepts where it is difficult to put an exact number on what it feels like to lose or gain, but in some circles it’s thought that a loss has twice the impact of an equivalent gain. This theory is obviously highly applicable to the financial world, as it influences risk-taking investment behaviours, but has even influenced sales tactics and given ‘savvy‘ internet marketers a leg up on consumers (framing).

Perhaps the most common use of the theory, at least in the popular financial press, is to discourage overly-frequent checking of stock values once purchased. Using loss aversion as a rationale, any day your stocks have suffered a loss, the effect of this loss will be disproportionate to any day at which it is higher than your purchase price. While these micro adjustments in stock price may mean nothing in the grand scheme of your investment practice, these small losses can result in irrational, fear-based investing and compromise your long-term financial health.

From a weight-loss perspective, I’m sure anyone trying to lose weight would never describe themselves as ‘loss averse’. Given the psychological implications of frequent stock picking, could there be a parallel between compulsive stock checking and daily weigh-ins when trying drop a few pounds?

Loss aversion as applied to weight-loss

With weight-loss, the theory is the same but operates in reverse. If weight-loss was predictable and you could expect consistent loss, even when weighing in on a daily basis, all would be well. Unfortunately physiology, especially when mixed with psychology, doesn’t seem to play along and produce nice consistent losses on a daily basis. So while gaining some cash can’t offset losing it, one bad weigh-in can offset days of hard work and potentially any previous losses that happened before it. Is that a chance you’d encourage your clients to take?

Does what you do with the data offset what the data does to you?

Believe me, I’m as much of a fan of data as the next guy, but in many cases I’m left balancing my desire to collect as much data as possible with the potential effect it can have on my clients. In advanced trainees who have a handle on things, I wouldn’t worry about their ability to handle frequent weigh-ins. But in new trainees I’m not convinced that the ability to map out trends in bodyweight would offset the potential negative effects. In many cases, it’s not the data that’s the problem, but the way in which we react to it. Just as losing a few extra pounds can reinforce hard work, a few pounds gained could do the reverse. If loss aversion truly applies to weight-loss then we’d expect the effect of this ‘failure’ to be more pronounced than any success.

There’s no universal prescription for the frequency of assessment

My earlier post on running experiments indicated that frequent assessment is essential so it’s not that daily data is bad, but I always rely on multiple measurements over time to make my program adjustments (except for rare cases). Every change you make to your programming is a hypothesis, and it takes time to observe the response in your experiment. Ultimately, the frequency with which you assess your training-related variables, including body-weight, depends on the characteristics of the individual and the specifics of the training and nutrition program.

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