The topic of loss aversion made an appearance briefly in my reading list again last week and as usual, the author hadn’t really thought about the problem and had merely parroted the usual stuff as to why traders cant take losses. For those who are unfamiliar with the basis for loss aversion it simply states The pain of losing is greater than the joy of winning and this asymmetry leads people to make poor financial decisions.
The original proponents of this form of loss aversion Kahneman and Tversky presented groups of subjects with a number of scenario’s, and then asked them to make decisions based upon the information presented. And it was a similar example to the one below that was shown as an example as to why traders cannot take losses.
One group of subjects was presented with this problem.
In addition to whatever you own, you have been given $1,000.
You are now asked to choose between:
A sure gain of $500
A 50% chance to gain $1,000 and a 50% chance to gain nothing.Another group of subjects was presented with another problem.
In addition to whatever you own you have been given $2,000.
You are now asked to choose between:
1. A sure loss of $500
2. A 50% chance to lose $1,000 and a 50% chance to lose nothing.
In the first group, 84% chose A. In the second group 69% chose B. The two problems are identical in terms of net cash to the subject, however, the phrasing of the question causes the problems to be interpreted differently.
Traditionally this has been reframed into the language of trading in the following way.
Imagine two groups of traders. The first group is asked to choose one of two scenarios. An 80% possibility to win $ 4,000 and a 20% risk of not winning anything or the chance of a 100% possibility of winning $ 3,000.
Traders consistently opted for the certainty of a guaranteed win rather than a chance to make a higher return. The decision to opt for the guaranteed return is made despite it having lower expectancy. The riskier choice had a higher expected value ($ 4,000 x 0.8 = $ 3,200), 80% of the participants chose the safe $ 3,000.
When traders had to choose between an 80% possibility to lose $ 4,000 and the 20% risk of not losing anything as one scenario, and a 100% possibility of losing $ 3,000 as the other scenario, 92% of the participants picked the gambling scenario. Based upon the results of question one, traders are more likely to opt from closing down a winning position quickly rather than allow the position to run for a potentially higher gain. Conversely, traders are more likely to gamble with a loss rather than acting on a stop. Time and time again they will allow a position to degrade even further on the slightest probability that the loss may be smaller than originally envisaged.
But and there is always a but. I have also had the belief that for ideas to be universal in application they need to be scaleable. So the conclusions based upon our first example regarding loss aversion should hold true over any dollar amount.
Imagine you are taking part in a lottery and you are offered an 80% possibility to win $100 mil, a 20% chance of not winning anything or a 100% chance of winning $70 mil. Whilst the correct answer based upon Prospect Theory is to opt for the riskier option since the expectancy is higher it would be a brave individual to opt for this scenario in a single shot endeavour such as a lottery. Despite knowing the expectancy I would opt for the safer road in this example – pocket the $70 mil. In doing so I have in fact opted for the most economically logical outcome. It is here that the traditional interpretation of loss aversion flounders in that it can not be scaled. In fact, it becomes somewhat nonsensical when scaled.
Newer work has also found difficulties with the notion of loss aversion. Work by Derek Rucker of Northwestern University and David Gal of Chicago University seem to indicate that loss aversion may actually be a somewhat overstated fallacy. Their conclusion is that there is no general cognitive bias that leads people to avoid losses. They also look at both the scale and context of losses and gains to provide some perspective.
To be sure it is true that big financial losses can be more impactful than big financial gains, but this is not a cognitive bias that requires a loss aversion explanation, but perfectly rational behavior. If losing $10,000 means giving up the roof over your head whereas gaining $10,000 means going on an extra vacation, it is perfectly rational to be more concerned with the loss than the gain. Likewise, there are other situations where losses are more consequential than gains, but these require specific explanations not blanket statements about a loss aversion bias.
Scale and context are important considerations.
This raises the issue of why are traders slow to take losses, if it, not the pain losing driving these decisions then what is. I would opt that the truth of the matter lies somewhere in between the perceived pain of losing money but this has to be viewed within the wider context of ego defensiveness. Traders like all humans will act to defend their ego at all costs even if this defensiveness has an economic cost. Add into this mix the power of a good story and it becomes clearer as to why traders are slow to take losses.