“One reason for the inferiority of expert judgement, compared with algorithms is that humans are incorrigibly inconsistent in making summary judgements of complex information” –
This is the seventh and last post in the series on Trend Following, the previous post and the ones before that can be accessed here. See list of Capitalmind Chase posts here.
So far we looked at how to build a trend-following system for yourself, but then what use is a system if you cannot diligently follow it. This post is all about that, ie how to follow the rules of a trend following system.
For conversation’s sake let’s say you trade CM Chase or any Trend following strategy for that matter. What if I could ask you to buy me a beer every time you prematurely exit Chase? My guess is, I would be set for life.
Jokes apart, they say every saint has a past, and it won’t be fair if I don’t accept that I’ve done all of this and more.
The question on hand is – Why do we break rules?
Why cut short or break a well-oiled system that has stood the test of time, I mean the back-test.
Why do we not trust the system, the system that is based on a set of variables namely, price, averages of those prices, etc.. More so a strategy that’s proven that it can make money and it has kept its side of the bargain for a while now.
So, what is the problem?
What’s interesting is that every time we break the rule, we promise not to do it the next time.
Why do we do it then? Does the answer lie in what behavioral economists call Intertemporal discounting? Partly and there are others, let me share a few with you. See which one appeals to you.
Intertemporal discounting
Let’s say you are in a trade for the past three days, you can take 200 points of gains today and exit, or hold on for three more days for probably 200 more points. What do you do?
I bet you would say, give me my 200 points now, and we shall see you when the next signal happens. Wonder why?
It’s just the way we humans process such dilemmas – our brains discount future gains and add a premium to present gains or in other contexts, our brains accentuate present pain and discount future pain/gain.
For instance, you know that quitting smoking is right for you in the long run, but quitting today brings some ‘pain’ and that pain of quitting today is much closer to present on the timeline than the pain of, say, dying of lung cancer somewhere in the future. This is pretty much how we view the payoffs and it extends to our trading desks as well.
So is it Intertemporal discounting at play? Our brains tendency to accentuate the gains/pains of the present and discount the possible gains/pains in the future.
Loss aversion
Closely related to the concept of intertemporal discounting is the idea of ‘loss aversion’. We must thank Daniel Kahneman for having made this a household term.
If you made 1000 points on a trade, you feel good. But if you saw 1000 points of gains and gave it all back, you would feel considerably more hurt. That’s one way of looking at loss aversion, it hurts more to lose than to gain.
Hence our tendency to avoid losses overpowers our tendency to make gains.
In the context of trend following, where typically we have more instances of losses than gains, this tendency to ‘protect gains’ accentuates even more and makes us break rules. Even though we know that following the system stands to make more profits, in the long run.
Algorithm aversion
Imagine you and your friend are driving out in separate cars. Midway you get stuck in traffic. Up until that point both of you followed the google map, however now you decide to ditch it because you intuitively know of a shorter way to get to your destination. Come to the destination and you see your friend there, having reached before you, all because he followed the map? And you tell yourself…
So what happened, for a quick second did you think that you are smarter than what google maps could have worked out? Did we just do a Gary Kasparov?
This is what we call an “algorithm aversion”. Where we think we can outmatch a computer’s brute computational power of doing all those complex calculations in a jiffy and yet we take the road less traveled.
Trust
Look around, you would see so many people who don’t want to take the Covid vaccine, and then there are some who don’t want to take the Indian one over the Oxford one and so on. At the heart of it is a lack of trust.
A trading system is similar to a vaccine, could be painful in the short run, but works well in the long run.
For many of us, it’s not easy to trust something that’s not our creation. Donald Sull in the book, Simple Rules: How to Thrive in a Complex World – echoes the same.
Trust is not a simple phenomenon by itself, you see, we cannot be omniscient, so we have to trust others, we have to trust others for most of our existence.
That being the case, who and what we trust becomes critical, and that boils down to our ability to reason.
Egotism, Self Esteem, Intuition
While factors like intertemporal discounting, loss aversion and algorithm aversion are key factors that lead us astray, at the heart of it lies something more meta. It is how we feel about ourselves and the rules that we intend to follow.
At times intuition dons the garb of intelligence, and we all want to be intelligent, let me rephrase that, we all want to at least think of ourselves to be intelligent. It ties well with our innate need to feel good about ourselves, and that makes us give in to our intuitions.
Kahneman calls it System 1 thinking, much before him, psychologists such as Chris Argyris had talked about it.
This kind of thinking is all about being fast and instinctive and guess what, it is where emotions creep in too, once that happens, to borrow from Jonathan Haidt, “The emotional tail wags the rational dog.”
The decision to ditch the ‘google map’, because you know better – that was System 1 thinking.
Popular science titles like Blink by Malcolm Gladwell and Gut Feelings by Gerd Geiringer, don’t make it any easier by extolling the virtues of intuitive decision making.
So what is wrong with taking a few snap decisions?
Was it Ray Dalio who said ‘Never seize on the first available option, no matter how good it seems’.
The problem I guess is, it’s too hard to think holistically in a fraction of a second, it’s just not possible, and that’s the reason, in any critical context, be it surgery or flying an airplane, you rely on flow-charts and checklists, which is nothing but an algorithm.
Trading is no different, the costs of bad decision-making can be huge. Our time and cognitive capacities are better spent in creating rule-sets and frameworks rather than dousing fires.
Getting out of the way of the system
While rule-following is challenging, it’s not impossible.
Kurt Lewin, the German-American psychologist, has a fascinating take on behavioral change. He looks at any behavior as an equilibrium, there are driving forces that help us say to follow a set of rules, and then there are restraining forces that make it hard for us to follow a rule set, what we tend to do more often is to add to the driving forces. But Lewin believed that it’s more important to reduce the restraining forces.
Following Lewin’s idea, here are some ways to make it easy for you to stick to rules
Get out of the way: Go have a beer, make yourself redundant and let the system do what it does best, follow the rules. Probably the easiest way to play your part is to not interfere.
Ignore the outcome: There is a nuance to this. Try varying the time intervals at which you monitor/evaluate your position. If you usually look at the outcomes weekly, do it monthly, that would increase your tolerance.
The other way to ignore the outcome could be by position sizing your trades, in a way that the outcome becomes less significant.
Work with like-minded people: Peer pressure/herd behavior, if it works for you. It’s easy to follow a rule-set if others around you are trying to do the same, the goal is no longer the outcome, but rule-following itself is the goal.
Make it yours: One way to increase engagement with the rule is to tweak it in a tiny way, find your sweet spot. Time intervals, Positioning sizing, Exits, SL. It’s tricky and can be a slippery slope but one needs to be hands-on to be able to come up with something meaningful. That way, we are happy to have contributed to the ruleset, we have a sense of ownership, and the ruleset, survives.
Log and document the trades: This is a biggie and I know several who swear by it. Seeing is believing. If you break the rule, let there be a log for it.
Understand the outcome distribution: DIY. Yes spend some time sifting through the data to understand the odds of various events, you will see your tolerance increase. For instance, if the win rate is say 40%, you know that 60% of the time you are going to lose, makes it easier to accept the losses.
Hopefully, some of these ideas help in your next trade. Don’t expect a radical change though, iterative and incremental changes are much more sustainable and lasting.
If you are still in doubt about rule-following, read the excerpt from this seminal paper by Robyn M Dawes, an expert in human judgment, who wrote this way back in the 1970s in the context of evaluating humans, the essence of the paper was that a simple algorithm is often good enough to compete with an optimally weighted formula, and certainly good enough to outdo expert judgment. He ends the paper on this strong and emphatic note.
“No matter how much we would like to see this or that aspect of one or another of the studies reviewed in this article changed, no matter how psychologically uncompelling or distasteful we may find their results to be, no matter how ethically uncomfortable we may feel at “reducing people to mere numbers,” – the fact remains that our clients are people who deserve to be treated in the best manner possible. If that means, as it appears at present that, selection, diagnosis, and prognosis should be based on nothing more than the addition of a few numbers representing values on important attributes, so be it. To do otherwise is cheating the people we serve”
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