Last Updated on April 23, 2021 by Oddmund Groette
The two researchers hypothesized that there might be a psychological explanation: when faced with a problem, people tend to select solutions that involve adding new elements rather than taking existing components away.
Did you know that the removal of traffic lights and road signs leads to fewer accidents? Why is it that we always want to add more complexity to a solution? Why don’t we remove items of information when solving a problem? Why don’t we remove laws and regulations to solve problems? Why do we add legislation instead of removing it?
I recently came across an interesting article in Scientific American written by Diana Kwon that explains how we can remove elements instead of adding and still get a better solution. Removing elements is for many a radical idea, but it shouldn’t be.
This is very relevant for traders and those interested in quantifying problems. Most of us make strategies based on many variables, yet it’s often the few and simple models that turn out to be both better and more reliable.
Why is trading difficult?
Morgan Housel writes in the brilliant book The Psychology of Money that an engineer can have a successful career knowing not much else than engineering. The same goes for a veterinarian – he or she doesn’t need to know much else. But in business, trading, and investing it’s not like this. Trading is a little math, psychology, game theory, history etc. Perhaps this doesn’t make it harder, but it certainly makes it much more prone to change and uncertainty. Imagine all the criteria you can put into a trading strategy! It’s endless.
Less is more in trading
Rory Sutherland wrote in his book Alchemy that bullshit multiplied by bullshit means bullshit squared. He’s right. The easiest and best solution in many cases is to remove information or criteria. A good quant makes things simple.
The chart below explains why Sutherland is right:
Once you have a minimum of information to form a judgment, it doesn’t improve the outcome by adding more information. Nassim Taleb once wrote that the easiest way to bankrupt a fool is to give him lots of information.
Jim Simons has made a fortune using quantified strategies in the markets, but in the book The Man Who Solved The Market the author argues the strategies are neither novel nor sophisticated.
Why do we make trading complicated?
Most likely we have an in-built bias toward complexity. This is what Diana Kwon writes in the article:
While the propensity for businesses and organizations to opt for complexity rather than simplification was previously known, the novelty of this paper is that it shows that people tend toward adding new features, “even when subtracting would clearly be better,” he adds. Meyvis also notes that other reasons for this effect may be a greater likelihood that additive solutions will be appreciated or the so-called sunk-cost bias, in which people continue investing in things for which time, money or effort has already been spent.
Curtis Faith on complexity:
Many have not heard about Curtis Faith, but he was one of the original “Turtle Traders” in Richard Dennis’ successful trend-following project back in the 1980s. Mr. Faith has written one of the best trading books out there: an easy to read book about the most important aspects of trading. Here are Curtis’ view on complexity:
It takes a lot of time and study before one realizes just how simple trading is, but it takes many years of failure before most traders come to grips with how hard it can be to keep things simple and not lose sight of the basics (page 115)…..Keep it simple. Simple time tested methods that are well executed will beat fancy complicated methods every time (page 131)……In a similar manner, simple rules make systems more robust because those rules work in a greater variety of circumstances (page 212)…….People have a tendency to believe that complicated ideas are better than simple ones….Some of us thought that trading successfully couldn’t possibly be that simple; that there must be something else to it (page 224).
Complexity increases the risk of curve-fitting:
As Curtis Faith mentioned in his book, complex strategies increase the risk of curve-fitting. Simple systems are more robust because the rules work in a wider variety of circumstances.
Traders should keep in mind Occam’s Razor
William of Ockham (1285-1347) argues the simplest of two theories should always be preferred to a more complex one. This is something all traders should have in the back of their heads.