Last Updated on December 2, 2024
Overview – Does a Trial and Error Approach Work in Investing?
There are many endeavours where the best way to learn what works is to first find out all the ways that don’t. That is, sometimes the best approach when trying to figure something out is through trial and error.
Learning to walk, learning to code, learning to use a mathematical equation for the first time: there are many instances where our best option is to simply try something out and to learn from our mistakes as we go along.
If a trial and error approach works for so many endeavours, then surely the same can be said about investing, right?
After all, every investor starts off as a beginner, and theoretical knowledge can only take them so far until they have no choice but to gain some hands-on experience. Over time, an investor’s style changes based on the lessons they’ve learned along the way.
While an investor adapts as they gain more knowledge and experience, this doesn’t mean they can accelerate this learning process by burning through their resources via trial and error.
The Requirements of Trial and Error
When an infant learns to walk for the first time, chances are they’ll repeatedly stumble and fall before they eventually learn how to balance themselves. When a math student tries to learn a set of equations, chances are they’ll perform lots of practice (and, inevitably, make mistakes) before finally figuring out how the equations work and how to apply them to any relevant problems they come across.
Trial and error, in any endeavour, is the process of burning through your resources in an attempt to figure out what does and doesn’t work.
Sometimes, the resources being spent aren’t immediately obvious, but it doesn’t take long to uncover them: a child learning to walk uses up their physical energy, and a math student uses up their stationery (or battery life if they’re using a device such as a tablet) and mental stamina.
In these scenarios, there’s nothing wrong with taking a trial and error approach because the resources being spent are: (a) inexpensive, and (b) are easy to recoup. These conditions are merely empirical, but this observation can always be seen any time trial and error is being performed.
No rational person would perform trial and error if the resources being spent were very expensive. For example, unless you have lots of money to burn through nobody would buy several different smartphones to figure out which one works best for them because the amount of money spent would be exorbitant.
Because trial and error processes consume resources that are inexpensive and are easy to regain, the argument can be made that trial and error works best on resources that aren’t as heavily affected by scarcity.
Understanding Scarcity in Economics
Imagine you recently filled up your car, which is enough fuel to last you for two weeks. You work from home, but there are some places you still visit regularly – the grocery store, your favourite park, the occasional trip to the mall across town, etc.
You have lots of places you want to visit, but the amount of fuel will only last you for two weeks and will last you for less if you drive more than usual. So, given the limited amount of fuel at your disposal, you’ll need to adequately plan how to best use this resource before you can gas up again.
This scenario is a classic example of scarcity.
Scarcity is one of the most fundamental concepts in economics. Scarcity occurs when the demand for a good or service is greater than its availability. Sometimes, you can’t have everything you want because the resource in question is limited, and other people want the same resource you do.
In our previous example, you can’t drive wherever you want all the time because your fuel is limited. You’re not the only person who needs to fuel up their car, and there’s only so much fuel to go around until the gas station needs to be refilled.
You could refuel more frequently if you plan to drive a lot, but the amount of fuel you can put in your car is limited by the amount of money you have, which is also a scarce resource. Chances are, there are other things you need to spend your money on other than fuel.
In the context of economics, it’s important to understand that “scarce” shouldn’t be confused with “very little”. Cattle is a scarce resource – lots of people want to eat beef, but there aren’t enough cattle at a given time to meet this demand.
In 2020 there were an estimated 987 million cattle around the world – no sensible person would call that amount “very little”, but assuming billions of people around the world want to eat beef, then there certainly isn’t enough cattle for everyone.
So, how exactly does scarcity relate to trial and error?
Trial and error is the process of consuming resources to figure out what does and doesn’t work. Nobody has an infinite amount of resources at their disposal, but some resources are more scarce than others. Therefore, trial and error works best when the resources being consumed aren’t that scarce.
Infants can learn to walk as much as they want because the only resource they’re spending is their energy (technically they’re consuming their time as well, but an infant has all the time in the world). If they’re tired, they can sleep or eat to regain their energy then go back to learning how to walk.
There’s no harm in taking a trial and error approach if the resources being consumed aren’t heavily affected by scarcity.
However, herein lies the problem with taking a trial and error approach in investing: the resources that an investor regularly uses are scarce, so the last thing an investor wants to do is to burn through them nonchalantly for the sake of experimentation.
Why Trial and Error Doesn’t Work Well With Investing
Investors use a number of resources in their day-to-day work, but two of the most valuable, by far, are their time and money.
Now, not all investors are made equal: that’s why there are different types of investors based on their financial means and level of experience. However, there is one aspect in which all investors are equal: nobody has an infinite amount of time and money. Time and money are both subject to scarcity.
Even the largest institutional investors in the world have a limited amount of capital, so the last thing they’d want to do is waste it for the sake of experimenting.
Every day, we all get the same 24 hours. If we spend our money, we can re-earn it down the road. However, what makes time arguably even more valuable than money is the fact that it cannot be recouped. No matter what we do, we cannot get lost time back. Are you really willing to use this non-renewable resource for the sake of trial and error?
So, if an investor insists on taking a trial and error approach to try and learn something or to experiment, they must understand that they’re about to burn through two incredibly valuable resources.
It’s true that some investors have more money than others, and they can have someone else perform experiments on their behalf, but no investor can afford to run prolonged trial and error experiments because they’ll eventually run out of either time or money, whichever comes first.
Investors are constantly looking for the best possible use of their limited time and money to help them achieve their goals. So, unless an investor really has no better use of their time and money, they probably can’t afford to spend them trying to figure out which portfolio compositions give the most yield or which industries have the highest return over a certain period of time.
As long as scarcity exists, does this mean investors have no way to test certain ideas or to perform any sort of experiments whatsoever?
There is a way for investors to try out certain ideas or to perform experiments…to an extent. One possible solution is to use an investment simulator.
Performing Trial and Error in Investment Simulators
We know that the problem with trying to experiment as an investor via trial and error is that an investor’s resources are limited, and as a result, are subject to scarcity. No matter what an investor does, they will always receive the same 24 hours every day, but something can be done about their limited supply of money.
Instead of burning through real money, an investor can give themselves all the money they want by using an investment simulator.
In an investment simulator, an investor can try out all the different portfolio compositions or investment strategies they want without worrying about running out of money to burn through.
Using an investment simulator partially solves the problem of trial and error because now one of the resources, money, is no longer scarce. Now, an investor can try as many different portfolio compositions, asset mixes, and other strategies without worrying about how much money they’re spending.
Although the problem of scarcity has now been addressed for money, the same cannot be said for time. How much time an investor wants to dedicate to using a simulator as opposed to managing their real portfolio is something they still need to think about and manage.
Wrapping Up
In many endeavours, the best way to learn what works is to figure out all the ways that don’t. Sometimes, it makes sense to learn and experiment through trial and error.
However, trial and error require resources to be spent: time, mental energy, money, etc. The problem is that many resources are scarce, that is, the demand for those resources is greater than their availability. Everybody wants more time to do the things they want, but every day we get the same 24 hours no matter what.
Taking a trial and error approach in investing is tricky because the resources that are most likely to be spent are time and money: two resources that are scarce, and as a result, are highly valuable. No investor, no matter what classification they fall under, has an infinite amount of these resources to burn through nonchalantly.
However, there is a workaround to this problem. By using an investment simulator, investors can have all the money they want, albeit virtually. Now, money is no longer scarce, but time still is: an investor still needs to decide how much time they want to dedicate to performing experiments in the simulator and how much time to dedicate to other tasks.
