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How to Learn from Your Mistakes

Eric March 9, 2024

When everyone starts trading, they start at a certain level. Maybe they’re horribly unprofitable. Maybe they tend to break even. Maybe they’re talented and are insanely profitable right off the bat. However, what everyone has in common when starting out is that mistakes will be made.

The mistakes can be small, and they can be big. They can be as small as clicking the wrong button or as big as forgetting about an earnings report. Regardless, no one is perfect and learning from your mistakes to make sure you don’t make them again is the key to constant improvement. When you improve this way, nothing can stop you!

However, there’s a slight problem when it comes to trading: Randomness and Luck.

Learning with Uncertainty

Let’s say you’re learning how to throw a basketball. You have a ball. You have a hoop. You practice every day. Over time, your body will learn how to adjust for the weight of the ball, the distance and height of the hoop. Over time, you will learn how to be really good at throwing a basketball.

Let’s say you’re learning how to predict what the top card will be in a randomly shuffled deck. Would you get better over time if you practiced every day? What if the activity was a coin flip? 

I hope it is obvious that in the first example, it is easier to learn how to do that activity over time whereas in the second activity, it is near impossible. 

Why is that? It is not possible to predict random events. It is not possible for you to get better over time because there is nothing in your abilities that improves outcomes. That’s the definition of random. If you could predict it, it would not be random.

Where do you think the stock market (or any market for that matter) lies between these two examples? Are they highly structured and predictable or entirely random?

Becoming an Expert…in Markets?

There are four things it takes to be an expert. They are:

When it comes to trading, you may have many repetitions of trades you make. You’ll also get timely feedback on your trading decisions in the form of a profit and a loss. If you’re disciplined enough, you’ll be practicing on a deliberate basis over time.

When it comes to becoming an expert in markets, the big question is whether or not markets are a valid environment. 

But what is a valid environment? It is defined as one with regularities that make it somewhat predictable, and therefore, learnable.

This suggests that to become an expert in markets, you need to:

  1. Believe markets are not entirely random
  2. Try to figure out the learnable regularities within the markets that help you become consistently profitable

There is a great debate over whether markets are entirely random. I won’t get into that debate here. It is simply important to reflect that there are random components and non-random components to market movements. 

If this is the case, you can become an expert on the regular and systematic part of markets, allowing the random parts to simply stay random.

Learning from Your Mistakes

Randomness is likely the main reason why most people fail at becoming consistently profitable. They learn all the wrong lessons such that all their experience goes to waste. Over time, the inevitable happens and they lose all their money. 

You cannot become consistently profitable if you do not learn the right lessons.

But what are the right lessons? How do you learn from your mistakes?

Most people believe that if they lost money, they did something wrong and if they made money, they did something right. This could not be further from the truth.

You can easily make money with dumb luck while also taking on too much risk. Also, you can easily lose money after carefully assessing the risks and benefits of the trade.

Let’s say you have a coin where if it’s heads you make $100 and if it’s tails you lose $200. You flip the coin and it becomes heads so you make $100. Did you do something right?

Let’s say you have a 6-sided die and if you roll a 2-6 you make $100 and if you roll a 1, you lose $200. You roll the die and it comes up 1 so you lose $200. Did you do something wrong?

Which game would you rather play over and over again? The Heads vs Tails or the 6-sided die? 

I hope you chose the 6-sided die…

You structure the game you want to play with your research. After research, you determine whether you’re playing a losing coin game or a winning die game. However, no matter how much research you do, you’re still going to take risks. You’ll have to be subject to randomness along the way.

Learning from your mistakes has little to do with the outcome of your actions. Rather, it has to do with how well you chose the coin vs die game. In other words, learning from your mistakes is about improving your process. Your process determines the type of die you’re playing, the win/loss ratios and probabilities. 

Learning for your Process, not the Profit & Loss

If you have a strong process, the Profit and Loss will show it over time. If you have a great Profit and Loss for a period of time but a bad process, your gains will eventually fade away.

Let’s say you want to buy ABC stock. If your reasoning is because you heard it on the news, it’s not a great process. Why? Because if everyone made money by listening to the news, everyone would be rich. The process has been time tested in the past by millions of people who have all lost their money only listening to the news for trade ideas. Why would you be any different?

If your reasoning is more robust and rests on fundamentals about the economy, specifics of the company, and market positioning, then you’re onto something. You can structure the trade to have a higher reward to risk ratio and take on the risk.

If you make money, great! However, it doesn’t mean you can’t refine your process further.

If you lost money, booo!! However, it doesn’t mean your process was bad.

Identifying your mistake has nothing to do with the outcome. It has everything to do with assessing whether your process was strong enough to cover all the necessary bases.

Let’s say you were short a stock, but you lost money because the stock went parabolic against you. You later learn that the short interest was really high when you were shorting them. Therefore, the runup was a bunch of short covering.

What was the mistake? You didn’t check the short-interest before shorting a stock. That’s something you can incorporate in your process in the future.

Avoiding Outcome Bias

Outcome bias is when you judge the decision based on the outcome of the decision. You can judge the outcome by the result when there are no random elements in the situation (e.g. playing chess). However, connecting outcome with decision quality is less effective when there is randomness involved. That is how the bias starts creeping into our psychology.

You want to avoid outcome bias when assessing your mistakes. Instead of determining whether a decision is good or bad based on the outcome, ask yourself a simple question:

What was the quality of my decision at the time of the decision with the information I had at the time of the decision?

If more information would have helped (like with the short interest example above), then you can improve your process. If there is nothing more you could have done, you might have made a good decision even though you lost money.

If your trading has a built-in learning process that improves your good decisions and reduces your bad decisions as informed by your mistakes, then it is only a matter of time before you become consistently profitable. It’s really that simple.

Key Takeaways

1

Determine how much you believe markets are random. If you believe they are entirely random, there is little expertise you can develop. If you believe they are not entirely random, focus on becoming an expert in the non-random parts

2

Learning from your mistakes is about refining your process. If you focus on developing a strong process, your profit and loss will come naturally

3

Avoid outcome bias when assessing the quality of your decisions. Determine the quality of your decision based on the information you had at the time of the decision, not on the outcome of the decision.

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