The Learning Loop: A Structured Approach to Improving Results in the Market
Make your time spent in the markets worthwhile.
Note: This post is addressed to both long term investors and day traders. I often use the term trader and investor interchangeably.
Whether you’re serious about trading or just in search of additional income, you employ some level of strategy that is unique to you. It’s your process or model for organizing information and approaching the market, informed by data, graphs/charts, news, mathematics, and other sources.
A good strategy encompasses more than just the charts or data, though. Just because you have the information does not mean you can execute the trade well. If you execute the trade well, then hopefully you have defined your risk parameters and profit objectives well. There’s a lot to it!
Master “multibagger” picker @FromValue recently tweeted that “The best in their industry make complicated things look simple”. He points out that the overuse of jargon is a clear signal of someone who doesn’t fully understand whatever it is that they are discussing, which gets to the heart of really learning whatever it is you are working to master.
Similar to best-in-class in their industry, the best traders or investors can take complex market data, simplify it, and then get the trade off without a hitch. Traders that follow haphazard processes, on the other hand, struggle to replicate that success.
This ability to break down complex things for decision making can obviously give market participants an edge: they can bypass the emotional triggers that haunt many and make a decision based on an objective view of the market.
Objectivity
We all know that one of the biggest obstacles to achieving objectivity is our emotions, which create biases. In his book Adaptive Markets, Andrew W. Lo describes the serious consequences that emotions can drive:
“Psychologists and behavioral economists agree that sustained emotional stress impairs our ability to make rational decisions. Fear leads us to double down on our mistakes rather than cutting our losses, to sell at the bottom and buy back at the top, and to fall into many other well-known traps that have confounded most small investors…Our fear makes us vulnerable in the marketplace.”
How do we get closer to objectivity in order to make better decisions in the marketplace?
The first thing to know is that there is a level of uncertainty in trading outcomes. It is an objective fact that nobody knows where a market is headed next. If you buy shares in a company that you think has significant upside, you have no way of knowing whether or not the company will meet growth forecasts or continue to execute well on the business plan. If you’re a day trader, a badly timed announcement can cause a trade to go against you.
A good decision can have a bad outcome because of bad luck. A bad decision can be rewarded because of good luck.
In her book Thinking In Bets, former professional poker player and decision-making guru Annie Duke discusses the art of the decision. You must be comfortable with uncertainty, admit/recognize when you’re uncertain about something, and then try to narrow down the possibilities to strive for the best possible outcome.
Duke points out that you must have an organized process:
“We can’t just absorb experiences and expect to learn…There is a big difference between getting experience, and becoming an expert. That difference lies in the ability to identify when the outcomes of our decisions have something to teach us, and what that lesson might be.”
She suggests creating a learning loop, which has become an integral part of how I’ve learned to improve my trading/investing, and which I discuss in further detail below. Whether you are investing in the short or long term, you get feedback on your decisions. For the day trader, this feedback comes pretty quickly, sometimes immediately.
I picture the learning loop as in the image below.
Beginning with the “Belief” circle: informed by your data/chart/etc, you form a belief on what you think may happen; you formulate the odds, expressed by how confident you are.
Second, you make the decision to either buy or sell, and how many contracts/shares.
Third, there is an outcome (you make money or you lose it).
The crucial next step refers to what Duke says above about recognizing whether or not there is a lesson to be learned, and how that lesson should be used to update your belief. The mistake, represented by the dashed line, is to continue doing the same thing without improving the quality of your decisions.
Let’s dive into this some more, set some ground rules, and then discuss implementation.
Fintwit account @fatbabyfunds said “If you aren't tracking your mistakes, you probably aren't learning from them”, and in many ways, this tweet inspired me to dig deeper into the process of tracking mistakes. There are certain mistakes that are big enough to never forget, but even minor mistakes have lessons to teach. As Fat Baby says, tracking your mistakes gets at the heart of improvement.
Being able to admit these mistakes gets right at the fabric of Duke’s point that there has to be an understanding that there is a level of uncertainty, and therefore the possibility of some bad luck too.
Tracking mistakes - and positive lessons, too - will help you to continually update the learning loop. Depending on what you are trying to do, you may make many mistakes until you start to iron out the creases in your approach.
Plan to start a journal, take notes, or follow the learning loop from my image above. Track your mistakes to learn from them.
Some ground rules:
You do not need to know where the market is going next to trade or invest.
Admit "I'm not sure" when you are not sure. You only need to say this to yourself, so no excuse not to do it.
Get into the habit of writing things down; this helps us learn.
When recording, do not editorialize or give yourself credit where you have not earned it. (This is hindsight bias, I wrote about it in a tweet and it’s of utmost importance to be aware of in this exercise).
Implementation
At a high level, I have found it to be helpful to go through each of my trades with the use of the learning loop, revisiting my decisions to close the loop and update my beliefs.
The overarching goal is to learn to formulate beliefs for trades that get closer to the desired outcome; to use your edge/analysis to formulate “most likely” scenarios.
The purpose of the learning loop process is to use our outcomes to improve out beliefs and out bets. For this reason, the focus of this post is on how to evaluate outcomes and not on how to form a belief or how to conduct analysis.
Let’s start at the end of the learning loop, with outcomes, with the goal of improving what it is that we feed into our beliefs and bets.
Classify Outcomes. The most important habit to put into practice centers on classifying outcomes as luck or skill, based on what you did to create that outcome.
The focus is on your process. However, if your process involves getting trading tips from someone else, then it makes sense to classify outcomes based on their process as well. If you are not aware of what their process is, then focus on your process in how you interpret and apply the guidance from someone else or focus on what they are teaching you. Adapt as needed.
Here are some examples on classifying outcomes, and let’s assume these all result in good outcomes/profitable positions:
Spend hours on researching and developing an investment thesis on a stock: mostly skill.
Purchase charting indicators that ring a bell when it’s time to buy: mostly luck.1
Open position based on your trade criteria being met: mostly skill.
Go long after the market has been going down all day, because you feel like it can’t keep going down any further: mostly luck.
Trade the opposite of what just happened, trying to catch micromovements and calling it a scalp: mostly luck.
Waiting for a trade to come to you: mostly skill.
Close eyes, click a button: all luck.
All of these outcomes can theoretically result in a profit. In particular, the last bullet point has a perfectly possible route to profitability and was not meant as a joke.
But to really improve, you need to be honest with your own results. Physicist Richard Feynman said:
"The first principle is that you must not fool yourself, and you are the easiest person to fool."
Continuing to pursue a strategy based mostly on luck will probably set you up for compounded failure in the future, like a house of cards ready to fall. Doing so could also reinforce a bad habit that will undermine consistency.
On the other hand, developing the skillset that produces profits gives you the reinforcement you need to lean into a winning strategy.
For these reasons, try to take notes on when and how you formed a belief so that you remember later on down the road.
Belief: “Revenues grew by 20% for 8 quarters in a row, but grew 4% in this most recent quarter, so I think it’s time to take a profit.”2
This is skill-based analysis, and you will get feedback on whether or not this was the right choice.
Belief: “The market just dropped 30 points, I bet this is the bottom, so I am going to go long here.”
This is luck, and if you do this every time the market drops 30 points, you are likely to get burned.
All of this helps you to watch your habits, identify patterns of success and failure, and helps you to feed new information into your beliefs and bets.
Rate your “bets” with a confidence/risk interval. As we learn lessons from outcomes and feed this information into belief formation, the crucial next step is in how we manage and tweak our bets. This is a form of creating or evaluating risk management.
A trading strategy without a risk management framework is incomplete. Mark Douglas, a psychology/mentality coach for market participants, listed “afraid of losing money” as one of the main challenges that we face.
As beliefs improve, we want to to evaluate our risk in advance of a position. If we are persistently afraid of losing money, we likely are being too risky in our bets. One way to think about our risk framework is to assign confidence intervals to our bets.
Possible ratings can be low/medium/high confidence, a numerical scale, or assigning an amount to invest/trade with based on your confidence. By evaluating outcomes and developing skills, we can move towards higher confidence trades or investments. For instance, in reference to the example belief above, next time a stock’s revenue growth declines, we can confidently sell.
The process of this learning loop can be adapted for any decision-making process. In the current bull market environment, many names are doubling or tripling with ease. It has been my practice over the last ~18 years of investing to always have a plan, because it will not always be like this.
For that look for day trades or swing trades over the short or medium term, it is wise to think about strategy early and often.
Finally, a few parting thoughts:
Know what data you want to use for belief formation processes, like market profile, advisors, other Twitter users, technical analysis, CNBC, whatever. You could begin by evaluating whether or not what you are doing is working to meet your goals. This could be a learning loop in itself; discovering what data you want to use or recognizing what motivates your decisions.
Do not confuse inexperience with incompetence. This is a learning process, and if you’re new to markets, you have less experience and will want to work on gaining competence.
Organize the data you want to use. Having this structure in place helps you cut through the noise and can make decision-making more efficient. I have shared the process (and analysis with the Market Profile) in the Trader Manifest, though this is specifically tailored to S&P E-mini 500.
As you gain experience, you begin to think through your decisions with a growing confidence interval. You have more conviction in your trade. You may double down, or take other steps that reflect strong or growing conviction.
This one is tricky. While the software may be useful for plotting support/resistance, it omits the circumstances surrounding the trading environment.
Sample metric; I am not advising to sell at any revenue decline, nor am I suggesting that 20% revenue growth is a target.