Unlocking the Secrets of Profitable Trading
A Journey Beyond Technical Analysis
After more than 20 years of successfully trading various assets, from stocks to futures and options, I can confidently assert that the major distinction between a professional trader (profitable and consistent) and an amateur (unprofitable and inconsistent) is that the former does not rely blindly on technical analysis.
In fact, for me as well as many other traders that I know, the turning point came when we realized the need to go beyond the tools provided by technical analysis.
I'm not saying that technical analysis isn't useful, because in fact it is, as it provides us with some useful tools. What I want to make clear is that it covers only a small percentage of the distance that must be covered to become a successful trader.
So, have you ever wondered how effective technical analysis is at predicting the future trajectory of a financial asset?
I'd bet your answer depends on your experience and the time you've been using it, because many traders sooner or later find themselves asking this question when they observe that sometimes the projections derived from technical analysis are accurate and sometimes they are not.
It is precisely in this feature of inconsistency where the greatest problem of technical analysis lies as a predictive tool. Its successes and failures are unpredictable, which hinders its reliability and usefulness for investors and creates a psychological burden akin to a ticking time bomb ready to explode at any moment.
In simple terms, a trader who relies solely on technical analysis as his primary approach to the markets is risking his hard-earned money by depending on a tool that only works occasionally.
In a succinct manner, in order to keep this post from becoming too lengthy, I'll briefly mention some of the main limitations of technical analysis as a predictive tool:
It's based on past data, which causes it to ignore key events such as political or economic events that have not yet occurred.
It's susceptible to a high degree of subjectivity because it relies on perception (what you see on the chart), which can be very different from what another trader sees.
It disregards fundamentals.
It doesn't take into account the changing psychology of the market.
At this point, a question arises: if technical analysis is unreliable, then is there a better way to handle uncertainty and anticipate future movements of a financial asset more accurately? Fortunately, the answer is yes. I want to draw your attention to the way I constructed the previous question, specifically when I mentioned 'handling uncertainty', because accepting and embracing the fact that the market is better modeled by randomness would be a big step that a trader can and should take on their path towards profitability.
Here I want to pause, because in short I will talk about mathematics and statistics, but don't worry, I won't get into the intricacies of technical specifics. Instead, my aim is to explain a vast technical arsenal of key concepts in an intuitive and straightforward manner without using mathematical jargon, and hopefully provide you with the basic understanding that will allow you to perceive the market in a different way, in fact, in a more realistic and operable one.
Let's return to uncertainty, because this is where the key lies. Firstly, let me underscore a fact: the market is governed by unpredictability, in the sense that the future value of any stock asset is influenced by a multitude of factors and may exhibit ambivalent fluctuations. As a result, it's impossible to anticipate such future value with undisputed precision.
The stochastic nature of the future value of our favorite asset, which we strive so hard to predict today, is so pronounced that it impacts not only technical analysis but also more sophisticated tools, such as statistical time series analysis and artificial intelligence. Despite our best efforts, these methods often fall short, providing accurate forecasts only in certain cases, rather than universally reliable predictions across the board.
Accepting that we may be correct in some cases and incorrect in others is precisely where we can embrace uncertainty effectively. Recognizing that my analysis and decisions may be both right and wrong before entering the market is a significant step towards understanding the probabilistic nature of the market and alleviating the psychological pressure derived from the need to always be right.
Thus, embracing the undeniable probabilistic nature of the market allows me to perceive things differently. It frees me from the unrealistic need to always be right and introduces a fundamental concept: the notion of assigning a probability of success to each trade, rather than focusing solely on being right or wrong.
Here, the approach undergoes a radical shift. Instead of seeking that infallible technical indicator or that machine learning model that will predict tomorrow's price, I redirect my focus towards creating a trading system that tilts the probabilities in my favor. The goal is to ensure that the sum of favorable events exceeds the sum of unfavorable events.
And well, here's the good news you deserve if you've made it this far in the reading: you do not need to be a math wizard to be profitable, because any trading system (solid foundations) is a winning system, if it focuses not on its ability to correctly anticipate the future, but rather on creating an advantage from a probabilistic standpoint, whether in other contexts it tends to produce negative results.
Yes, just as you're reading it, even a simple system, let's say a crossover of two moving averages, is susceptible to being a winning system if we have the ability to bias the probabilities in our favor with its use.
The immediate question that arises is how to bias the probabilities in my favor. Fortunately, the answer is less complicated than it might initially seem. While there is a vast mathematical and statistical framework supporting everything, involving advanced techniques such as stochastic calculus, random functions, quadratic forms of Brownian motion, statistical inference, and so on, thankfully in practice, we don't need to delve into all of that.
On the contrary, a very basic understanding of concepts such as random walks, the normal distribution of returns, expected value, and variance is sufficient. These concepts all converge to provide nothing less than an average that indicates the positive contribution (or negative, in case of making mistakes) of each of our trades, considering the historically calculated probability of success.
In other words, a numerical representation of the potential positive or negative expected contribution of your next trade before you execute it. This removes uncertainty from the decision-making process and, ultimately, provides you with an invaluable tool for making informed decisions. On top of that, it becomes a powerful ally when dealing with the anxiety and emotional burden of trading, by providing a quantifiable measure that can be known before any action.
There is indeed an abundance of books, blogs, and videos available on the use of probabilities (expected value) in trading. While some sources provide valuable insights, unfortunately many lack a deep understanding of the mathematics behind it, resulting in explanations that are not as comprehensive as desired. However, these resources can still serve as a good starting point for traders looking to grasp the concept.
I plan to publish several follow-up parts to this post, where I'll delve into more specific details to offer actionable guidance on incorporating these concepts. However, time is a scarce asset for me, not because I spend long hours in front of the screen, but because I limit my work engagement as practice for maintaining happiness. Therefore, I must find the time to produce the continuation of this publication, but I will find it, because at this stage in my journey as a successful retail trader, I'd like to share knowledge for the benefit of the trading community.
After more than 20 years of successfully trading various assets, from stocks to futures and options, I can confidently assert that the major distinction between a professional trader (profitable and consistent) and an amateur (unprofitable and inconsistent) is that the former does not rely blindly on technical analysis.
In fact, for me as well as many other traders that I know, the turning point came when we realized the need to go beyond the tools provided by technical analysis.
I'm not saying that technical analysis isn't useful, because in fact it is, as it provides us with some useful tools. What I want to make clear is that it covers only a small percentage of the distance that must be covered to become a successful trader.
So, have you ever wondered how effective technical analysis is at predicting the future trajectory of a financial asset?
I'd bet your answer depends on your experience and the time you've been using it, because many traders sooner or later find themselves asking this question when they observe that sometimes the projections derived from technical analysis are accurate and sometimes they are not.
It is precisely in this feature of inconsistency where the greatest problem of technical analysis lies as a predictive tool. Its successes and failures are unpredictable, which hinders its reliability and usefulness for investors and creates a psychological burden akin to a ticking time bomb ready to explode at any moment.
In simple terms, a trader who relies solely on technical analysis as his primary approach to the markets is risking his hard-earned money by depending on a tool that only works occasionally.
In a succinct manner, in order to keep this post from becoming too lengthy, I'll briefly mention some of the main limitations of technical analysis as a predictive tool:
It's based on past data, which causes it to ignore key events such as political or economic events that have not yet occurred.
It's susceptible to a high degree of subjectivity because it relies on perception (what you see on the chart), which can be very different from what another trader sees.
It disregards fundamentals.
It doesn't take into account the changing psychology of the market.
At this point, a question arises: if technical analysis is unreliable, then is there a better way to handle uncertainty and anticipate future movements of a financial asset more accurately? Fortunately, the answer is yes. I want to draw your attention to the way I constructed the previous question, specifically when I mentioned 'handling uncertainty', because accepting and embracing the fact that the market is better modeled by randomness would be a big step that a trader can and should take on their path towards profitability.
Here I want to pause, because in short I will talk about mathematics and statistics, but don't worry, I won't get into the intricacies of technical specifics. Instead, my aim is to explain a vast technical arsenal of key concepts in an intuitive and straightforward manner without using mathematical jargon, and hopefully provide you with the basic understanding that will allow you to perceive the market in a different way, in fact, in a more realistic and operable one.
Let's return to uncertainty, because this is where the key lies. Firstly, let me underscore a fact: the market is governed by unpredictability, in the sense that the future value of any stock asset is influenced by a multitude of factors and may exhibit ambivalent fluctuations. As a result, it's impossible to anticipate such future value with undisputed precision.
The stochastic nature of the future value of our favorite asset, which we strive so hard to predict today, is so pronounced that it impacts not only technical analysis but also more sophisticated tools, such as statistical time series analysis and artificial intelligence. Despite our best efforts, these methods often fall short, providing accurate forecasts only in certain cases, rather than universally reliable predictions across the board.
Accepting that we may be correct in some cases and incorrect in others is precisely where we can embrace uncertainty effectively. Recognizing that my analysis and decisions may be both right and wrong before entering the market is a significant step towards understanding the probabilistic nature of the market and alleviating the psychological pressure derived from the need to always be right.
Thus, embracing the undeniable probabilistic nature of the market allows me to perceive things differently. It frees me from the unrealistic need to always be right and introduces a fundamental concept: the notion of assigning a probability of success to each trade, rather than focusing solely on being right or wrong.
Here, the approach undergoes a radical shift. Instead of seeking that infallible technical indicator or that machine learning model that will predict tomorrow's price, I redirect my focus towards creating a trading system that tilts the probabilities in my favor. The goal is to ensure that the sum of favorable events exceeds the sum of unfavorable events.
And well, here's the good news you deserve if you've made it this far in the reading: you do not need to be a math wizard to be profitable, because any trading system (solid foundations) is a winning system, if it focuses not on its ability to correctly anticipate the future, but rather on creating an advantage from a probabilistic standpoint, whether in other contexts it tends to produce negative results.
Yes, just as you're reading it, even a simple system, let's say a crossover of two moving averages, is susceptible to being a winning system if we have the ability to bias the probabilities in our favor with its use.
The immediate question that arises is how to bias the probabilities in my favor. Fortunately, the answer is less complicated than it might initially seem. While there is a vast mathematical and statistical framework supporting everything, involving advanced techniques such as stochastic calculus, random functions, quadratic forms of Brownian motion, statistical inference, and so on, thankfully in practice, we don't need to delve into all of that.
On the contrary, a very basic understanding of concepts such as random walks, the normal distribution of returns, expected value, and variance is sufficient. These concepts all converge to provide nothing less than an average that indicates the positive contribution (or negative, in case of making mistakes) of each of our trades, considering the historically calculated probability of success.
In other words, a numerical representation of the potential positive or negative expected contribution of your next trade before you execute it. This removes uncertainty from the decision-making process and, ultimately, provides you with an invaluable tool for making informed decisions. On top of that, it becomes a powerful ally when dealing with the anxiety and emotional burden of trading, by providing a quantifiable measure that can be known before any action.
There is indeed an abundance of books, blogs, and videos available on the use of probabilities (expected value) in trading. While some sources provide valuable insights, unfortunately many lack a deep understanding of the mathematics behind it, resulting in explanations that are not as comprehensive as desired. However, these resources can still serve as a good starting point for traders looking to grasp the concept.
I plan to publish several follow-up parts to this post, where I'll delve into more specific details to offer actionable guidance on incorporating these concepts. However, time is a scarce asset for me, not because I spend long hours in front of the screen, but because I limit my work engagement as practice for maintaining happiness. Therefore, I must find the time to produce the continuation of this publication, but I will find it, because at this stage in my journey as a successful retail trader, I'd like to share knowledge for the benefit of the trading community.