Category: Trading Psychology

In this internet age, people always question the authority of anyone who tries to make a point. That’s especially true when the point of view one has is completely different from what the mainstream beliefs are. Since my beliefs are at odds with the mainstream trading education community, I guess it is time to set the record strict so that you can decide for yourself why you should listen to me on things related to trading.

Interviewing Myself

I have a habit of interviewing traders (if they allow me to) and collecting answers from them if they prefer the questionnaire format. That adds up to several boxes of records over the years. Many of these traders are good traders whose life long trading experience are extremely useful to newcomers. However, my trader friends also prefer not being put in the limelight, so to speak. I can only use the information myself as oppose to publishing volumes of trader interviews.

One of the questions I always ask these traders is, “How it all begin?”

I am going to answer that myself. Right here, right now.

How It All Began

Many people get into trading because they learn about it from a friend or saw on TV how traders are making big money. If you are interested in making money quickly, you will give trading a try. That’s not what happened to me at all.

When I was young, I have no interest in money making. I did not have what they call entrepreneur spirit. I was not interested in the financial markets. My hobbies were reading books, playing chess and making my own electronic devices.

My older brother was completely opposite. He liked creating his own businesses. He had a keen sense about the financial markets since he was young. He was the person who, at the first opportunity he found, became a floor trader in the Toronto Stock Exchange.

As a young trader, being Asian no less, in a place dominated by very aggressive western people, who would have imagine that he can last six months?

He went on to set a record there – as a first time newcomer, he not only survived the game for a full year but also made 4 times his trading capital by the end of the year. He was the hottest new guy.

From there the direction of my life took a sharp turn. My mother believed that my brother’s new found prosperity was the way to go. My brother thought that my intention to become a full time academic was stupid. Without any other option, I had to give trading a try.

So I followed my brother’s footstep to became a floor trader at the Toronto Stock Exchange.

I also set a record there – I was the youngest floor trader they have accepted thanks partly to my brother’s star power and partly for my perfect score in their exam which never happened before. I had an advantage over others in taking the exam – the hardest part of the exam was related to option pricing and strategies which was damn easy for someone who spent most of his life studying math and science.

That’s why I do not think like others who try to beat this game.

I did not even want to play this game, for God’s sake.

That’s how my trading career started some thirty years ago.

When I was in Europe last month, it was inevitable that I had to go out and socialize with my business associates. One such night we ended up going to a club with blackjack tables. One of my friends there knows very well I am an avid card counter and would like to see if I can beat the house. So there I was, sitting at one of the blackjack tables with couple hundreds of euro in chips to play the game.

The Game

I asked the dealer like how many decks are there and started playing.

I did my usual counting and noticed that the cards dealt out were collected and put back into the card dealing machine. I knew something was not right but I could not recall exactly what it was at the time, partly due to all night wine and dine activities.

Needless to say, I got cleaned out.

Whenever I tried to increase my bet size, thinking that it was the right time to do so, I encountered significant losses.

The chance for me to count wrong was very low. So low that I knew something did not add up. After I lost my last chips, I recalled exactly what I should have remembered before I started playing.

My associates asked me to keep on going so that I can win the money back. I told them I don’t want to do that because I was low on cash. In reality I had more than enough cash to keep going but I knew better not to. My friends even tried to pool together more cash for me to do it again because they probably feel bad that I lost money.

I ended up telling them the truth. I pointed out the machine on the table is something I cannot beat. Since I do not like playing blackjack to lose money, I told them we should do something else instead. They were quite upset and were afraid that I was unhappy. I had to assure and reassure them that I am perfectly alright.

I was secretly relieved that I did not need to grind at the table. I was happy because I knew this is the right decision.

The Machine

The issue I pointed out being the card dealing machine was not an excuse. This type of card dealing machines is designed to save time for the dealer, prevent cheating through manual card shuffling and, most important of all, to beat card counting. Cards are consistently redistributed back into the shoe hence the chance of these cards showing up again, say, five hands later, would be the same as all the other cards within the machine. There is no more distribution imbalance that a card counter can rely on. Thus, all card counting strategies based on the cards not being reused until next complete reshuffle would fail.

I should have walked away the moment I sit down at the table and noticed that the machine is in place for dealing cards. But I did not.

I suspect that my inability to recall the important fact about the card dealing machine is my commitment bias. I changed my Euros for chips. I sat down at the table. And most important of all, I have a crowd around me watching. My mind swing from being a careful pro into a casual player.

The Crowd

Emotions ran high when the crowd saw the dealer’s hand busted at the fourth and fifth card. Emotions ran even higher when someone on the table getting 21 on the fifth card.

Of course, emotions swing low when the dealer managed to clean the table with 20 or 21 even though many players had pretty strong hands.

Everyone has been participating in the game, with emotions invested into every card being dealt out.

I could see on the face of everyone that they were emotionally exhausted about an hour into the game.

Isn’t it interesting that we all know this is a game of chance yet we would cheer on wishing the dealer to go bust, or that some players were so anxious that it took them forever to decide whether to hit or to stand?

Maybe this is the very reason some people love gaming.

They enjoy the emotional rides and excitement that these games bring to them.

The Odds

Going a bit technical here, I will explain what the difference is between a normal Las Vegas style blackjack and the one I played with the card dealing machine.

In short, the Las Vegas style dealing will give the house a very slight edge over the players if the player is not counting cards, while exercising all normal cautions like not to hit when you cards already total at 20. With a good card counting strategy, a player can, at times, having a significant edge over the house when many high cards are left in the shoe leading to very uneven distribution.

For the card dealing machine I played, it actually offers the players a very minute edge, as long as the player is exercising the normal cautions. This means, if you have a big enough bank roll, you can win a small percentage of your capital as long as you are betting with the same size. Obviously, the goal of using these machines is not to beat the players. These machines are installed for the purpose of facilitating a service, to keep the guests entertained.

However, if a card counter is not aware of the design, the uneven betting based on the wrong projection of the existence of a bias distribution, will lead to unnecessary losses.

The Lesson

It is a good reminder to us, the professional traders, that we manage to make money in trading because we have good strategies and game plan in place. However, we have to be aware of the changes to the game itself that may completely alter the odds of our trading strategies. Keeping up with the environment change is very much part of our responsibility as a pro trader.

The latest round of buzz about AI (Artificial Intelligence), particularly the new meme Machine Learning, has triggered many talks on its applications in trading and investing. It is very interesting how it suddenly becomes the latest holy grail in trading. Is it really that much better? Not necessary.

What AI is Good at

AI is very good at picking up patterns from large amount of data based on the framework we have provided them. It also gives AI the advantage to find patterns that human often miss since we are born to identify visual anomalies only. In other words, AI can assist us to uncover useful information from large amount of data. From the game of chess or online games, to industrial design of cars and equipment, AI helps us resolve many difficult problems in much faster and efficient manner comparing to human based discovery approach.

When I use the word “pattern” above, it is not limited to visual or statistics based patterns. It can be patterns of rules that govern a dynamic system. For example, the machine learning process may discover that certain set of rules are failing to produce the expected results, and that they all belongs to the same category of underlying patterns in the data.

By applying this meta logical pattern on the rules, AI can develop new rules itself. This is the technological direction, namely self reprogramming and self refinement, that Elon Musk is so worried about. Think about an AI based program deployed to defend a country that has built-in self management rules to improve itself. What if one day the system produced a new rule that it is better to launch all the missiles to guarantee winning a war, or chose to delete a rule that emphasize on minimizing the casualties of civilians?

AI in Trading

AI has been applied to trading ever since it was introduced many years ago. The earlier approaches are mainly developed to capture patterns in price and related financial data (e.g. PE ratio) to make forecast on individual stock and markets. Later on we have seen successful trading models built for short term trading on indices using patterns recognized from large amount of data including price patterns and market breadth data. The concept behind the development of these models, however, are still very human centric. We were using AI to discover patterns and then we apply the patterns in our trading. In short, we decide what discoveries made by the computer are applied in our trading.

The latest round of AI application in trading, however, is taking on a different direction. Many professional traders and trading firms are now testing fully automated trading models that are managing themselves. What I mean is that human factor is reduced down to the initial feeding of data into the computer with an overall theme specification and subsequent risk management only. In short, we are teaching the computer to trade by themselves instead of teaching human to do the job because we prefer traders to have little or no emotion at all for better performance.

The advantage of these new approach to AI based trading does not stop there. Models will continue to evolve on their own, either in live or simulation environment (which human still have control). This helps proprietary trading firms tremendously with much better control over the consistency in performance.

Context Matters

It is obvious that AI is best fit for trading in short term environment as the amount of data to be processed can be too much for human to analyze. It is also clear that the AI models that self manage can pick up subtle changes in the data much faster than human can. This ability to teach itself to adapt to a changing environment can be a double-edged sword though.

For a changing environment, say, a news driven shock to the markets, can be very short term. Given enough historical examples feed to the AI systems, they will figure out a way to handle these situations. The catch is, however, that certain longer term environment change never repeats themselves, yet they produced all the major characteristic changes that affect the markets for years. As there is never enough historical data on these situations, AI cannot really learn from them nor can they incorporate safety measures to safe guard themselves properly when such tide turning events happen in the future.

In other words, the adaptive AI based trading systems are doing exactly opposite of what many classic (and successful) trading models do. Instead of exploiting one specific bias to extract profit from the market with money management strategies to protect the profits like the classic trading models, the new self learning AI systems keep tuning themselves to outsmart the markets. This approach is not that different from what we called routine re-optimization of deployed trading models. Since we do not know if the set of parameters we use on a trading model would perform best in the future, by optimizing the models based on a subset of the historical data, usually the most recent part, on a regular basis, it gives us a way to tune the model to better fit the current trading environment. The self learning AI systems basically does that themselves.

Human Factor Still Key to Success

Hence, it is important more than ever that the trainer / designer of an AI system to understand the various potential drivers in a market. There are things the AI system would never be able to learn or to adapt to. There are things the AI system should never adapt to. The boundaries necessary to make the AI system safe to trade have to be provided by human.

Seriously, everyone can train their generic AI toolbox to deploy trading models to trade real money. In fact, I am sure every model deployed has a pretty darn good historical performance. But, it is not how good a system perform that matters. As the old saying goes, “If you avoid the losers, the winners take care of themselves”. It is how the system react to adverse situations and not losing too much money in the process that really counts. Only those designers who are well aware of defensive money management principles would do this correctly right from the beginning.

The bottom line is clear – it is still the person behind the machine based trader that matters most.

KISS Still Shines

“Keep It Simple, Stupid!” believe it or not, still holds true even in this heavily bots populated trading environment.

As I explained many times over the years, with more bots trading, the markets evolved into something much more predictable in a very sarcastic sense. Yes, older style of trading no longer produces good performance. And yes again, many trading methods are neutralized by the existence of bots. However, new patterns emerges from the very existence of these bots because they all behave in a very similar way. AI systems are no different. Given the technology are all based on similar toolbox, and that the obvious patterns are picked up by the AI systems one way or another, it is likely the AI systems will all behaviour similarly and go after very similar biases identified by them. In aggregation, they produce consistent footprints just like any other market participants.

So it is not necessary to stay at the forefront of technology or employing the latest trading gadget to make money in the markets. It is your overall approach to the market that matters. KISS still shines in the current trading environment. I know many size traders still focus on a few simple trading setups to make their living. The existence of these smarter AI bots changes the characteristics of many markets in the smallest timeframes only.

A Common Misconception About Day Trading Models

Lots of people spend all their time to discover or fine tuning a strategy so that it trades so many times to give them stellar performance like 300% or even 500% return per year. That may work but it is also dangerous to put all money on such models.

As I explained before in last instalment of this series, it is much better to emulate a good day trader who has multiple trading setups for which each one offers its own independent risk reward profile. It is the combination of these trading setups that produce a balanced approach to trading. With the right combination of these strategies, you get the same spectacular performance with much lower risk of complete melt down in performance like the single strategy approach.

Here is also the main concern with AI based bot traders. Unless you have a way to dissect the trading approach, you do not know the risk profile of each individual decision made by the system. You just know, as a whole, the machine trader you have on hand somehow perform great on the historical data. But we know they their were trained on those data, of course they would perform well on those data. You cannot throw a evolved model back in time to see if they would do well by the same reason.

If you train an AI system with certain part of the historical data, keeping the model not adaptive, it is then just the same old machine assisted discovery method. If you let the system retrain itself from time to time with new data, it is similar to the re-optimization mentioned above with the drawback of not able to gauge the historical performance. I think you get the point – machine learning is not perfect.

Summary

AI based bot traders are sexy for many reasons but they are far from perfect. If you know nothing about the underlying data and its characteristics, using AI to speed up your research is definitely the future as we are going to amass a lot more data going forward. However, it is not going to do you any good if you are an amateur in trading hoping that you can simply train the machine to do the job for you. Your have to be a good trainer (not necessary good trader) to make your trading bot a good trader.

At this point, it should be quite clear where I stand on the subject. I use AI to assist my research. I also use AI based models to warn me of potential changes in the market dynamics. I like the technology as it saves me time on data mining and other tasks in research. But I do not deploy trading models that are based on AI only. I prefer the KISS approach because I need the transparency and consistency with the models so that they are much easier to manage. It is a matter of personal preference. Maybe I have paranoia on AI just like Musk.

There are two main approaches to trading for decades. One is discretionary trading and the other is mechanical trading since the rise of the personal computer era. Retail traders are often molded into one of the two camps and led to believe that one is superior to the other. This naive belief causes so much misery among the retail trading communities that it deserves a much better narrative to explain the subject.

Trading is a Trap to Lose Money for Majority of People

I have explained in so many writings including several series of articles for beginners to understand what it takes to learn to trade successfully from scratch. In short, majority of people attempting to learn to trade discretionarily will fail, either right from the beginning or eventually, because they have not corrected their internal belief system to handle trading from the proper perspective. There are many courses out there teaching people how to correct their belief system but it only works on those who are willing and determined to change themselves for greater success.

This leads to the appeal of mechanical trading for anyone who understand the obstacles with discretionary trading. After all, a mechanical system with the right edges should generate profits automatically, isn’t it?

It turns out trading with mechanical models takes the same type of belief system in the first place to achieve success consistently. It is just a different approach to the same pursuit for those who are more scientifically minded with personalities more open minded to accepting automation.

Basic Success in Discretionary Trading

In other words, knowledge is secondary in terms of achieving basic success in trading. What I mean is that if one is seeking for consistency in making money from trading for the long term, the best approach is to fix themselves first. Getting oneself ready for trading, or simply any other business or venture, is the same. Any basic concept in approaching the market with just a little edge will give the trader consistent profit over time, given the people has the right attitude and beliefs in life. Whether the trader is willing to accept what the market is offering based on specific approach to that market is a completely different question.

One thing we have to understand though, is that discretionary traders do not acquire exactly the same set of knowledge for a trading strategy as mechanical traders.

For example, a beginner learning to trade discretionarily is taught to buy pullback in an up trend. If the beginner is willing to focus on this one and only one idea, with full attention to figure out all the details of this single trading setup, mastery of this single technique will happen and consistent profit will follow. But some people just do not hold the belief that pullback setup works and until they change their attitude and embraces the concept 100%, they will never be able to trade the strategy with 100% consistency. It has nothing to do with vagueness.

Look at the skill of riding a bike to see why vagueness does not matter.

When you ride a bike, do you know at any moment exactly how much force you need to apply to each individual leg to get the bike moving?

Do you need to know the exact theory and details behind the fact that you can balance on the bike while it is moving?

You just know how to ride a bike because your brain is trained to handle the details for you by taking all the sensory inputs into account but only if you let go of the belief that it is impossible to ride a bike and believe 100% that you can do it too. Once you learned to ride a bike, even after years of not doing it, you can pick it up quickly again because your brain is wired to believe that you can do it already.

In short, you are programmed to react properly. This also explains why some people are better at discretionary trading. They are more adapted to learning from all their sensory inputs to form the basis of their acquired knowledge.

Basic Success in Mechanical Trading is Different

In a similar situation, when a beginner trader is taught to look for mechanical setup to trade a pullback, they have to look for things that are quantifiable that can be converted into rules that a computer can understand. Since a beginner trader has limited knowledge about the market, their research on how to quantify the pullback strategy will be limited by whatever knowledge they start with.

This approach works well with those who believe 100% that the rules they have discovered will deliver consistent profit over time. In other words, it is acceptance of the discovery and its past performance, disregarding how they come from or why they work, that is necessary to make the mechanical trader consistently profitable. It is hard to do, especial for those people who are actually more suitable with mechanical trading, because people who are more evidence driven and scientific minded are those who likely prefer high probability winning although what really matters is that the strategy discovered is consistently profitable with controlled risk.

Due to lack of complete sensory input like learning to trade discretionarily, mechanical trading strategies discovered by many traders are likely to have lower winning probability since they do not have access to better depth of trading knowledge. Being able to accept this lower probability of winning, is key to basic success in mechanical trading. In this aspect, the hurdle to trading success is very different for discretionary trader from mechanical trader.

Good Discretionary Trading Takes Only a Combination of Consistent Trading Strategies

To become a good discretionary trader, one has to learn to add trading strategies to their trading arsenal one at a time. Once the trader has master several trading strategies to complement each other in different market environment, the trader will perform many times better than a trader who mastered just one trading strategy. Many discretionary traders believe that it is their trading skills improved that leads to the exponential growth in performance . What really happened is that they are benefiting from the Law of Large Numbers.

By looking at a good discretionary trader from mechanical trading point of view, the performance of a good discretionary trader is a combination of several high probability winning strategies. Due to the increased frequency in trading and that the strategies are likely complementary to each other as the trader is adding strategies to handle different market environments, less drawdown is expected and so is consistency in profitability on, say, monthly basis.

In other words, it is not an overall improvement in trading skill per se. It is proper parallel combination of applying these individually profitable strategies that leads to better performance. Traders failing to realize this will suffer eventually as their egos take over their minds and ruin their futures as they hit the eventual obstacle of performance block.

The combination of multiple strategies does not require the trader to understand them from a higher level of clarity. Just like being able to ride a bike and eventually learned how to ride it to do difficult tricks, one does not need to understand exactly how the tricks work in terms of physics. Eventually, there will be tricks that no matter how hard one tries to do them, it seems like they are impossible to do. That’s the performance ceiling. One will not be able to overcome until after playing catch up to learn the science behind riding a bike so that one knows exactly what is required to accomplish the more complex bike tricks.

From this perspective, mechanical trading of multiple uncorrelated trading strategies can offer the trader much better consistency in performance because the mechanical trader does not have the burden of not knowing how to handle the potential conflicts among multiple strategies. All the mechanical trader has to do is to let all the trading models do their own thing. As long as the trading strategies are followed, the aggregated result in performance should be close to the expectations.

Thus good traders will have to eventually accept the fact that they can only do as much in terms of extracting profits from the market if their trading strategies are just a combination of techniques that they do not have deep understanding of. Relearn everything about the markets they trade is a risky business decision that everyone has to evaluate carefully.

Great Discretionary Trading Requires a Coherent Framework

Great discretionary traders are different from the good ones because they have a completely coherent framework in mind. All their trading strategies are derived from the framework hence there is no internal conflict whatsoever when they engage the market. In the minds of these great traders, everything is happening as they are supposed to be. Observing these traders trading, it feels like these traders know what will happen next in the market before things actually happen.

I am not saying these traders really can tell what will happen next in the markets. What really happens is that they know what is more likely to happen next with their deep understanding of the market anchored by their framework on how a market is supposed to function. There are quite a number of market theories that can help traders to think logically and interpret the information in a structured way. Notice that not all of these theories are functional and it is up to the trader to figure out which one actually works. Assuming a trader picking the right theoretical framework to learn from, it still takes the trader to commit fully to the framework and rewire the brain to think and analyze every aspect of the markets using such framework in order to benefit from this approach.

Great discretionary traders are often not the best performer when they just start out trading with their approach. That’s reasonable as a framework driven approach is never optimized to what is happening currently in the market. But eventually, as these traders are gaining experience in trading, they are the ones who will eventually perform better than the others because they do not suffer from being overloaded by trading strategies that have conflicting principles behind.

Great Discretionary Traders Are More Than Super Mechanical Trading Models

If a good discretionary trader is simply a combination of several well defined trading strategies, a great discretionary trader is a super trading model that is built on top of a complete price discovery framework. Using the phrase super trading model is really an understatement considering a discretionary trader has to develop the discipline to manage every trade with straight risk management, let alone handling the psychological challenges like emotional interference from losing and winning streaks. Above all, great discretionary traders also act as control of their trading models. When these great discretionary traders notice a change of market behaviour, they can formulate theories on what caused the changes based on their frameworks to adjust their trading strategies to work better in the changing environment.

Hence it is not that difficult to emulate a good trader using mechanical models provided that we figure out all the facts that are considered by the trader in making the trading decisions. However, to emulate a great trader, one has to resolve the issue of modelling at least part of the price discovery framework employed by the trader. This can be very difficult as the logic used by the trader can be more complex than some very complicated strategy games like go that are well known difficult computation problems.

As a summary, I do not see discretionary trading being all that different from mechanical trading. Overall, there are many similarities among successful traders in both camps as they have to overcome their egos to follow straight trading rules so that consistencies in performance can be achieved. On the other hand, the distinct requirements for each camp take a very different set of personalities to deal with the issues unique to those trading approaches in order to succeed. To the best of my knowledge, mechanical trading models at the present state are still not as good as the great discretionary traders of our time. By giving the mechanical traders ten more years, they may eventually develop trading models that can surpass the performance of the best discretionary traders in the world.

One of the themes I came across meeting people all around the world is that they think that it can be too late for them to learn to trade. Coming from that point of view, they ask for shortcuts to get trading success quickly. Thus their enormous interest in trading courses promising instant success and guarantee income from secret trading systems showing consistent performance, say certain amount of money every month. Is it really true that it can be too late to learn to trade properly?

It is Never Too Late to Learn to Trade

I have met people from all walks of life from all age groups who managed to get trading success. I know several traders who started to trade by the age of 60 years old and they managed to do pretty well in trading after several years of committed learning. In fact, it is usually a bad idea for young adults to go straight for a career in trading after graduating from school because they lack the normal work experience needed to develop good working habits like discipline and perseverance.

Given the modern age life span, it is not a surprise that we will live to 80 or 90 years old. Hence learning to trade properly and gaining success in trading by committing several years to acquire the knowledge and develop the necessary skills is a great investment. Yes, by 70 years old, it may not worth our time to take on this challenge. But if you are younger than that, the benefit of having the proper trading skill set in place will pay off handsomely for many years.

There is really no excuse for people at their 30s, 40s and 50s to avoid learning to trade. Yet, people keep saying it’s too late for them and they need a quick fix. I think the issue here is a combination of cultural misconception and psychological weaknesses.

Modern Day Career Path Has a Completely Different Time Schedule

Our world view of career path is shaped by the beliefs coming from our parents and grandparents. Those people at the age of 50s and 60s were taught to believe that they have to be established by the time they are at their 30s and by 40s they should be on track to a great career path or they will be stuck in life. And then retirement is near as their age approaches 60s. This mindset is completely messed up.

First, by taking good care of yourself, given the modern understanding of the human body, there is really no reason why we cannot live healthily by 80 years old with our body staying fit like we are 40s. The whole concept of retiring by the time we are at 60s was just part of the historical past. Planning your life around that concept nowadays will seriously side track your ability to live a meaningful life as all your attention is wasted on a finishing line that was drawn arbitrarily.

Second, the society we live in now do not bound people to one single career anymore. In different stage in life, many people switch career or even industry at their 30s and 40s with great success. Trading does not have to be a replacement path of the main career you are pursuing either. It can be complimentary as managing one’s wealth is no longer a task that we can put our trust in the financial industry.

Conquer Our Fear of Failure

When we have a reasonably established career path, it is difficult to take on trading knowing that it is a very difficult to master with very low chance of success. After all, just casual research on the internet will tell you that 90% of retail traders will fail. This psychological problem of not willing to deal with failures affects majority of people who are looking to improve their lives in all areas from health to financial success, not just with trading.

The fact is, many people were taught to think of failing to do something is the equivalent of themselves being failures. This thinking is plain wrong. Yet, we are often misled to think this way when we were young as we do not have proper guidance to separate our ego and our abilities. When we fail at doing or learning something, it is just that, nothing more.

For example, I may not be talented at drawing and that even though I tried very hard to learn to draw better, I know I will not be a great artist. The learning process to draw better is full of obstacles with failures all the way. This does not define me being a failure. It is just one area that I am not good at. Without trying, however, I will never be knowledgeable about drawing nor able to appreciate paintings at a higher level. I learn a lot about myself during the process of learning to draw. My drawings produced along the way are not good quality by any standard. But that does not define me being a bad person, or a failure, a very ambiguous term people often use when they cannot find something in their lives that they can be proud of.

Success in any field is the result of accumulating many failures. The most successful people in any field are likely the ones who encountered more failures than their peers. Only by being not fearful of failure and mentally prepared to handle failure as part of the process, will you be able to pick yourself up quickly after every fall. This better mentality in dealing with failures also help us master any craft faster with less emotional torment.

Accepting Our Ignorance

One interesting behaviour I often observed is the underestimation of the difficulties in learning something new. In trading, I have seen many people with success in their own fields often look at trading as something simple. Their perception mislead them into learning this supposedly completely new skill with the wrong approach. In short, they try to adapt the information on trading they are given, no matter how detail or complicated the materials are, into concepts they already have in mind, based on their past experiences in other fields.

This approach to learning only works if you are learning something that has a lot of similarities to something you have deep knowledge of. For example, if you already know a European language like Spanish, then learning German is not as hard. For those people whose background is in Asian language only, it will be much more difficult to learn German quickly even though both are languages for general communication.

But how do we know if we already have deep knowledge in something similar to what we are going to learn?

We don’t.

People in general assume they know because their brains tricked them into thinking that they have some ideas what they are learning. For many simple skills, you can be slightly better than average and you would already be able to utilize that proficiently to solve 90% of the problems requiring the particular skill set. Majority of the skills we acquire in life belongs to this category.

However, trading is one of those fields that in order to be successful you have to be part of the top 5%. This means taking it seriously and accepting our ignorance about trading is very important. This correct mindset will steer us in the right direction, making us willing to learn more carefully like we once were when learning to write while we are young. Being able to take extra care in learning everything in details helps us to build the proper foundation. In turn, it ensures us a better chance of success in trading.

Financial Freedom is a Reasonable Goal

As I explained in my more technical writing about trading, it is not striking it big quickly that matters in trading. It is all about consistencies and having a proper game plan. Once you become more consistent, your performance is just a function of the compound growth rate as you get to increase your trading size over time.

One cannot rush the learning process in trading. The mental development of a person in trading is as important as acquiring more knowledge about trading. There is no shortcut. Just better ways to focus your learning while not wasting time on misleading information.

From my experience working with many traders, once they “clicked”, it takes only 2 to 3 years to get them to produce decent profits putting them at par to top 10% income in their countries, provided that they are trading fulltime. For those who choose to keep trading as their side business of managing their savings, it takes about 3 to 5 years for them to produce enough profits to exceed their main income. Of course, everyone will follow their own pace so my observation can only act as a reference. So we are looking at doubling one’s income being a reasonable short term goal and gaining financial freedom as an achievable long term goal.

In summary, acquiring or mastering trading skill is not as remote as many people think. It often takes too long because people tend to approach it wrong as I pointed out the psychological challenges earlier in this article. If you look at trading serious enough and are willing to commit yourself to the learning process, I am sure it will be one of the best things you have ever invested your time and energy on.