My Journey to Fully Automate My Trading: AI vs. KISS

Thinker

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.

Better Time Management, Back to Content Curation and the Big Secret Projects

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Over the past several weeks, I have reorganized many things that I do into tasks delegated to either my team or contracted outside companies. The goal is to further reduce the amount of time I spend on managing the websites and day to day responsibilities in running these sites and services. I think I have achieve the milestone of taking back my time finally where I can focus more on what I deem most important going forward.

Part of this saved time will allow me to restart the content curation for Essence of Trading. Many of you enjoy the videos and product reviews I did in the past. They are precious resources of all traders and especially true for beginner traders. Now that I have some time on hand, I will be able to add new content and finding ways to better organize the site for future expansion. I am doing this also because of its practical purpose. Seriously, I don’t think I can ever write enough on the subject of trading and managing one’s trading business. Having the site dedicated to providing useful information for traders makes it much easier for me to point the aspiring traders to a centralized resource.

Here is the first new video for a long time.

This gets me thinking. Maybe the academia links I used to provide in the Daytradingbias user forum should be moved here too. After all, those are very valuable trading related research too. Will see what I am going to do with this soon.

Many readers and friends have been asking why there has been nearly no new posts on DaytradingBias but mainly the monthly newsletter and special updates. Well, I am not lazy and let the site goes autonomous. What happened is something quite interesting that has taken a life on its own.

I was writing a whole set of articles on trading Emini / SPY and forex some two years ago. And things were going very well. They were written with focus around two main themes – fully mechanical trading models based on a framework and long term consistency in trading performance. One way or another, as the work keep expanding, the articles turned into two organized projects that is way beyond just articles to be published on the site.

Part of this project is now in experiment for live trading which formed the foundation of my re-organized trading service for my clients. This firm focuses on providing long term stable return that is built on short term consistency in trading performance. I am very excited with the potential.

These two projects are still under development. Most likely I will release them in some form of training course or webinar. Lots of work still before I can release them but I know they will change the landscape in trading training forever.

Trading Product Reviews Have a New Home

The moving of the trading product reviews from DaytradingBias.com to EssenceofTrading.com is now completed. It took a while because the rating system has to be replaced and the formatting of the posts have to be manually revised. Anyway it is now done so we are going to proceed with the next step of the revision process.

Major changes to the front page will be next as we remove all the sections there that are retired from the site. The clean up has been a slow and painful process since the site was built some 10 years ago and has been evolving on the same older platform since. Upgrading the site into something more mobile friend should improve the overall usability going forward.

For more advanced searching options on the trading product reviews, they will be addressed separately.

Feeling Stupid

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We were working on a computer with Multicharts to test our trading models on a live trading account this morning. But we were stuck at the very first step. We just couldn’t get the damn thing to connect to CQG for some mysterious reason. My team freaked out as that computer was completely clean installed for just this purpose. And it was working perfectly several months ago. Once we have it working we never look at it again until now.

So WTF gone wrong?

I was told that it was not working earlier in the morning so I simply asked my team to figure it out. I thought it must be something trivial and told them so.

The first thing they tried was looking for help. My team talked to technical support with the brokerage. They recommended us to turn off the firewall, opening ports with our routers and even turning off our anti-virus program. All things were done. Nothing helped.

My team were so desperate that they literally tweaked everything they could before talking to me again that they could not fix the problem.

I then joined them walking through everything they had done so far.

Something did not feel right though … and I popped the question,

“Is everything up-to-date?”

Shockingly, that damn Multicharts installed on the computer was on version 9.1 BETA.

I asked my team to check with the brokerage again to make sure that version still works. Of course, it is not and the currently supported version is version 10. My team waited anxiously over the next few moments for the download to complete and rushed to do the installation.

Voila! Problem solved.

What a reminder of overthinking and missing the most basic things by a group of accomplished programmers and engineers. Not just them, same goes for the support with the brokerage.

If I were the first person handling the situation, I would probably do the same whole routines of messing with the computer and the network. Lucky me that I was the one who sit out of the diagnosis process and got to join them later with a fresh look. Otherwise we would still be struggling at this point.

At the end, everyone has a laugh though.

Site Revision Progress

This week we have completed the move of one set of articles from DaytradingBias.com into a separate website, Essence of Trading. Obviously, the site is for the publishing of the article series bearing the same name. I expected to write more articles for the site whenever I find the right topic.

The original Essence of Trading articles are now redirected to the new site to avoid duplication. So don’t be alerted that you are redirected there. In the meantime, I have the tedious task of reviewing and editing the articles on the new site to make sure they have the correct formatting, etc.

In the future, I will invite other successful professional traders to pen articles for Essence of Trading. Many of my trader friends are not the type who enjoy the spotlight hence don’t hold me responsible when I come up empty handed on this pursuit.

More changes are coming to DaytradingBias.com as we are streamlining the design to prepare for the launch of the new real-time trading signals and trading models.

I will keep you all posted.

Have a nice weekend all!

Madness with Trading Platform Differences

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A week into testing various trading platforms on live data feed gave my team a nice little surprise. It turns out, the customization around the major retail trading platforms is a lot more work than we thought. This affects not only the indicators (minor issues) but also backtesting results (major issues).

For major retail trading platforms, I am referring to, well, the ones that majority of retail traders are using. So, that includes Tradestation, MultiChart, NinjaTrader, eSignal and MetaTrader. These platforms are the ones I get to open brokerage accounts to test them directly with live data from the brokerages. It turns out, even the minute bars on forex data are so different that we cannot even believe that we are looking at the same symbols in real-time. For other data like Emini S&P, the differences is minimal in terms of real-time streaming but the way how some of the bars are constructed definitely affect decision making from platform to platform.

I lived through such nightmare decades ago when I was switching my trading platform. I did not expect that the same issue still exist today. Maybe I am asking for too much?!

This is a very interesting experience for me but I cam imagine how frustrated many retail traders can be when they switch from one platform to another as they switch from one brokerage to another.

As we grind along the process, I learned that for even a simple indicator like the one for charting STOPD levels will have to be implemented in ways completely different from one platform to another. In long run, this will be nightmare scenario for maintenance of the more complicated indicators and trading systems across multiple platforms. A simple wish to provide cross platform toolsets is now turning into something a lot more complicated.

A challenge that deserves a place in my weekly rant, indeed.

Reviving NeoTicker Blog Site and Updates on Other Projects

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Within several weeks, I am optimistic that the NeoTicker blog site will be restored. The site was hacked through exploits in the older version of WordPress which led to massive email spamming coming off the site. I made an agreement with NeoTicker’s company to oversee the restoration project. So far things are progressing slowly but it will be done very soon. After all, many of the articles I wrote on trading are posted there. It is a valuable resource for not just NeoTicker users but the whole trading community.

After very long deliberation with my team working on the real time trading signals for Emini and Forex, a surprise decision is made. Against my personal prejudice, I will delivery the trading performance reports in Tradestation format. In other words, at least some of my trading models will be backtested and tracked with Tradestation. People who know me probably know why NeoTicker existed in the first place and it was not based on a good experience with using Tradestation.

This also implies that I will offer my indicators and trading code in Tradestation format, in addition to the other ones already supported.

For the ebook Art of Chart Reading, I am waiting for the edited version on the remaining chapters. From there I will have a lot of reading to do to finalize the project. This is going to make my busy schedule even more busy.

For many of you waiting for so long for my forex research and courses, they are progressing slowly. Unlike the web articles, this time they are done in a very different fashion. As I mentioned before, it is now time for me to produce the much more sophisticated materials.

The amount of time and effort necessary to produce a book length course on trading models is exponentially longer than having each chapter being independent article like the ones I wrote for daytradingbias. On this aspect, I totally underestimated the commitment necessary hence slowing everything down so much. Luckily, I am not those people who give up easily. I can see light at the end of the tunnel at this point.

Enough babbling. Back to work.

Belated Happy Easter!

My Journey to Fully Automate My Trading: Understanding Discretionary Trading

Strategy

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.

It’s Never Too Late to Learn to Trade

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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.

My Journey to Fully Automate My Trading: The Commitment

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I talked about fully automating my trading for many years yet I could not stop myself from staying in front of the screen most of the time. This year, my new year resolution is to commit to the process of converting whatever I am doing in trading to a fully automated process. I know it is going to be a challenge for a discretionary trader who has been trading for better half of my life. I also know that the process itself can be a very rewarding experience. After all, I have not taken on a challenge this big for a long time.

A Bit About Myself and My Trading

In case you are not my long term readers or members of my website daytradingbias.com, it can be very confusing of what I am talking about. Here is a proper introduction of myself.

I have been trading for more than two decades (getting close to three now) professionally. I started out trading as a floor trader in a stock exchange trading stocks and stock options. I moved on to trading commodities and index futures. I manage other people’s money and also act as advisor to very affluent families on their high-risk portion of their funds. There were good times and bad times with my trading over my long trading career. Overall I manage to do pretty well and it has been a life enriching experience.

Over the years, my trading style has changed a lot. Although I started out trading 100% discretionarily, my current trading is a mix of mechanical trading on certain markets while engaging the other markets I have very specific routines and rules I follow strictly. Hence I am no newbie in mechanical trading. I just do not want to automate my main markets, the index futures, probably because of psychological reasons.

What Pushed Me to Take on this Challenge

I have a tough ride in my personal life over the past few years. Time became a very precious resource as I have to strike a balance between taking care of my loved one and my professional obligations of managing my clients’ money. During that time, I researched and refined my trading style so that it is more streamline and robust such that my emotion component would play a much lesser row in affecting my performance.

It turns out, my effort in reducing my time in front of the screen did not reduce my trading performance. It actually improved my trading performance significantly. I would not say the outcome is a result of those clichés like “less is more” bullshit. I think it was the process of objective reflection and evaluation of what I did that gave me clarity in reducing the clutters in both the actual rules of engagement in my trading plan and the beliefs I held for years about the markets which I never questioned until then.

So here I am, equipped with everything I have got, including time to spare at this point. I have no excuse not to complete the journey. The experience and knowledge gained from the process alone worth giving this a shot with everything I got. If the goal of fully automating my trading is partially successful, I gain even more time to take on even more important tasks in the future. There is really no downside to this challenge.

In other words, I have no excuse not to make it happen, now.

What’s Next

There are many things to get done in preparation phase for this project. It takes time to get these tasks completed before I can move onto the next phase of the project. Since I am not in a rush to make this happens overnight, I will take my time to complete these tasks carefully.

Throughout this project, I will document what I do so that all of you will learn something about the process of converting a discretionary trading method into fully automated trading. I am documenting my journey also for the purpose of holding myself accountable. This is my way to push myself to commit to the project no matter what the outcome is.

Life is worth living if it is a meaningful one. Finding new challenges to overcome is one way to make life more fulfilling. I find a serious challenge this time and I am very excited.