Day Trading and the Programming Trap
Many retail traders want to give day trading a try because, aside from a number of other factors, they are pretty good at working with computers. This group of traders usually has a hard science background like engineering, computer science, and other disciplines that require a certain level of proficiency in programming. In their normal life, it’s a pretty easy task for them to tackle anything that requires a certain level of computing proficiency. Trading, however, is a completely different story. In fact, these scientifically minded people are usually the ones who perform the worst when it comes to trading or investing in general.
Starting with the Wrong Foot
People with a technical background characterized by their ability in computer programming tend to be solution-oriented. They see problems and try to solve these problems with solutions. However, when it comes to day trading or trading in general, such a mindset can easily lead them to one of two paths of failure.
The first path is usually taken by those who are pretty smart relative to their peers. They overestimate their ability after casually reading online about day trading, or maybe they buy some books and decide that they are good enough to get started. They quickly jump into the game and start to trade. These people will fall into the same trap like the others, but they are often the ones who refuse to accept their failures. As a result, they lose a lot more money than the others.
What they fail to realize is that their belief about the simplicity of trading made it easy for them to start trading but also stopped them from thinking clearly about what is really required to become successful in trading. As I explained before, all those books out there will not help because none of them have real working examples of consistently profitable trading strategies.
The more you read those books, the more likely you will develop some illogical and messy beliefs about trading.
The second path is the one usually taken by the exceptionally smart people. They see the risk of trading but are determined to beat the markets nonetheless. They learn to write indicators and create their own trading strategies. They spend hundreds to thousands of hours seeking the trading edge mentioned on the internet and in books, but the trading strategies they thought they had “figured out” never really work as well as they expected.
This second group of people is failed by their background. Their solution-oriented mind steers them into working on trading edges and strategies that don’t really exist. They thought they know what they are doing, but they do not. They fail because they do not really think with a probabilistic mindset. They are striving for perfection, as engineering solutions are always done with that in mind. Accepting a 90% winning rate in a trading strategy is just too uncomfortable for them. Anything less “reliable” is always deemed not good enough and must be fixed.
Blame the Tools
Today’s trading platforms are built with 99% of their features to appeal to those who have no idea what they are doing. As an analogy, the trading platforms for retail traders are more like slot machines in casinos than professional tools built for robust trading.
One can find visually appealing customization and fancy features that are more distractions than practical functions a trader needs.
So you must think that at least some of these platforms have decent backtesting and optimization tools, right?
In my experience, these are the two most important tools for our trading education. After so many years of improvement since the 1980s when Omega Research first introduced System Writer for backtesting, aren’t we supposed to have something that is way more useful now than before?
The painful answer is no. Due to lack of demand for the really useful features, these two essential trading tools are not any better than they were 10 years ago. None of the most common platforms we have nowadays can help a trader educate themselves efficiently.
This is actually a very good thing, though. Consider all the other traders who do not know what must be done to learn trading quickly and effectively. You have this advantage once you learn how to do it right. The weaknesses of these two essential functions on the major trading platforms become a barrier for entry. The majority of people just cannot figure out how to utilize these tools correctly.
If you find that you have trouble learning trading strategies, don’t worry—you are not at a disadvantage against those “smart asses.” They have their own problems that mess with their minds, and many of them are getting nowhere even with a head start. There is no need to envy their prowess in programming, because even just a moderate proficiency in coding your trading strategies will be enough.
It is even more important that you learn to accept the fact that trading is a game of incomplete information, just like poker. It is much easier for normal people who are not engineering-minded to accept uncertainty. Several famous poker world champions, both men and women, are psychologists who adapted their more flexible probabilistic worldview to playing poker with great success.
The trick these poker champions used is equally applicable for traders. These poker champions trained their minds to accept the fact that there is no such thing as making the best decision when the information you have is incomplete. The best decision that you can come make does not translate into giving you the best outcome with certainty.
In fact, action taken based on your decision has no causal relationship with the outcome at all. What you do know, however, is that by taking the same action and given the same scenario, you would come out ahead on average over the long term. In other words, accepting the best practice and ignoring the individual outcomes is the real key for anyone to master trading. But how do you achieve that? By studying the historical behaviours of your day trading strategies in great detail, just like the professional poker players trains themselves on hard data, not guesswork.
Part of the A Smarter Way to Learn Day Trading E-Mini S&P 500 series