Better Trader vs More Profitable Trader?

Trader's Mindset

Apr 01

Most traders think that becoming better at trading will lead to greater profits. However, as I have learned about myself that being among the “best” in predicting and calling markets does not necessarily lead to great profits. I have, also, started to recognize that being the best trader does not necessarily lead to the greatest profits. Read on to learn why and how one might pursue both goals.

Many traders focus on getting better at trading. However, it may not be the path to success. Let me share a story to explain why. I am a professional software engineer/developer. I developed and sold my first computer program when I was around 8 years old and by 12 I was leading a group of 19 to 20 year old developers. Yet, by the time I turned 19 I was struggling to even get a job in the field!

At around that time, one of my best friends and mentors was a prominent scientist and statistician. While looking back I am not sure whether he intended to leave the impression or if it was of my own creation– regardless, my conversations with him around job prospects always left me with the impression that I needed to get better at programming. As such, I was working constantly on becoming the best developer possible. But, I was not landing any jobs.

Finally, the big turning point came during an interview when I recognized the interviewer did not know anything about software development. It was at that point that I started to think more about how people make decisions. It lead to a simple recognition that I was already way better than many professionals working in the field. In fact, I would later learn that I was probably already as good as many professionals a decade earlier. What I had missed was the importance of the credentials and identifying the opportunity in the market.

Long story, short– I reframed my problem as “not being a good enough developer” to “lacking the skills and fit that were in highest demand”. Instead of focusing on mastering my discipline, I focused on the market opportunity and how well my skills meshed with that opportunity. That change in focus eventually led to my having finding greater success in my field– including passing all the managerial and engineering requirements for an engineering job as Microsoft (external circumstances actually prevented me from taking the job).

Going back to trading, some of the better struggling traders out there may be similar to myself when I was the programmer working on my craft but ignoring the market opportunity such as the skills that were actually in-demand. Such a trader may have finely developed capabilities but skills that are no longer well-suited to the current opportunity in the market or they may only be trading the most difficult markets.

On the other hand, it is very likely that comparably lesser skilled traders, who are superb at identifying the greatest market opportunity could be making significant profits in the same environment.

The question this topic presents is really about whether a trader focus on becoming better vs. finding the best opportunities, i.e. easiest trades? I do not think this is an easy question to “answer” because if it were there would be more highly profitable professional traders– and we know there are not many of them!

If you are new to trading, you should probably focus first more on skill development and basic competency in a narrow niche. Because one should be able to develop what it is like to do well– to know that feeling– and that is more difficult to do if one is scattershot and never sticking with anything for any length of time. In fact, we have all heard of stories of traders who get into trouble just because they venture into new products and markets that they do not understand.

Yet, on the other hand, among the traders who share their results and are the highest earning traders I have noticed that most tend to be more “market oriented” vs “skill oriented”. One argument for why this might be the case are that markets are just very efficient: that makes it very difficult to both obtain and maintain skill level that far exceeds the other traders. And, yet, this is what one must do to even produce meager profits unless one finds or lucks out into the profitable and easy to trade markets– or makes it their goal and focus on lucking out into easy trades.

One tactical approach toward branching out is to seek out and connect with other professional and serious traders. It reminds me, in the “old days”, I used to always say I could turn any method to gold regardless of whether it really worked for the one teaching it. And, that is the kind of winning attitude that can lead to new mastery.

Another approach is to structure ones trading as “systems” even for the discretionary aspects. Each “system” will have its own risk allocation and objectives. One can allocate or dedicate, for example, a blend of their trading toward different methodologies. A trader might pursue a 50% systematic and 50% discretionary allocation. Within those allocation, there can be multiple systems or discretionary projects. This can be especially relevant for scalping futures where taking a few trades, hitting a profit objective, and shutting down often leads to better results. Such a trader instead of shutting down their trading, can shut down that particular “program” while still working on other opportunities.

In summary, the most profitable trading is likely the result of a balance between identifying emerging opportunity and developing specialization and consistency of specific method. The trader who is too aggressive in seeking out new products to trade may be more likely to find trouble. On the other hand, a trader who is unwilling to adapt may simply be struggling because the opportunity landscape has shifted.

About the Author

The author is passionate about markets. He has developed top ranked futures strategies. His core focus is (1) applying machine learning and developing systematic strategies, and (2) solving the toughest problems of discretionary trading by applying quantitative tools, machine learning, and performance discipline. You can contact the author at