Programmers & Coders Often Fail in Trading

Why Do Programmers and Coders Often Fail in Trading?

Programmers and coders often fail in trading because they look at the market like science. But the market is completely different from math and other sciences. The market is non-stationary, non-binary, and evolves all the time. You need “alpha skills”, not “coding skills”, to succeed in the markets.

Do software developers make better traders? Are programmers and coders perhaps even bad traders? We have been in contact with numerous traders over the years. Many of them have enormous technical skills far superior to our own. They start trading enthusiastically – often by making their own software and programs – but unfortunately, their optimism stops when they realize their technical skills don’t produce any profits.

Key Takeaways:

  • Programmers and coders often fail in trading because they mistakenly apply binary logic to markets, which are non-binary and evolve constantly.
  • Trading success requires “alpha skills” such as creativity, experience, and “street smartness” over mere coding skills.
  • Many programmers waste time creating trading programs and apps, ignoring available tools that are already optimized for trading.
  • The mindset and approach to trading are as important as technical skills, with a blend of street-smart intuition and creativity being crucial.
  • Coders might be better off financially sticking to programming jobs, given the high demand and good salaries in the tech industry.

Programmers and coders believe the market is binary

Programming is based on binary logic: 0 or 1 – true or false.

Unfortunately, you can’t transfer this logic to the financial markets. The market doesn’t operate like this. The markets are non-stationary, evolve, and change all the time. Moreover, prices are often set by irrational participants. It’s a chaotic place that overreacts frequently.

Markets are not based on logic – often news makes the price counterintuitive.

We believe programmers/coders have it completely backward. You need to learn how to trade before you’ll ever have any use of any coding skills.

Trading knowledge trumps coding by a wide margin

We believe it boils down to this: Without the correct mindset and creativity, it doesn’t matter what technical skills you have. Knowledge about trading trumps coding by a mile. So-called “quants” are completely worthless without some street smartness.

For some reason, many programmers believe that their coding skills will make them successful in trading. But the world is full of quants, and just a small percentage are successful.

It takes time to build knowledge about trading. We are talking about years, even decades, while coding can be learned by logic in a much shorter period of time.

Traders better be long on experience and creativity

Youth doesn’t guarantee creativity, and coding knowledge doesn’t result in alpha or profits.

Trading requires an open mindset, creativity, and a huge degree of “street smartness”. Coding doesn’t hand you these assets. Passion beats expertise and complexity.

Free education is abundant, however, but the desire to learn might be scarce.

Coders and programmers waste time on programs and apps

One thing we have noted is that independent “coder traders” seem to have one thing in common: They spend a lot of time developing programs, apps, scanning functionality, etc.

They believe their skills in coding and logic will make them money.

Let’s give you one example: One programmer wanted to make his own trading platform and subsequently spent over a year coding a trading platform with an API bridge to his broker.

What is he trying to accomplish? For example, Amibroker and Tradestation, the programs we use for both backtesting and trading, is a cumulative package of over two decades of knowledge and feedback from thousands of traders. Why reinvent the wheel and make your own software/platform?

What these programs don’t offer compared to your own proprietary program is beyond us. The ready-made options in the market are almost endless. Why invest your time by reinventing the wheel?

Traders or programmers – who make the most money?

That being said, programmers, in general, probably make more money than traders. If you’re a good programmer you are more likely to be much better off by sticking to a regular job. Coders are in demand and salaries are good.

Programmers get paid a monthly salary while the great majority of traders only are prey for bigger traders further up in the food chain.

Trading and coding are professions that are completely different: it’s a choice between scalable vs non-scalable professions.

Trading is highly scalable, ie. if you are successful you can quickly scale it and make millions. The downside is that very few traders make it big.

Python and trading

We are not experts in Python, but plenty of traders want to use Python. We are at a loss of why but we assume the big community is one of the main reasons. (We have written about Python Strategy and backtesting.)

However, we struggle to understand why you would spend time in writing code for absolutely everything when you can purchase a software that has already made these functions available to you. Yes, the software costs money but in our opinion it’s well worth it.

One of these software platforms is Amibroker – you might find our post Amibroker vs Tradestation worthwile.

Why coders might be bad traders – not being street-smart

You want to be a street smart trader: being street smart is much more important than being book smart. Why is being street smart more important than being book smart?

Trading is much about common sense and heuristics. Street smarts beat book smarts in trading because street smarts don’t make it more complicated than necessary. Occam’s Razor states that the simplest answer is normally the best answer and street smarts use heuristics and Occam’s Razor all the time.

Yes, I know it works in practice, but does it work in theory?

Rory Sutherland – Alchemy

We believe street smart traders stand a better chance of succeeding in the markets than book smarts, although some elements from both are probably optimal.


Because quant trading requires creativity, innovation, and experience, much more so than technical or academic skills. Technical skills don’t automatically result in alpha. Likewise, youth doesn’t guarantee creativity, flexibility, or innovation.

The market is not a mathematical equation to solve

The market is not a mathematical equation to solve, well one part of trading success is an equation to solve (backtesting) but a huge portion is not and that is where they go wrong. They cannot figure out why the market didn’t do exactly what it has done in the last 20 years this pattern turned up. Why did it turn out different this time?

Fat Tony and Dr. John by Nassim Nicholas Taleb

Nassim Nicholas Taleb has its fans and enemies (we are mostly fans and highly intrigued by his books which we strongly recommend). In one of his books, we believe it is The Black Swan, Taleb mentions a toss coin involving Fat Tony from Brooklyn and Dr. John, a rational and logical academic:

Fat Tony is loud, perhaps a bit careless, shrewd, and lives by heuristics and his wits. He is a typical street smart.

Opposite, Dr. John is careful, detail-oriented, meticulous, logical, rational, and very intelligent. Dr. John is a typical example of someone who is book smart.

Both Fat Tony and Dr. John make mistakes, but usually very different ones as will be shown below.

Taleb uses a coin toss to separate the distinction between the two gentlemen’s mindsets:

Assume that a coin is fair, i.e., has an equal probability of coming up heads or tails when flipped. I flip it ninety-nine times and get heads each time. What are the odds of my getting tails on my next throw?

Dr. John answers, of course, that this is simple and trivial. The correct answer is 50% as each toss is independent of the last one. What else could it be?

Fat Tony begs to differ: No way it’s 50-50 chance of heads or tails, the game is rigged. At best there is a 1% chance of getting tails on the next throw as the coin is loaded!

Street smart vs. book smart traders

The academic environment puts a lot of emphasis on books and classes, while “street smartness” only can be developed by trial and error in the real world (common sense prevails).

We can argue that the two mindsets differ significantly in how they operate and work. The academic world is based on structure, logic, and rationality.

However, the real world is often light-years away from academic theories. The world is not rational, bell-curved, or structured. It’s complex and difficult to understand. Models can’t capture how the world operates. The financial markets are non-stationary and correlations change all the time.

Theories can’t explain behavior, there is risk asymmetry, information overload, and experience often trumps what you learned in an organized classroom.

Success in the street is something different than success in the academic world. Is high IQ an advantage when you are setting up a new venture? A new venture is always based on risk and incomplete information. It’s a lot about gut feel. Street smarts often rely on their guts and intuitions to guide them, while book smarts rely on surveys and rational explanations.

Trading is all about incomplete information and making decisions on an uncertain future. This brings us to Occam’s Razor:

Trading and Occam’s Razor

William of Ockham was a monk who lived in the 1200s. He stated that problem-solving should be simple and done with as few variables as possible. His conclusions have since become what is called Occam’s Razor:

The simplest explanation is usually the best one. Other things being equal, simpler explanations are generally better than more complex ones.

We should always select the hypotheses with the fewest assumptions!

This applies to trading: You should always use simple strategies with the fewest variables and assumptions.

We believe street smarts are more likely to use Occam’s Razor and heuristics in decision-making, while book smarts tend to dig into their models – often to no avail because the market is non-stationary.

Thus, street smarts beat book smarts in trading. Of course, the optimal would be to have a little of both worlds.

To sum up: Why programmers and coders are bad traders

Do the best traders possess great technical skills or “alpha” skills”? By alpha skills we, of course, consider their trading skills and how to make money in the market.

“Alpha skills” are much more important than coding skills.

Why might programmers be considered bad traders?

Programmers can often be considered bad traders because they often approach the market with a scientific mindset, which may not align with the dynamic nature of financial markets. Programmers face translating binary logic used in programming to the non-binary, non-stationary, and frequently irrational nature of financial markets.

Can coding skills alone ensure success in trading?

No, coding skills can’t alone ensure success in trading. On the contrary, coders often lack an understanding of the market.

What is the significance of a trading mindset?

A good trading mindset mix coding with street-smartness. A good trader needs “alpha skills,” including trading skills and the ability to generate profits, as opposed to relying solely on coding proficiency.

How long does it take to build knowledge about trading, and why is it a long-term process?

It takes years to build knowledge about trading. It’s all about experience, and you don’t get experience after just a few months.

Why is being street smart more important than being book smart in trading?

Being street smart is more important than being book smart in trading because street smarts simplify decision-making using heuristics and Occam’s Razor, adhering to the principle that the simplest answer is often the best. In contrast, book smarts might overcomplicate matters with theoretical approaches, potentially deviating from practical, common-sense solutions.

How does street smart trading differ from book smart trading?

Street smart trading differs from book smart trading because street smart trading involves learning through real-world trial and error, emphasizing practical, common sense, and gut instincts.

On the other hand, book smart trading is often associated with academic theories, logic, and rationality, which may not always align with the dynamic and non-stationary nature of financial markets.

What role does creativity play in quant trading?

Creativity plays an important role in quant trading because quantitative trading requires technical skills, creativity, innovation, and experience. The content suggests that these qualities are more pivotal for success in quant trading than relying solely on technical or academic proficiency.

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