Cause and Effect: Thinking Differently for Traders and Investors By, D. R. Barton, Jr.

Barton TT1When I was studying and training to get my degree in chemical engineering, the process of decision making was quite “yes or no”. Learn the rules of the physical world and then apply them. Learn how molecules combine and separate. Learn how mass and energy get transferred from place to place. Learn what is economical and what is not. And along the way, learn how to study hard and get a good passing grade—the higher the grade the better your job choices.

However, once I was out of school and practicing engineering in the real world, things weren’t always so clear-cut. Outside influences often complicated things. The world of rote “yes and no” answers became a world with many shades of grey. In a pristine and controlled lab environment (like back at school), molecules always combined the same way. But in the real world, contaminants could get in the system and reduce yields. Temperature gradients could change reaction conditions from one part of the pipe or vessel to another. And the combinations of unexpected or unforeseen conditions could even create new and undesirable products altogether.

Equipment that was rated at “x” horsepower would always seem to run a little less efficiently because some field condition (normal wear, extra bends and turns, fluctuating temperature and humidity) would strip away performance.

In the end, the best process and field engineers were those who could deal most effectively with problems and conditions not found in the textbook. And it will come as no surprise to most that raw intelligence was not directly correlated to success on the floor of a chemical plant. There was a certain savviness or, what my dad would call, “horse sense” about the best engineers.

And I have found a very similar quality in the best traders and investors I’ve gotten to know. They don’t have to be the most book-smart folks (though a few are), but they have a certain grounded grasp of the big picture that allows them to adapt, correct and continue with a self-assured ease.

This group of characteristics that turns the average thinker into someone with good common sense or “street smarts” is somewhat difficult to sum up in a few sentences. But let’s look at some of these concepts—or decision-making loops—that may be most easily modeled.

Two Minds Vector 1

Trading Is Not Engineering or Accounting

Before we jump into some key decision-making characteristics, let’s be clear on the differences between the learning paths for trading and the path for traditional knowledge-based professions like engineering or accounting.

I’ve often heard professional traders lament that those desiring to learn their craft and do what they do see a few mouse clicks and some fairly elementary math and assume that they, too, can be consistently successful traders and investors right away. Some pro traders will respond to this sentiment with a saying like, “A highly paid accountant or lawyer had to study for years before getting compensated handsomely. Why would you expect to get paid like me after studying just a couple of weeks or months?”

And while part of that thought process is correct (the fact that there are knowledge-based aspects to both trading and accounting), there is also a major fallacy in the argument.

For traditional university education-based professions, acquiring and demonstrating minimal proficiency in the basic knowledge set needed for engineering or accounting or law or medicine will lead to a well-paid position for the vast majority of participants. Not so for traders.

In this regard, the learning path for a trader is more like that of a professional poker player. Demonstrating knowledge and proficiency in the basic skills gets you a seat at the table. But it doesn’t assure you that you’ll make any money. And while the poker-trader analogy isn’t perfect, those two paths are much more related than those of an accountant and a trader.

Let’s look at one key area that makes trading very different from accounting or engineering:

In search of certainty or “What happens when you do everything right and it still turns out wrong?” Doctors and engineers (and most professions) live in a cause-and-effect world. If you do “A” then a very high percentage of the time, “B” will follow. There are notable exceptions (when a treatment doesn’t work or a product line gets contaminated) but by and large if you do the correct action, you get the correct result.

Not so in trading. Perhaps the largest mental disconnect between most people’s classical education and the tool set required for trading is this ability to deal with uncertain outcomes. A trader can have the perfect set-up and entry, execute everything perfectly and still have the trade result in a loss.

The biggest mental problem with this loop is not the physical loss of money after doing things right. It’s the seeming disconnect between cause and effect.

If we do things exactly right and still only get the desired result 60% of the time (or 50% or even 40% of the time in long-term trend following systems), our cause-and-effect-oriented minds can easily jump to damaging conclusions. Since cause and effect seem only causally related:

  • The rules really aren’t good and don’t serve me.
  • I no longer need to follow the rules exactly, or at all.
  • I can at least tweak the rules to feel like I have some sense of control. (This was one of Van’s

And from that point, our problem-solving bent kicks in. Almost all traders and investors tweak their systems and strategies prematurely, based on too little data (too small of a sample size). We have all been trained in an education system that teaches pure cause and effect and the use of immediate feedback loops to solve the problem if we don’t get the desired outcome. Dealing with more complex systems, with higher levels of uncertainty, is just not in most people’s basic educational background or experience.

So what?

Our cause-and-effect thinking works in most areas of our personal and professional life. And it is deeply rooted in our need to be right (another one of Van’s favorite biases…).

A useful solution to help overcome our mental “cause and effect” disconnect is simple to describe, but much more difficult to adopt for the long term. We must allow our trading and investing strategies to play out for a long enough time to reach their expected profitability. The simple solution is to lengthen our time horizon for our trading results. Don’t fret and wring your hands over the results of every trade.

Each trade should be evaluated ONLY in terms of whether or not we followed our trading rules or guidelines without regard for the dollars and cents results. Reset your cause-and-effect decision process on a group of 30 or 50 trades (or an even higher number if you trade more frequently). Then you can evaluate cause and effect on a useful data set, not on one trade that has many more outside influences than one can ever hope to control.

This large data set review discipline serves several purposes:

  • It reduces stress by telling our mind that no single trade matters very much, as long as we follow our rules.
  • It reduces the variability of results over time because we’re only tweaking our system or strategy after an appropriate interval of time.
  • It greatly increases the chances of profitability because we do fewer and fewer of the systematic things that cause losses.

No one trade is important (as long as you honor your stop-loss and use proper position sizing for your size of account)—it is just useful data as part of the larger whole. Allow yourself and your strategy the luxury of time. And don’t be surprised if lower stress and greater profitability follow close behind.

Do you have a different way to look at or deal with the uncertainty inherent in trading? Email me and let me know. I love to hear your feedback! Please email your thoughts to me at drbarton “at”

Great trading and God bless you,

D. R.

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