Random Reinforcement: Why Most Traders Fail

One interesting emerging topic in trading is that of random reinforcement. Random reinforcement, as it relates to trading practices, occurs when a trader misattributes a random outcome to their own skill or lack of skill. This can be detrimental as a trader may come to believe their own prowess when it does not, in fact, exist—or greatly discount it when it does.

Key Takeaways

  • Random reinforcement is the attribution of arbitrary events to qualify (or disqualify) some hypothesis or idea; giving the illusion of skill or lack of skill to an outcome that is unsystematic in nature.
  • Random reinforcement occurs when traders are rewarded (at random) for behaviors that are not actually of their own doing.
  • Because of random reinforcement, traders may grow overconfident in their ability even though it may be objectively unfounded.

How Random Reinforcement Affects Us

The market, it turns out, occasionally rewards bad habits and punishes good habits because of randomness and noise. This can be especially detrimental if a new trader wins on a few early trades, having absolutely no plan whatsoever, and chalks this success up to innate skill or "intuition." Random reinforcement can also hurt veteran traders who experience a string of losses and thus come to believe they no longer possess their true skill.

Random reinforcement can create long-term bad habits that are extremely hard to break. It is similar in some ways to gambling addicts who keep playing because they win just enough to keep them there, but of course they are losing their money over the long run. A talented card counter may likewise experience a significant drawdown, abandon a proven strategy and in doing so give the edge back to the house.

The concept of random reinforcement is hard to grasp for some traders, but understanding it can be the difference between actually improving as a trader or simply believing we are improving when we are not. The best way to understand this to go through a few examples.

Example 1: Relying on Randomness

Alex is a new trader with a business background who watches the news and follows the stock market; but has not so far traded personally. Still, Alex thinks they have what it takes to be a good trader, but so far, has not written any strategies or trading methods down. Alex has opened a trading account and believes background knowledge will make for profitable trading. Pulling up a price charts for the first time, Alex sees a pre-populated stock ticker listed by default in the trading platform, and the prices are rising quickly. Alex quickly buys 200 shares of the default stock without even thinking. The stock continues to rise while during lunch. After lunch, Alex comes back and sells the shares, making a $100 profit after fees. Alex makes another trade and ends up with a similar result, starting to feel self-assured and having a "knack" for trading.

In analyzing the situation, experienced traders will notice a few things that could lead to a short-lived trading career for this trader. The main problem is that a handful of successful trades are not a valid sampling for if a trader will be profitable over the long run. Alex, the trader in this case, needs to make sure that they do not fall into the trap of believing that current methods, which are still very much untested, will bring long-term success. The danger lies in refusing proper market guidance or methods, whether self-created or provided by someone else because this initial untested method is believed to be superior based on these preliminary trades. The trader can begin to think very strongly that, if it worked once, it can work most, or all, of the time. The markets will not reward erroneous thinking over the long run but may reward random and unplanned trades some of the time.

In the next example, we will look at random reinforcement again, but from a different angle. This example pertains more to experienced traders, or traders who are coming to the market with a written down strategy or method that is back-tested or proven to be profitable in live trading. It should be noted that not all methods that were successful in the past will continue to be, as we just found out in the previous example (on a small scale). But methods that have shown success in the past are more likely to provide a chance of profitability in the future than a method that is completely untested or has never been profitable over the long run.

Example 2: Abandoning a Sound Strategy

Alex has now been trading in the markets for some time, and realizes that approaching the market without a well-thought-out, written, and thoroughly-researched plan was a mistake. The early problems evident in the first example have been overcome and now a solid trading plan for approaching the markets is in place. This new, disciplined method has worked well over the past two years, and has produced profits.

Alex, however, is now facing another problem. Despite past success with this plan, the strategy has now led to nine consecutive losing trades, prompting worry that the plan is no longer working. Alex therefore, hastily changes the trading plan, thinking that the prior method is no longer valid. In doing so, Alex ends up trading a new untested method, making similar missteps as in the early days.

The problem in this example becomes evident when Alex abandons the tried and true method, which has indeed been successful, in exchange for an unproven method. This could put Alex right back to the beginning, even after trading successfully in the markets for a number of years.

Why did this happen? Alex failed to realize that, while randomness can create winning streaks using a flawed trading method, randomness can also create a string of losses with an excellent trading plan. Therefore, it is very important to make sure a trading plan is not actually going to work anymore (was the original success random?) or determine if this could simply be a run of losses based on current market conditions that will soon pass.

All traders experience losses, and there is no definitive number of losing trades in a row that will tell a trader if a plan is no longer working. Each strategy is different, but we can learn to deal with randomness.

Frequently Asked Questions

Why does random reinforcement happen?

Human beings are naturally pattern-seekers. But, the world as we know it is full of randomness, which the human brain does not often like. At the same time, people like to feel in charge of their own destiny and have a sense of self-determination. As a result, when random events happen, people are apt to misattribute them to something that they themselves have done.

How does random reinforcement influence traders?

There are two primary ways that random reinforcement manifests itself among traders. The first is that it can give novice or unskilled traders a false sense of ability, when past positive outcomes are due to chance alone. The second way is that string of bad luck can influence an otherwise skilled practitioner to doubt their ability and abandon a good strategy.

How can one protect against the negative biases of random reinforcement?

Once we realize that randomness can create strings of losses in great trading plans and strings of profits in poor trading strategies (and also scenarios that fall in between these examples), one can adjust accordingly. Each trader should maintain a written trading plan that outlines how trades will be made and when. This plan should be well-researched and clearly spell out entries, exits, and money-management rules. In this way, the trader will know over the long run if the plan is flawed or successful from an objective measure. It is also important to risk a relatively small percentage of capital on each individual trade; risk levels of each trade should be covered in the trading plan under the money management section. This gives leeway to the trader as they will be able to withstand a string of losses and be less likely to make a premature change in the trading plan when it is not needed.

The Bottom Line

The markets are extremely dynamic and in constant flux. This brings in an element of randomness that can create profits for unskilled traders and losses for skilled traders, and it happens all the time. A trader must also determine when a certain string of losses or profits can be attributed to their skill and when it is random.

The only way to do this while you are learning is to approach the markets with a trading plan and risk a small percentage of capital on each trade. In this way, the trader can see how a method performs over the long run, in which randomness becomes less of a factor. It is also important to remember that even the best traders and trading methods experience strings of losses, and this is not a good reason to abandon the strategy. However, isolating why the method is no longer working may help lessen the extent of the losses when similar adverse conditions arise again.

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