Random Reinforcement: Why Most Traders Fail
Random Reinforcement: Using arbitrary events to qualify (or disqualify) a hypothesis or idea; attributing skill or lack of skill to an outcome that is unsystematic in nature; finding support for positive or negative behaviors from outcomes that are inconsistent in nature—like the financial markets.
One of the most interesting topics in trading, and really throughout many areas of life, is random reinforcement. Random reinforcement, as it relates to harmful trading practices, occurs when a trader attributes a random outcome to skill or lack of skill. The market occasionally rewards bad habits and punishes good habits because the market is so dynamic. It is especially negative if a new trader who wins a few trades, with absolutely no plan whatsoever, attributes this success to “intuition.” Random reinforcement can also hurt veteran traders who experience a string of losses and believe they no longer possess skill. (See also: Trading Psychology and Discipline.)
Random reinforcement can create long-term bad habits that are extremely hard to break. It is equivalent 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 successful card player may also experience a significant draw down, abandon his proven strategy and in doing so give his edge back to the house. (See also: 10 Cleaning Tips to Spruce Up Your Trading.)
How Random Reinforcement Affects Us
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.
[You are more likely to avoid the issue of random reinforcement if you consistently and meticulously incorporate the proper technical tools in your analysis. To learn more, check out the Technical Analysis course on the Investopedia Academy, which includes interactive content and real-world examples that can help you along the path to profitable trading.]
Example 1: Relying on Random
John is a new trader. He has a business background, watches the news and follows the stock market, but he has not traded personally. He feels he has a good handle on what it takes to be a good trader, but so far, he has not written any of these methods down. John has opened a trading account and believes his background knowledge will make him a profitable trader. Opening his charts for the first time, John see a default stock in the trading platform, and it is rising quickly. He quickly buys 200 shares without even thinking. The stock continues to rise while he makes lunch. After lunch, he comes back and sells his shares, making himself a $100 profit after fees. John makes another trade and ends up with a similar result. He is starting to feel that he is very good at this and that he must have a “knack” for trading.
In analyzing the situation, experienced traders will notice a few things that could lead to short-lived trading career for this trader. The main problem is that several successful trades are not a valid sampling for if a trader will be profitable over the long run. John, the trader in this case, needs to make sure that he does not fall into the trap of believing that his current methods, which are still very much untested, will bring him 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. (See also: 9 Tricks of the Successful Trader.)
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 Strategy
John has now been trading in the markets for some time. He realized that approaching the market without a well thought out, written down and well researched plan was a mistake. He has overcome the problems evident in the first example and now has a solid trading plan for approaching the markets. This method has worked well over the past two years, and he has made money.
John is now facing another problem. Despite past success with this plan, his method has now led him to nine consecutive losing trades, and he is starting to worry that his plan is no longer working. John therefore changes his plan for trading, as he feels his method is no longer valid. In doing so, John ends up trading a new untested method, possibly similar to when he started trading.
The problem in this example becomes evident when John abandons his method, which has been successful, in exchange for an unproven method. This could put John right back to the beginning, even after trading successfully in the markets for a number of years. (See also: Day Trading Strategies for Beginners.)
Why did this happen? John 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 his or her plan is no longer working. Each strategy is different, but we can learn to deal with randomness. (For more, see: 4 Key Elements to Create a Successful Trading Plan.)
What We Can Learn
Once we realize that randomness can create strings of losses in great trading plans and strings of profits in poor trading plans (and also scenarios that fall in between these examples), how do we adjust to trade profitably over the long term?
While each trading plan is different, each trader must have a written trading plan that outlines how he or she will trade. This plan should be well researched and lay 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. It is also extremely important to risk a very small percentage of capital on each 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 he or she 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. (See also: Ten Steps to Building a Winning Trading Plan.)
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 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 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. (See also: Financial Ratios Tutorial and Investing 101 Tutorial.)
Source: Read Full Article