By David Adams
The New York Stock Exchange and the Chicago Mercantile Exchange are home to some of the most sophisticated trading systems and automated trading computers in the world. It would not be an exaggeration to say that billions of dollars have been invested in computerized trading in the last 20 years. Computer based trading is even highly specialized in the function performed. Some computers are utilized to call turns in the market, others are used to map out hypothetical movement in the market, and still others are used to systematically scale in and out of potential and present market positions. Oddly enough though, most of the real trading, and especially the important calls on when to buy and sell, are a human function.
One of the most difficult and obtuse concepts for most laymen and new traders is the degree of randomness present in all market conditions. Depending on which source you quote, anywhere from 60 to 80% of the typical price action is random in nature. By definition, it is impossible to predict random movement. For this reason alone, computerized trading has fallen short of the grand expectations the investment industry envisioned a decade ago. The real workhorses on the exchanges are not computers but real live human beings.
But it would certainly be a grand idea for the average American to flip on a computer and earn thousands of dollars every month without any idea how the market functions. Heck, investment professionals would love to have a computer that spit out consistent profits month after month. Unfortunately, computers haven’t lived up to their expectations and it is doubtful that they ever will.
Why?
The very best in computerized trading systems used by major investment firms require constant reprogramming to compensate for the many phases and moods the market exhibits throughout the course of a single year. To calculate the multitude of pricing anomalies that occur in a five-year period is staggering in scope. To be sure, computerized trading suffers from the same problems that all human traders suffer; the market is a beast with many moods and exhibits such a wide range of pricing behavior that it takes years for the human mind to recognize and adjust to these ever-changing conditions. Since the computer is only as good as its programming, Wall Street finds itself constantly adjusting risk components and pricing mechanisms to compensate for the wide variety of price behavior I have described above. Quite simply, the market’s random behavior combined with some of the very organized behavior it exhibits are difficult to predict with any accuracy via mathematical algorithm. This is a very difficult concept for many individuals to conceptualize, as our minds are conditioned to gather data and organize that data into some system that makes sense on a consistent basis. You need only look at the hundreds of trading systems in existence to realize that there is absolutely no consensus on how the market prices its underlying securities. For that matter, there is very little consensus on how the market actually functions, in terms of equity pricing.
But it has become very common to see advertisements in recent years hawking computer robots that will rake in thousands of dollars monthly. I don’t doubt that from time to time these computer robots have very successful months, but the wide range of market behavior has always precluded even the most sophisticated computers from consistently outperforming the market. This fact is evidenced in the relative rates of return over the last 30 years. They haven’t changed very much; with or without computers the major investment firms have been unable to appreciably increase their rates of return.
My point is a fairly simple one, you can earn money in the equity markets with proper training and knowledge and a major amount of experience, but the expectation of purchasing a $300 computer robot and raking in a consistent income has been empirically proven to be, at best, unlikely. To be sure, most testing as shown that computer robots tend to lose money, especially when the tests are over a 3 to 5 year business cycle. Again, the problem is as described above; there are simply too many pricing variables for any computer to analyze properly and invest profitably.
In summary, we have discussed the random nature of the equity markets and the inability of some of the most sophisticated computers in the world to accurately invest and profit. I have pointed out that the majority of major investment decisions are still made at the human level. And finally, I have warned that the retail computer robots currently being marketed may not perform as advertised, at least over the long term. If you’re interested in earning money in the equity markets, learn to trade and profit.
About the Author
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