Trading Automated? Market Research Software Advantages and Limitations
Every brainchild of human thought seems to be inevitably fraught with complications, especially when money is mixed in. It pains one to visualize the inner workings of something like the stock market, especially now that the world is besieged by global economic and financial recession. Many companies are struggling to be rid of the vise grip of the crisis that has already claimed many others, not just any companies, but known ones. With such influential organizations rising and falling, stock traders need all the help they can get trying to make sense of stock market figures that might some might even try their luck in automated trading via stock software.
Putting a computer’s excellent data gathering and analysis skills to use, stock market software is one of the more useful things that had come out of the mesh of the World Wide Web that has today become commonplace. Such software range from simple observational systems that collect and organize data to analysis programs that analyze the collected figures to decision making software that forecasts trends in the market and buys and sells accordingly based on the gathered and analyzed data. The data observation and gathering plus the analysis parts make such stock trading software virtual assistants to stock traders and are quite accurate and useful. But the decision making software is rather dubious.
It may be true that a computer is the best machine to analyze such twisted data as stock market figures and also best suited for performing the analysis based on a predefined principle or theorem like fundamental or technical analysis, but it is also true that the stock market can at times be beyond logic. One example of such an irrational instance is the stock market crash of 1987 where the Dow Jones Index dropped 22.6% for no probable reason. None logical, at least. Even if computers were observing the trends before the crash and were making forecasts thereafter they could not have been able to predict such an outlier. This is still the case today. No computer can accurately forecast an outlier possibility in a Normal distribution of trends and in so doing take advantage of it. Furthermore, the Efficient Market Hypothesis of Professor Eugene Fama effectively negates a computer’s potential to break the bank, or in this case, beat the market. Stating that it is not possible to consistently outperform the market from information from the market, though the hypothesis has its drawbacks and contenders, is sound enough to ring true for the case of a investment management software.
Finally, there is the psychological aspect wherein a computer can’t predict human over or under reaction that can cause over or under pricing. In the end, though computers are undoubtedly excellent in observation and analysis, humans should still have the final say.
