All throughout the close of the 20th century, human civilization was promised a veritable wonderland of technological innovations and advancements that would completely revolutionize the way in which we lived, worked, loved and even dreamed. From jet packs and flying cars to robots and condos on the moon, human kind expected the 21st century to be a completely New World Order. Of course, now that we are collectively entering into the second decade of the 21st century, we are beginning to realize just how far off of the mark the predictors and experts really were.

Instead of flying cars and jet packs, we now have super-slim computers and a first class World Wide Web. And though the latter two are no slouches, they are not really what one would consider as “grandiose.”

But there is one innovation that is making some serious noise, and is poised to completely change the way that investors make money. In fact, with this new innovation, stock market crashes may become a thing of the past. The innovation is an automated trend trading system that can nearly perfect the way in which investors deal with the markets, and eliminate a large share of the risk inherent with stock market trading.

Here are two ways in which automated trading systems far surpass traditional trading systems.

They Eliminate Human Biases

One of the biggest things that automated systems have going for it is the fact that they completely eliminate the biases and prejudices that come with human stock brokering and fund management. Say a particular trading broker once got burned on soy bean futures. Twenty years later, he or she now completely dismisses the market of soy bean futures and does not factor them into the market analysis. An automated system harbors no such bias, and is able to make full use of the advantages of all types of investments. Truly, nothing is off of the table with an automated trend trading system.

They Mitigate Human “Emotional” Error

Automated systems can also mitigate human error, because they have a set pattern recognition algorithm that is responsible for analysis, and every move that it suggests is based upon preconceived patterns. With human analysis, this is not true. A human stock broker faces the problem of being caught in a particular situation that he or she could not predict, and overreacting in one way or another.