Trading systems are generally computer software programs which issue buy and sell signals based upon price, volume or other empirical data. By analyzing real-time price data and comparing such data to pre-set pattern recognition inputs, or by running said data thru mathematical algorithms generally compiled by the system provider himself, trading signals are generated and then run through an auto-execute applet in order to effect the trades thus indicated.

Because such systems are computer-based, they are not liable to human input and thus don’t carry the tendency to second guess the pre-set parameters, hesitate to execute indicated trades, or simply miss signals because the trader is distracted for any reason.

They are thus incapable of straying from the trading discipline set into the system at its outset.

In short, they are significantly less liable to the human frailty inherent in any trader’s psyche.

Because computers aren’t subject to distraction or fatigue or hesitation, they offer a more disciplined approach to trading volatile markets while also possessing the added advantage they are able to make trading decisions 24 hours per day, seven days per week often for weeks on end. Additionally, because the developmental stage is where the decision-making process is defined, tested and refined, subsequent decisions are made with split-second efficiency far beyond the capability of any human trader.

This defining, testing and refining process often goes on for years and in some cases even decades to come up with the end result. That being said, hypothetical results do offer investors the ability to evaluate key performance statistics such as: