Automated trading refers to the act of using automated trading systems in order to establish specific rules for both the trade entries and exits that, once programmed, can be automatically executed through a computer.
The trade entry and exit rules can be based on simple conditions like moving average crossover, or they can be complex strategies that need a comprehensive understanding of the programming language specific to the user’s trading platform or the expertise of a qualified programmer.
Even though automated trading systems do have huge advantages that many traders enjoy when they are doing it right, it also sports many inherent risks that are quite difficult to just ignore. In this article, we’re going to talk about those disadvantages. After all, the more you know a system’s risk, the better you can mitigate them.
The theory behind automated trading make it seem overly simplistic: just set up the software, have some programs for the rules, and watch the computer execute the trade. However, if we’re talking reality, automated trading is a sophisticated method of trading that is, just like any other system, not infallible.
Depending on the trading platform being used, a trade order could reside on a computer and not a server. That means if an internet connection is lost, an order might not be sent to the market. There might also be a discrepancy between the “theoretical trades” generated by the strategy and the order entry platform component that turns them into real trades.
You might want to expect a learning curve when using automated trading systems. To begin, it’s generally advised to start with small trade sizes while the process is being refined.
Although it would the idea of merely switching the computer on and leaving for the day sounds really fantastic for a trader, automated trading actually requires monitoring. This is because of the possibility of mechanical failures, such as connectivity issues, power outages, or computer crashes.
It’s also possible of an automated trading systems to encounter some anomalies that could result in erroneous orders. If you monitor the system, these events can be identified and resolved very quickly.
Even though it’s not specific to automated trading systems, traders that use backtesting techniques can create systems that appear great on paper and perform terribly in a live market.
Over-optimization refers to the excessive curve-fitting that results to a trading plan that’s quite unreliable when it comes to live markets. It is possible, on the other hand, to tweak a strategy to achieve exceptional results on the historical data on which it was tested.
Traders sometimes assume incorrectly that a trading plan would work out just fine and should have close to 100 percent profitable trades or should never experience a drawdown to be a viable plan. As such, the parameters can be tweaked to create a “near perfect plan” that completely crumbles down to pieces once you apply it to a live market.