Computers are now enabled to automatically perform particular rules for trade entry and exit that were created by traders in what’s known as the automated trading system. Automated trading systems are also known as mechanical trading systems, algorithmic trading, automated trading, and system trading.
Automated trading systems account for 70 percent – 80 percent or more of shares traded on US stock exchanges. Traders and investors can automate trading systems that allow computers to execute and monitor deals based on exact entry, exit, and money management criteria.
The criteria for trade entrance and exit rules can either be straightforward, like a moving average crossing, or they can be complex methods that call for a thorough knowledge of the programming language used by the user’s trading platform.
The majority of the time, automated trading systems need to be run on software connected to a direct access broker, and any special rules must be defined in the platform’s proprietary language. The EasyLanguage programming language, for example, is used by the TradeStation platform, while NinjaScript, on the other hand, is used by the NinjaTrader platform.
The ability to reduce some of the emotion involved in trading by automatically placing trades when particular conditions are satisfied is a plus and considered by the users as one of the main benefits of automated trading.
Backtesting evaluates the validity of a concept by applying trading rules to past market data. All rules must be rigid and devoid of any opportunity for interpretation while developing an automated trading system. Precise instruction must be given to the computer because it is unable to guess. Before putting their money at risk in live trading, traders may use these specific sets of rules and test them on historical data. The system’s expectation, or the average amount a trader may anticipate to gain (or lose) per unit of risk, can be ascertained by careful backtesting, which also enables traders to assess and fine-tune a trading concept.
Discipline is maintained even in tumultuous markets since trading rules are defined and transaction execution is automated. Emotional considerations like the dread of suffering a loss or the desire to squeeze out just a little bit more profit from a deal cause discipline to be lost frequently. Automated trading makes it easier to keep discipline since the trading strategy will be adhered to precisely. Pilot error is also reduced to a minimum.
Automated systems can generate orders immediately since computers react to shifting market circumstances instantly. A few seconds earlier entry or exit from a transaction can make a significant impact on the deal’s result. All additional orders, such as stop loss protection and profit objectives, are produced automatically as soon as a position is opened. Markets may move rapidly, and it is discouraging to see a trade exceed the profit objective or blow beyond a stop-loss level before the orders can even be submitted. Such occurrences are avoided by automated trading systems.
The use of numerous accounts or different trading techniques at once is made possible by automated trading systems, which allow for trading diversification. The creation of a hedge against losing positions can distribute risk over several instruments. A computer efficiently completes tasks in milliseconds that would take a very long time for a person to complete. A variety of marketplaces may be searched for trading possibilities by the computer, which can also produce orders and track trades.
Automated trading systems necessitate monitoring, even if it would be fantastic to turn on the computer and go about your day. This is due to the possibility of technological setbacks such as system oddities and connection, power, or computer difficulties (such as problems with loss of power). For instance, anomalies that might lead to erroneous orders, missed orders, or duplicate orders could occur in an automated trading system. These occurrences may be immediately discovered and rectified if the system is monitored.
Trading strategies that appear excellent on paper but perform poorly in a real market can be produced via backtesting procedures, but this is not exclusive to automated trading systems. An excessive amount of curve-fitting results in an unstable trading strategy in real-time trading, which is referred to as over-optimization. On the historical data that it was tested on, for instance, a strategy may be adjusted to produce extraordinary outcomes. It’s common for traders to believe that a trading strategy needs to be almost 100% profitable or should never have a downturn to be successful. As a result, specifications may be modified to produce a “near perfect” strategy that entirely fails when applied to a live market.
The traders who are aiming to apply the automated trading system should choose a trained coder to trust and rely on their knowledge in the process. Also, they should consult the game-changers in the cryptocurrency world, Volofinance. Visit our website or contact us via email at [email protected] and let the professionals take it from there.