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What are the Different Types of Automated Trading Systems?

Automated trading systems come in various forms, from simple algorithmic models to complex artificial intelligence-driven strategies. They can be trend-following, arbitrage-seeking, or based on statistical indicators. Each system aims to execute trades with speed and precision, often outperforming human traders. Wondering how these systems can enhance your trading experience? Let's examine their unique advantages and potential risks together.
Ron Davis
Ron Davis

There are two ways of classifying automated trading systems. One is on the basis of whether the algorithms are disclosed. If the algorithms are disclosed, the systems are called a “disclosed system.” Automated trading systems that are not disclosed are referred to as “black box” systems. The second way of classifying these systems is based on the type of algorithm used.

Cycle studies, volatility break out, and price break out are the most popular algorithms. Cycle studies bring together cycles of different lengths to predict tops and bottoms. Volatility break out systems generally focus on times when a stock or commodity has low volatility, then enter the market on an increase in volatility. Price break out systems trace the highest and lowest prices over a period of time, then enter the market when a higher high or lower low is made.

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Businessman giving a thumbs-up

After an automated trading system has entered a position, it must determine when to exit that position. Some systems use a moving average while others hold for a certain number of time periods, and then exit. Another approach is to exit as soon as a position is profitable or to exit after a certain level of profitability is reached. Most systems have a fixed amount of loss that is the largest loss the system is designed to allow. The term for that amount is the “stop loss.”

There are many computer programs sold as black box trading strategies. Most of them are sold on the basis of “backtesting.” If there is either no substantial history of real time trading, or a large body of good results on data other than the backtest data, such as a Monte Carlo simulation, using the system with real money is a major gamble. It is not hard to put together a few rules and then optimize the system over five or ten years of trading data so that they produce eye-popping results, but such a system is unlikely to be profitable in real world trading.

Automated trading systems that are profitable do exist. They have been created by people with a very deep knowledge of physics working along side people who have a very good understanding of how markets work. The creators work for investment or trading groups that, for the most part, keep a low profile. Like all areas of trading or investing in the markets, entrusting one’s money to an algorithmic, automated trading system should be done with great caution and only after substantial research.

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