Algorithmic trading, or rule-based and process trading, is a way of operating in financial markets that uses algorithms to perform buy and sell operations.
This is a way of trading based on mathematics and logic, where orders are given based on an automated algorithmic procedure. These algorithms follow a set of previously defined instructions for certain circumstances and if they are met, the operation is executed. For example, we can decide to buy or sell when the difference between both prices gives us a certain profitability. This way, the algorithm interprets that if this goal is reached, it should give the sell order.
The history of algorithmic trading goes hand in hand with computing. The arrival of increasingly powerful computers allowed for many financial operations to be carried out without the need for human intermediation, such as digital banking. One of the main advancements was predictive modeling or backtesting applied to personal computers. Initially, programming was used, but later, specialized software that did that part of the work appeared. The next step was to automate the markets themselves through platforms that performed these processes without human intervention, allowing them to operate directly in financial markets without the need of intermediaries.
Over time, different countries and supranational entities, such as the European Union, have legislated to regulate the use of these strategies. Among other aspects, they take into account the requirements of companies, the systems used, or electronic access.
There are a number of widely used indicators that can be of two types: late or momentum indicators, which aim to enter an already established trend, and contrarians, which aim to change the trend. The most well-known are: Relative Strength Index (RSI), which uses the moving average to observe possible trend changes. Moving Average Convergence Divergence (MACD), which also uses moving averages. Trade Break Out (TBR), which is an indicator based on support and resistance and breaks when the price is above or below these. Momentum (Mom), if it takes a positive value, the market would be on the rise and vice versa. Moving Average (MA), in this case, if the short-term moving average exceeds the long-term moving average, an upward trend is expected. Bollinger Bands, which make use of moving averages and standard deviations. Average Directional Index (ADI), an oscillator whose values are between 0 and 100.
Advantages of algorithmic trading include: Execution speed and precision, Ability to handle large volumes of data, and to monitor multiple markets simultaneously, 24-hour operation, and the ability to backtest and optimize trading strategies. However, it also has some disadvantages such as the risk of errors in the algorithms and the need for constant monitoring.
