Algorithmic trading is a new direction in the financial sector. The sense of this process is in using special algorithms, strategies, approaches based on the analysis of the accumulated massive of information.
Algo-trading uses the latest technologies:
- big data;
- data science;
The basic concepts of mathematics, statistics, and probability theory are laying in Algo-trading essence. The essence of the research is in calculating the price hitting the specified range based on the analysis of historical data and other financial criteria. Automated trading provides a significant advantage over manual trading. The choice of a trading strategy is important, and the creations of an algorithm taking into account all the nuances of exchange trading.
A trading strategy is a set of rules or a plan of action in the market. It includes some basic parameters: instruments, entry/exit points, amount of funds, and risk of loss.
Trading strategies can be divided into 4 types:
- trend, such as Momentum;
- based on reversion to mean (counter-trend);
- based on ML, alternative data;
- based on the imbalance.
The trend is the basis for making a profit when using trending strategies. Their essence means simple things:
- trend definition;
- determination of the moment of entry;
- all deals are made only in the direction of the trend;
- operations are performed up to a trend reversal or correction.
Trending strategies are the most common trading systems. They mean work on the rise or fall of the price. The strategies are considered classic in the foreign exchange market, are available for understanding and use by novice traders, and provide high profitability. However, not everything is so simple, -sometimes, false signals appear that you must distinguish from a real trend reversal. Moving with the trend is the easiest way to make a profit without the risk.
The mean reversion strategy is categorized as a counter-trend. Sooner or later, the asset price will return to the average. In this case, it is assumed that trading is carried out against the trend (that’s why the name is counter-trend). Using this strategy requires great care and attention – many different factors must be taken into account. The average price can easily change, which leads to the breakdown of the entire strategy.
ML (Machine Learning) – machine learning, the use of “artificial intelligence” in trading. Automatic learning algorithms provide effective trading strategies, minimize risks and increase profits. The training algorithm is based on the concept of patterns, most often historical price data.
Imbalance-based strategies. The market can be in two states – balance and imbalance. In the first case, supply and demand are balanced. In the second, an imbalance occurs, a trend sets in, the price rushes in search of a new balance zone.
Advantages of Automatically Applying Strategies
The main disadvantage of manual trading is the human factor. The trader can make the wrong decision on the trade, which will lead to losses. Algorithmic trading completely eliminates the negative impact of the human factor on trading. The advantages of algorithmic trading:
- a computer algorithm eliminates the subjectivity – each trader has his own criteria for assessing the situation on the market. The machine follows only the program logic while analyzing huge amounts of information without failures and emotions;
- the psychological factor is completely excluded in the case of algorithmic trading – the trading robot has no fear, it doesn’t feel any panic, but follows only the set program, excluding an error;
- the capabilities of machine processing are great in comparison with the capabilities of the human brain – an algorithmic strategy implies working with large data massifs, deep analysis of the market, which allows to make the right decision and get a perfect result;
- the machine works with factors that a person may not pay attention to, missing the moment to make an important decision on the transaction;
- speed of information processing and decision-making is a very important advantage of the robot, you can significantly expand the set of tools;
- the computer eliminates the possibility of errors – the machine works always properly, excluding the human factor.
Despite the imaginary simplicity and ease of implementation, algorithmic trading requires serious knowledge. It is necessary to understand programming, understand the basics of exchange trading, have information about the situation in the financial market, and many other aspects.
Self-study of algorithmic trading is a hard and lengthy process. It is easier and safer to entrust your savings to professionals.
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