Trading bots differ among themselves in terms of complexity, device principles and, of course, in price. There are three main categories of such programs: simple bots with predefined logic; Software based on artificial intelligence and machine learning (“smart” bots); advisers. Simple bots act on the basis of ready-made scenarios that guide them in a given situation. The algorithms embedded in them, as a rule, can be edited, since once configured bots are unlikely to provide a stable income in the long term. "Smart" bots. Solutions of this kind are usually capable of self-learning. They can be based on neural networks and machine learning algorithms that increase the efficiency and depth of analysis.

These bots are usually more expensive and harder to use. Robots-advisers can belong to both the first and second categories. From the name itself, it is clear that such solutions give recommendations, and do not make deals. Such programs are also often used in the context of fiduciary management, when transactions via the API are managed by a remote broker. In automated trading, various strategies are possible, including: arbitrage - earnings on the difference in prices of digital coins on different exchanges (or between the underlying asset and its derivative instrument); market-making is taking advantage of the difference between the buying and selling prices of coins, as well as their derivatives. When cryptocurrency trading was still in its infancy, and the market efficiency was even weaker than it is now, many traders made money on arbitrage. In other words, they bought assets on one exchange and sold on another at a higher price, making a profit in the form of income from the difference, minus commissions.

The fact is that a few years ago the volume of the market was several times smaller than it is now. There were not so many people trading, there were fewer exchanges and, accordingly, the competition between the sites was not so fierce. All this served as a cause of imbalances on different platforms from which it was possible to benefit. As the infrastructure developed and the market grew, the differences in prices smoothed out, and gradually such an activity became less relevant. The market-making strategy involves making speculative profits. In accordance with price fluctuations, the trading bot places limit orders and makes a profit on the difference between the buy and sell prices. For providing liquidity that improves the quality and attractiveness of the trading platform, traders can receive bonuses in the form of reduced commissions.