Most trading transactions in the financial markets are carried out by automated trading systems or, to put it simply, bots. According to ZeroHedge, the share of such transactions in the total volume of trading operations in the financial market is more than 80%. The cryptocurrency market, which is in a legal vacuum, is no exception - auto trading and manipulations prohibited in traditional finance also flourish here. Moreover, the crypto exchanges themselves often encourage high-frequency trading in every possible way, which brings liquidity to the platforms and, of course, a considerable commission income. Many experts are convinced that the loosely regulated digital currency market is dominated by trading bots that influence trading volumes and pricing. The problem of market manipulation is the object of close attention from regulators, including the US Securities and Exchange Commission (SEC), which, by rejecting applications for the launch of bitcoin-ETF, hinders the development of the cryptocurrency market by institutional investors. What is automated trading and why do we need trading bots? Automatic trading systems (ATS) or trading robots are programs that are used to fully or partially automate trading.
They use special trading strategies where bots open and close positions within fractions of a second. ATS is often mistakenly identified with the term "algorithmic trading". The fact is that the latter does not aim to make a profit. Algorithmic trading is a method of executing a large order when it is divided into several sub-orders with specific price and volume characteristics. Each of them is sent to the market for execution at a specific time. Algorithmic trading is designed to reduce the cost of executing a large order, minimize the impact of the latter on the market and reduce the risk of non-execution of the transaction. Another thing is trading robots, the only purpose of which is to make a profit.
These programs interact with exchanges via API, receiving and interpreting market information, and placing appropriate buy or sell orders. The actions of bots obey the given rules and algorithms. For example, the bot can take into account market parameters such as price, volume, orders in the order book, time, etc. They can also take into account data from technical indicators, such as exponential moving averages (EMA) or Bollinger bands, as well as various variables set by the user. In addition, bots can interact with each other and with various trading platforms (if we are talking about arbitrage strategies). Trading bots allow the trader not to devote much of his time to analyzing the market and price movements on various currency pairs. Bots have advantages over real people, mainly due to their ability to complete transactions in fractions of seconds, 24/7.
Unlike people, programs are devoid of emotions and can work with a large number of exchanges and currency pairs. PBXs are used by professionals, including fairly large financial companies, and by "amateurs" - simple owners of cryptocurrencies who seek to receive passive income and increase their capital. Note also that high-frequency trading firms and individuals usually do not need a huge amount of capital, nor do they need to accumulate and hold positions. In addition, the potential Sharpe ratio for high-frequency trading can be several times higher than for traditional strategies such as Buy and Hold. Progress does not stand still, algorithms become more complex, and various bots compete not only with people, but also with each other. Bot types and basic trading strategies 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 - taking advantage of the difference between the prices of buying and selling 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. Are trading bots effective? As mentioned above, the opportunities for arbitrage in the cryptocurrency market are no longer so attractive. As for market making strategies, many bots, for example, are guided by data from the EMA and other lagging indicators.
The values of such technical analysis tools are based on past history, which is their undoubted disadvantage. Thus, most automated trading systems analyze only in retrospect. In general, the technical analysis of cryptocurrencies is criticized by many, referring to the key role of external, non-market factors. However, critics often overestimate its capabilities, forgetting that analysts' assumptions are only probabilistic. Technical analysis is only an assistant in decision making, not a get-rich-quick tool. In the conditions of a market that is not so liquid, volatile, prone to manipulation and reacts sharply to “high-profile” news, it is difficult to predict anything in advance. Do not forget that each market participant has his own risk appetite.
The latter represents the degree of readiness of a trader/investor to work with high-risk assets. This term is often interpreted as the degree of uncertainty that an investor can afford regarding a possible negative change in the value of his portfolio of assets. All this means that certain trading strategies are suitable for some traders, but completely unacceptable for others. In addition, a bot that has shown good results will not necessarily show high performance in the future. Ignoring this fact can lead to the so-called survivor bias. .