How Do AI Trading Bots Work? A Detailed Explanation

AI trading bots can be the answer to the volatility of cryptocurrency trading. These automated systems can tirelessly monitor the market, analyze complex data, and execute trades based on predefined strategies, saving you time and effort. Still, how do AI trading bots work? Are they safe?

To demystify these applications, I’ll show you a step-by-step explanation of how they work, from configuring parameters to executing the trades automatically. I’ll also talk about AI trading bots’ legality and some considerations to manage their risks to help you make informed decisions before using them.

That said, if you want to minimize risks, I suggest you learn from free built-in bots from exchanges like Bybit and Binance. These platforms provide a safe and controlled environment to experiment with AI trading strategies without risking significant capital.

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How Do AI Trading Bots Work?

Before answering the question, "How do AI trading bots work?" it is important to understand that these programs are automated software applications designed to execute trades in financial markets, including stocks, commodities, and cryptocurrencies.

As the name suggests, it involves AI and machine learning (ML) to analyze data, make decisions, and execute trades with minimal human intervention. Generally, how AI trading bots work can be summarized in these three steps:

Step 1: Humans configure the bot by setting parameters like risk tolerance and target markets.

Step 2: The bot processes data collection and analysis.

Step 3: Based on its analysis, the bot determines whether to buy, sell, or hold an asset and executes trades by placing orders.

I'll explain each step in more detail below.

Parameters Set by Humans

Before an AI trading bot can operate autonomously, humans need to define its operating framework by setting key parameters, like preferred asset classes and trading strategies. Doing this ensures that the software aligns with the trader's goals, preferences, and risk tolerance.

The first step I suggest you take is to determine your trading goals (e.g., short-term profits, long-term portfolio growth, risk mitigation). Clearly defining your objectives allows the bot’s settings and strategies to be tailored to meet your expectations effectively. Here's a breakdown of common objectives and the corresponding strategies:

Table: common objectives and strategies

After deciding on a goal, think about clear benchmarks, including the desired percentage return over a specific period and the level of risk you’re willing to accept per trade or overall. Ensure these benchmarks are aligned with your financial resources, the level of monitoring required, and your understanding of the specific market you're targeting.

Data Collection and Analysis

AI trading bots rely on data collection and processing as the foundation of their operations. Once you enter your key parameters, the program typically begins to gather relevant data.

The first thing it will start to collect is information about real-time prices that show the current bid and ask prices for assets and trading volumes that indicate the total quantity of coins traded in a specific period. Usually, the bots incorporate fundamental economics into their analysis, including financial indicators like Gross Domestic Product (GDP) and central bank policies.

Besides market and economic data, good AI trading bots should scan sentiment data. These intelligent systems analyze news articles and social media sentiment related to economic updates, company announcements, and geopolitical events that may influence markets. They also assess and quantify investor sentiment by analyzing keywords, hashtags, and online discussions.

After collecting raw data, the bot processes it to extract actionable insights. Generally, the data analysis steps involve:

Step 1: Cleaning and normalizing data by filling gaps or excluding incomplete data points to maintain accuracy. Then, it ensures data is in a consistent format (e.g., converting all currency values to USD) and removes random fluctuations in price data to focus on meaningful trends.

Step 2: Identifying the average price over a specific time frame to highlight trends and measuring the strength of price movements or Relative Strength Index (RSI) to identify overbought or oversold conditions. Several bots may also offer to detect reversal or continuation patterns (candlestick patterns).

Step 3: Generating predictions to forecast market movements.

How do AI trading bots work to gather and process all of this data? These bots do so by the use of machine learning algorithms to find patterns and predict potential price movements^[1]. Some machine learning models that might be used include:

• Regression models that can predict price levels based on historical data trends.
• Neural networks that analyze complex patterns in price movements and predict future changes.
• Reinforcement learning so that the bot learns optimal trading strategies by simulating market interactions.
• Natural language processing (NLP) to evaluate positive/negative sentiment from text-based data.

Once data is processed, the bot combines findings from multiple sources and executes the trade.

Trade Execution

Trade execution translates its research into actionable buy or sell orders. In this step, the software requires precision, speed, and adaptability to make sure the trades are executed efficiently and as intended. That said, how do AI trading bots work in detail during trade execution?

When executing a trade, the automated program starts connecting itself to trading platforms, brokers, or exchanges via APIs, depending on how the humans set in the first step of this workflow. Once the connection is established, the bot sends buy or sell orders based on the signals generated by the AI algorithms.

Common order types include:

• Market orders execute immediately at the current market price.
• Limit orders ensure trades occur at the desired price or better but may not execute if the price doesn’t match.
• Stop-loss orders automatically sell an asset when its price falls to a predetermined level to minimize losses.
• Take-profit orders close a trade once the price reaches a specified profit level.

The list above includes common strategies. Meanwhile, those who seek more sophisticated approaches can choose an advanced execution method. One example is smart order routing, which splits large orders across multiple exchanges or brokers to achieve the best possible price. Alternatively, there is an iceberg order, which breaks large orders into smaller chunks to minimize market impact and reduce detection by other traders.

If you want to minimize market impact and achieve a more stable execution price, you can choose a time-weighted average price (TWAP) to execute orders gradually over a specified period to achieve an average price close to market trends. Another option is volume-weighted average prices (VWAP) which executes based on market volume to minimize price disruption.

Meanwhile, for high-frequency trading (HFT), the bot is usually optimized for ultra-low latency by executing trades in microseconds to capitalize on rapid market fluctuations. Alternatively, it continuously scans order books to detect profitable micro-arbitrage opportunities.

For those who are unsure about the best strategy, many AI trading bots offer backtesting capabilities. Using such a feature allows you to simulate the performance of different strategies on historical data to assess their potential effectiveness without using real money.

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Post-Execution Analysis

After executing a trade, an AI trading bot doesn’t stop its work but shifts focus to active monitoring and execution adjustment. It continuously assesses market conditions to ensure the trade aligns with its strategy and goals. For instance, the bot verifies whether the broker or exchange has successfully processed the order and takes corrective action if discrepancies arise.

If the market experiences sudden price changes or increased volatility, the program may cancel or modify pending orders to prevent unfavorable executions.

Yes, the transactions are not always successful. Failures can occur due to network issues, technical glitches, or exchange-side errors. When the bot fails, it typically retries the order automatically. Still, some automated programs enable you to set specific parameters for retry attempts (e.g., cancel a trade without retrying or cancel the trade after a specific number of consecutive failed attempts occurs).

Later on, the bot evaluates its performance by recording details like execution price, time, and volume and comparing the fill price to the predicted or expected price. This analysis helps identify areas for improvement, such as refining trading strategies or adjusting risk parameters.

Most bots also allow for human intervention. Traders can step in to manually adjust parameters, review strategy settings, or even override the software's decisions to align with changing market conditions or personal insights, ensuring greater control and adaptability.

Once you finish readjusting, the bot typically checks market depth before re-executing trades, ensuring there’s sufficient liquidity to complete transactions without significantly impacting prices – a critical factor, especially in less liquid markets. Additionally, it applies predefined thresholds, such as halting execution when prices deviate significantly from expectations, to limit losses.

Types of AI Trading Bots and How They Work

To better understand "How do AI trading bots work?" it’s essential to consider the different types available. Their specific functionalities and strategies can vary significantly, even within the same platform.

For example, a Dollar-Cost Averaging (DCA) bot executes trades at regular intervals with a fixed amount of capital, regardless of the asset’s price. Traders using this type of program typically aim to minimize the impact of market volatility by spreading investments over time. In this case, the underlying technology may include scheduling algorithms or predictive models to automate regular investment intervals.

Meanwhile, arbitrage bots exploit price differences for the same asset across multiple markets or exchanges. Compared to the aforementioned type, this one may require more technical setup and maintenance since it must gather APIs to monitor prices across various markets or exchanges.

Instead of relying on a simple scheduling technology stack, an arbitrage bot may utilize AI models like decision trees or rule-based systems. These models are designed to identify potential arbitrage opportunities based on specific criteria, such as price differences, market depth, and trading fees.

Grid trading bots, on the other hand, may use rule-based systems to set grid intervals. These programs execute trades automatically within a specified price range, buying at lower prices and selling at higher prices.

Lastly, trend-following bots, in contrast, may employ statistical models that rely on technical indicators. Examples include Moving Averages (MA), which smooths out price data to identify trends, and Bollinger Bands, which measure volatility and detect potential trend reversals.

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Benefits and Challenges of Using AI Trading Bots

At this point, you’ve got the answer to “How do AI trading bots work?” and you might have noticed that they help automate and accelerate many processes.

First, these systems can scan and interpret data much faster than any human could. Typical scans take only milliseconds or seconds, allowing them to react to market movements in real-time. Instead of manually tracking prices, indicators, or news, these bots work tirelessly in the background, handling repetitive tasks and freeing you to focus on refining strategies or exploring new investments.

When you choose an arbitrage trading bot, for example, it can simultaneously analyze multiple markets, currencies, or exchanges, offering broader coverage. This type of system can manage a portfolio of assets, spreading risk across different investments.

Some platforms also let you deploy multiple bots to execute various strategies, such as day trading, swing trading, or long-term investing. They’re customizable to align with specific goals, whether that’s high-frequency trading or conservative portfolio management. Others even manage trades across numerous stocks, forex pairs, or cryptocurrencies at once, so you won’t miss out on potential opportunities.

Besides customizability, you may benefit from ease of use. Many platforms offer user-friendly interfaces with step-by-step instructions, making the bots accessible to beginner traders.

With a range of free and subscription-based tools, these solutions cater to traders with varying budgets. For crypto traders, several exchanges - such as Bybit and Binance - even provide free bots, making it easier for anyone to try automated trading.

Additionally, bots trade based purely on algorithms and pre-set rules, eliminating emotional influences like fear, greed, or panic. Emotional trading is especially prevalent in the volatile cryptocurrency market, where emotions and speculation drive many investments^[2].

Therefore, the bot’s objective decision-making process is particularly advantageous. Many investors often make irrational decisions based on emotions or misinformation, leading to herd mentality and significant price fluctuations.

Still, using AI trading bots comes with challenges that traders should consider before fully relying on them. The most notable one is technical complexity, as understanding how to configure these systems and set parameters can be confusing for beginners.

There are numerous settings and variables to adjust, such as position sizing and trading strategies, which can be overwhelming for those who aren’t tech-savvy. Some bots also require coding skills to customize or develop unique trading algorithms.

Moreover, advanced bots can be expensive to develop, customize, and maintain. Some platforms charge premium rates for access to their most sophisticated features and strategies.

Another challenge is regulatory restrictions. Some jurisdictions may limit the use of automated trading systems, so the answer to "Is AI trading legal?" depends on your location. Regulations vary widely from country to country, making it essential to understand the legal framework in your specific region. Non-compliance can lead to legal and financial consequences.

Security concerns may also arise. Bots connected to trading accounts via APIs can be susceptible to hacking or unauthorized access. Storing sensitive financial data with third-party platforms increases the risk of data leaks, so it’s crucial to consider security measures when choosing an AI trading solution.

Does AI Trading Work and Make Money?

So, how do AI trading bots work to guarantee 100% profitability? Research suggests that using a simpler AI approach combined with a massive dataset and smart labeling helps achieve profitable trading strategies^[3].

In that study, the team employed a Neural Network model and reached 66% accuracy on a binary-labeled scheme, indicating that the trading system was profitable under every market condition.

Now, if you're still wondering, does AI trading work? While the researchers demonstrated promising results, they cautioned that these findings may not be universally applicable. Performance can vary significantly across different time periods and asset classes. It's important to remember that no bot can guarantee consistent profits, as markets are inherently unpredictable.

The bot itself isn’t immune to market fluctuations and unforeseen events. For instance, investment bankers have used basic AI capable of learning financial data and making autonomous decisions since the early 1980s. However, many events - from 9/11 and the 2007-2008 credit crisis to the COVID-19 pandemic - have blindsided financial markets, and the AI systems of that era did not predict such crises.

Despite this uncertainty, hype about AI’s capabilities has spread over the past few years. The BBC reported that 30% of investors would be comfortable letting trading bots make all their decisions.

While bots can reduce emotional trading and improve efficiency, as discussed in the previous section, they are only as effective as their programming and the prevailing market conditions. They strictly follow programmed rules.

Therefore, just like any investment method, your capital may be at risk when using AI trading bots or even human investment managers. I suggest learning how the overall market works - regardless of the asset - so you don’t rely on the platforms blindly without ongoing monitoring.

Is AI Trading Legal?

Besides understanding the answer to “How do AI trading bots work?” before using the tool, you should check how they are controlled in your country because regulatory guidelines vary among jurisdictions.

Given the hype surrounding AI, some regulators, such as the Securities and Exchange Commission (SEC) in the United States or the Financial Conduct Authority (FCA) in the United Kingdom, oversee markets to ensure fair trading practices.

The FCA, for example, takes a principles-based approach to regulation, prioritizing outcomes over rigid rules. While the specific regulations for AI trading don’t exist yet, firms using artificial intelligence must adhere to broader principles of fairness, transparency, and consumer protection within existing legislative and/or regulatory frameworks.

Meanwhile, the EU has recently implemented the Fifth Anti-Money Laundering Directive (5AMLD) that regulates cryptocurrency activities, including AI trading bots. If a company operates or uses a trading bot within the EU, it must comply with 5AMLD regulations, such as:

• Implementing the Know-Your-Customer (KYC) procedure to monitor transactions;
• Conducting stricter due diligence for high-risk third countries;
• Making public records of who ultimately owns or controls companies, trusts, and other legal entities.

To stay compliant and ensure your AI trading bot operates within legal boundaries, it's crucial to consult the official website of your chosen platform or service provider. They often provide detailed information about supported regions and specific regulatory requirements. Staying informed and adhering to these guidelines can mitigate legal risks and protect your investments.

Things to Consider Before Using an AI Trading Bot

From the explanation above, you might have noticed that these platforms can be powerful tools for optimizing your trading strategies. However, they also come with challenges that may hinder your overall trading success. So, how do AI trading bots work to manage risk effectively? In a nutshell, humans still play a crucial role in selecting and monitoring AI trading bots.

Knowing the platform's track record is among the most important aspects to minimize potential risks and maximize returns.

Research the bot’s provider background by checking user reviews and review articles to gauge its reputation and reliability. BitDegree can be your go-to source for searching for the best crypto trading bot because it has compiled comprehensive reviews and ratings of various platforms. Its reviews discuss user-friendliness, security and legal compliance, and performance so you can make informed decisions.

Besides the provider’s credibility, ask yourself, “How do AI trading bots work to make them align with your goals?”. See the type of strategy the bot uses (e.g., arbitrage, DCA, or grid bot), the asset it supports, and customization options, like risk levels, trading frequency, or stop-loss limits.

Some programs can be programmed to prioritize trades with a favorable risk-reward ratio, where the potential profit outweighs the potential loss. They diversify portfolios across different asset classes and geographies, reducing exposure to specific risks.

I also suggest that you choose a bot providing a backtesting or paper trading capability. By testing strategies on historical data, the software can identify potential risks and optimize their parameters to minimize losses.

Moreover, note that AI trading bots rely heavily on accurate data to ensure optimal performance. Poor or outdated data can lead to inaccurate predictions and suboptimal trading decisions. Therefore, it's crucial to use reliable data sources and implement robust data cleaning and preprocessing techniques to minimize errors and biases.

If the bots collaborate with an exchange or an analysis platform, make sure the partner is reliable, providing access to high-quality market data and secure APIs.

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Conclusions

AI trading bots offer a powerful tool for both seasoned traders and newcomers to the cryptocurrency market. By automating trading decisions, these programs can improve efficiency, reduce emotional biases, and potentially enhance profitability. However, it's essential to approach AI trading with caution and a thorough understanding of the technology to avoid the constant wonder of “Is AI trading legal?”.

To minimize risks, consider starting with free, built-in bots offered by exchanges like Bybit and Binance. These platforms provide a controlled environment to learn and experiment with AI trading strategies.

Remember, while AI trading bots can be a valuable asset, they’re not a guaranteed path to riches. It's crucial to conduct thorough research, continuously monitor market conditions, and be prepared to adjust your strategies as needed.

The content published on this website is not aimed to give any kind of financial, investment, trading, or any other form of advice. BitDegree.org does not endorse or suggest you to buy, sell or hold any kind of cryptocurrency. Before making financial investment decisions, do consult your financial advisor.

Scientific References

1. F. Dakalbab, M. A. Talib, Q. Nasir, et al.: 'Artificial Intelligence Techniques in Financial Trading: A Systematic Literature Review';

2. M. I. H. Chowdhury, M. Hasan, E. Bouri, et al: 'Emotional Spillovers in the Cryptocurrency Market';

3. M. Parente, L. Rizzuti, M. Trerotola: 'A Profitable Trading Algorithm for Cryptocurrencies Using a Neural Network Model'.