Harness the power of AI and LLMs in the modern trading world

Author: Max Karasev

Artificial Intelligence (AI) and Large Learning Models (LLMs) are everywhere, and the trading world is no exception.

In this article, we share some ideas of how to use the power of AI in the trading world to solve both your basic and more complex challenges as a broker and as a trader. The AI topic is extremely broad, and there are many applications. Here, we have collected a few suggestions to get you started.

After reading this article, if you are interested in a specific topic, for example, how to use AI to make data-driven risk management decisions, please email us at sales@t4b.com or let your TFB account manager know, and we will write another article specifically addressing that topic.

The fundamentals of AI and LLMs

As we delve into the integration of artificial intelligence and large language models in the trading world, it's crucial to remember that these systems are essentially sophisticated mathematical algorithms.

At the time of publishing this article, the best practice for working with LLMs is to:

• Invent the approach yourself
• Hand the implementation to the neural network
• Double-check the result

This ensures that while AI can handle complex computations and pattern recognition, human oversight prevents and corrects any potential errors.

AI in trading from a broker’s perspective

So, how can AI actually benefit brokers? Let’s look at the main points.

#1 Utility tasks

For brokers, AI systems can handle various utility tasks more efficiently than traditional methods. For example, AI excels at matching different lists of symbols from the platform and liquidity providers, identifying discrepancies quickly and accurately.

It can also scan large Excel files to detect suspicious trading activities, which might otherwise go unnoticed. Additionally, AI can provide valuable insights and arguments for and against different approaches when brokers face uncertainty in decision-making processes.

#2 Getting Insights from Big Data

Brokers can leverage AI to analyse anonymised big data from trading histories, gaining insights into trader behaviour and market dynamics. AI systems can categorise traders into different groups based on their trading patterns, enabling brokers to tailor their services and risk management strategies more effectively. Based on this data, brokers can utilise the A/B Risk Tool provided in the multiplatform Trade Processor liquidity bridge to transfer traders between different liquidity pools to mitigate risks or maximise profit potential. By understanding the profiles of their clients, brokers can offer more personalised and relevant services.

Brokers can provide user guides, configuration formats, and desired setups to the LLM, which will then effortlessly create the rules and settings. However, it is important to remember not to provide logins and passwords to LLMs. This approach works perfectly for a number of TFB turnkey solutions compatible with the TFB Toolbox, including TFB Swap Changers, Swap Free Solutions, Trade Limiters, Dynamic Leverage Changers, Credit Management Applications, and Dividend Payout Applications. For the Copy Trading Solution, LLMs can analyse a whole set of rules, even if there are hundreds, detect the chains, provide an overview, and answer specific questions.

#3 Adjusting platform settings

AI can also help brokers adjust various platform settings to better meet the needs and preferences of traders.

By providing the AI with an interface, values that could be adjusted, the resulting parameter that should be returned, and a description of the rules, the AI could be connected to practically any switch or valve inside the trading system. This allows for real-time adjustments based on market conditions with more flexibility than any traditionally coded set of rules.

AI can monitor gauges and adjust valves and switches to achieve the necessary results. This could include adjusting markups for feeding or execution in the liquidity bridge. The rules of Continuous Execution could also be tweaked for specific symbols based on the market situation for that symbol on a specific liquidity provider and how many symbols the bridge needs to execute in batches. AI can be connected to monitoring values and analysing the load and performance during news events, making on-the-fly adjustments to optimise performance and reduce risk.

AI in trading for individuals

Okay, AI is great for brokers, what about individual traders?

#1 Acquiring Knowledge

One of the most significant advantages AI and LLMs offer individual traders is the ability to rapidly acquire and process vast amounts of information. These systems can analyse market trends, news, and historical data to provide traders with comprehensive insights and educational content. For instance, an LLM can summarise financial reports, breaking news, and market analyses, saving traders valuable time and enabling them to make more informed decisions.

#2 Getting Advice on Specific Trading Strategies

AI systems can also offer tailored advice on specific trading strategies, such as setting stop-losses or other trading parameters. By analysing a trader’s historical data and current market conditions, the AI can suggest optimal stop-loss levels to minimise potential losses, recommend entry points to maximise gains, or advise when to close non-profitable positions. At times, receiving a suggestion from a machine, rather than a human professional, to close a position could be life-saving, providing direct instructions that align with best practices and market conditions.

Additionally, AI can greatly enhance technical analysis by identifying patterns and trends that might be overlooked by the human eye. It can analyse charts and technical indicators such as moving averages and the relative strength index (RSI). This can help traders make more precise decisions on when to enter or exit the market based on historical price movements and statistical probabilities.

#3 Using LLMs to build trading bots

One of the most transformative applications of LLMs for individual traders is the ability to create customised trading bots without needing to hire a developer.

Traders can describe their desired trading strategy in natural language, and the LLM can generate the necessary code to implement it. This opens up access to automated trading, allowing more traders to leverage sophisticated algorithms to execute trades based on a predefined criteria.

Here at TFB, some of our team members use ChatGPT 4 to write code ranging from utility scripts to addressing minor problems to implementing large projects for managing human resources, calculating KPIs, and managing tasks. This is done simply by describing the necessary features in natural language and then refining the provided code, all while using natural language.

Final thoughts

The integration of AI and LLMs in the trading world offers numerous benefits for both individual traders and brokers. While these systems can handle complex tasks and provide valuable insights, it's essential to remember that they are tools that should be used with human oversight. By inventing approaches and allowing AI to handle the implementation, while always double-checking the results, traders and brokers can harness the power of AI to enhance their strategies and operations effectively.