Can we trade with ChatGPT?

The answer is sort of. ChatGPT is very smart and sophisticated, but it does not have access to the internet or any information before 2021. ChatGPT also warns users that the program is 'not able to provide personalized financial advice'. Without being able to analyse news or new data as it appears this means that ChatGPT has the potential to produce unreliable results. This becomes a serious risk when being asked to handle important financial calls which have serious implications for the user that is relying on the algorithm to function productively.

This means that ChatGPT falls short of being an effective tool for assessing instruments or the larger market in the context of current events. However, while ChatGPT cannot be used as a personal trading assistant, it can be used to streamline many of the workflows that a trader will go through. For example, it can be used to summarise large amounts of information and therefore can save traders time in responding to data and report releases that inform trading decisions. Alternatively, traders can already use AI tools that are specifically designed to execute trades. This is known as 'algo trading'.

Here are a few examples of how it can be used to gain an edge in the market:

Algorithmic trading, or algo trading for short, is the use of computer programs and algorithms to automatically place trades on an exchange. These trades are based on a set of predetermined rules, which can be as simple as "buy on a dip" or as complex as a multi-factor model that considers a wide range of market data. The main advantages of algo trading is speed. Because the trades are placed automatically, they can be executed much faster than a human trader can. This can be especially beneficial in fast-moving markets or when there is a large amount of trading activity. Algo trading also helps to minimize the emotions that can often influence trading decisions. By following a set of predetermined rules, algo traders can avoid making impulsive emotional decisions.

However, using AI to trade ultimately requires a significant amount of upfront investment and expertise in order to set up the necessary infrastructure, including high-speed computers and sophisticated software. Algo trading also relies on the accuracy of the algorithms and models used, which can be affected by factors such as data quality and market conditions. The rules an AI is programmed to operate under can easily change from perfect to disastrous in changing market conditions which means algo traders must constantly monitor and adapt strategy to produce the best results.

It can be trained on historical market data to identify patterns and make predictions about future market trends. This can be used to inform trading decisions and identify potential opportunities.

It can be used to analyze social media and news articles to gauge market sentiment. This can provide valuable insights into how investors and analysts feel about a particular stock or sector.

It can be used to optimize a portfolio by analyzing past performance, market trends and other factors to make recommendations on what assets to buy, hold or sell.

It can be trained to identify potential risks in the market, which can be used to make strategic decisions to minimize losses and maximize returns.