How AI is changing the trader’s world

In the past couple of years, AI has become an extremely hot topic, with the November 2022 release of OpenAI’s ChatGPT a particularly significant watershed moment.

Since then, individuals and businesses around the world have been watching excitedly for the release of new AI products that can assist with or even fully automate a wide range of tasks - including traders.

What is AI’s role in trading today, and what are some of the computer-assisted trading technologies that have preceded it?

At Alpari, we are thrilled by the opportunities that AI offers traders, so we’ve decided to put together a guide to some of the technology that is available today and it’s being used, from individual traders in FX, commodities, stocks and more to the world’s biggest hedge funds.

 

Advantages of AI tools

As we will see later on in this guide, specific tools have been developed for different purposes, but overall, traders can access numerous benefits by adding AI technology to their trading strategy.

• Filtering opportunities: AI tools can help you decide which trading or investment opportunities to go for, by presenting you with options that fit all the parameters you’re looking for. The first chatbots are now coming out that will make recommendations to you verbally, based on data from successful trading and investment moves. However, this technology is still very new.
• Research tools: There are tools that can parse news stories to determine trader and analyst opinion on opportunities, speeding up the research process and helping traders see at a glance what others are thinking about certain stocks, commodities, indices and Forex pairs.
• Trade faster and in higher volumes: Large hedge funds that have access to powerful data centres will be able to get the most of this AI benefit. Computers that are equipped with the best technology will be able to carry on many more trades at incredibly high speeds.

 

Alpari’s Pro Trading Tools

Traders who use our service through MetaTrader 4 or 5 can access a range of powerful tools from FX Blue. You can also use tools from TradingCentral which are not available to traders directly, and which can only be accessed by traders who have an account with a broker like Alpari that has partnered with TC.

TradingCentral offers TC Crowd Insight®, a tool that harnesses the power of language processing to help give you a quick, thorough overview of what people are saying about different investment opportunities.

It works out the Sentiment Signal (bearish or bullish), Sentiment Score (how strong the sentiment seems to be, on a scale from 0-100), Subjectivity (is the general opinion rational or irrational) and Confidence Index (how much weight these opinions hold based on how many news outlets have shared their opinions).

FX Blue offers a suite of tools that can be used within MetaTrader 4 or 5, including the ability to look at all of your Forex trades at once and take actions across all of them at the touch of a button, such as closing all losing trades.

FX Blue tools show you trader sentiment and technical analysis on any FX combination you want, and you can also create sophisticated charts to visualise detailed information. The inbuilt Market Scanner tool allows you to scan multiple markets for any technical indicators of your choice.

Let’s get into some other types of technology that traders are using today.

 

MetaTrader Expert Advisors

MetaTrader Expert Advisors are a popular type of add-on for MetaTrader 4 or 5. These applications, made by independent developers, analyse price data, searching for Forex, stocks, indices or commodities according to the parameters they have been programmed with.

They can even trade on your behalf. There is, as with any trading, a level of risk involved in using Expert Advisors, but you can select them based on different levels of risk, and you can also read reviews from other users. 

 

High-frequency trading

High-frequency trading is often used by large hedge fund companies. This trading method depends on powerful computers that complete millions of trades within the space of a few seconds.

The trades are based on algorithms, making this a specific type of algorithmic trading which can less easily be carried out by individual traders and investors.

 

AI for commodities trading

Earlier this year, the chief executive of commodities trading group Vitol told the Financial Times that the industry was currently engaged in an AI “arms race”.

This sector is most interested in tools that can process large amounts of data at once, so that traders can capitalise on in depth information about all the factors that can affect their trades, from weather to global interest rates. 

 

Simulations

Traders in all markets can benefit from tools that can simulate what would happen in the future if certain variables were met, thoroughly testing trades before committing to them. 

 

A brief history of computer-assisted trading

 

1971: The Nasdaq, the first electronic stock exchange, is established.

 

1987: Black Monday (October 19, 1987), a major stock market crash, is partly attributed to program trading, an early form of algorithmic trading which uses computer systems to execute large orders based on predefined conditions. However, opinion is divided today on whether the method was to blame. 

 

1992: REDI, one of the industry’s first electronic order entry systems, is launched by Spear, Leeds & Kellogg, later acquired by Goldman Sachs.

 

1998: The SEC allows Electronic Communication Networks (ECNs) to compete with traditional stock exchanges, boosting algorithmic trading's adoption. Companies begin using algorithms to facilitate faster and more efficient trades.

 

2001: Decimalization of stock prices (shifting from fractions to decimals) makes it easier for algorithms to trade in smaller price increments, increasing high-frequency trading (HFT).

 

2005: Regulation National Market System (Reg NMS) by the SEC encourages faster trading, helping algorithms thrive.

 

2007: Algorithmic trading accounts for over 30% of equity trading volume in the U.S.

 

2010: The Flash Crash in May 2010 causes the Dow Jones Industrial Average to plunge nearly 1,000 points in minutes, which may have been partially due to a massive sell order executed by an algorithm. 

 

2012: The SEC establishes a limit-up/limit-down mechanism to prevent extreme price swings and implements circuit breakers to stabilise markets during volatile conditions.

 

2012: Knight Capital Group suffers a $440 million loss due to a trading algorithm error, further underlining the dangers of faulty code in algorithmic trading systems.

 

2014: Michael Lewis's book "Flash Boys" brings mainstream attention to high-frequency trading (HFT), sparking debates about fairness in the markets.

 

2016: By this point, approximately 80% of all Forex trading is algorithmic.

 

2019: Algorithmic trading accounts for 60-73% of trading in the US, according to Wall Street data.

 

2024: The rise of chatbots. AI startup Bridgewise launches a chatbot called BRIDGET that will provide investors with regulatory-compliant insights, including Buy/Sell recommendations. 

 

Final thoughts

Before you decide to take the leap into using AI tools, make sure you do your research and make an informed decision.

If you are not yet a trader but you are interested in getting started, you can make a demo account on MetaTrader 4 or 5 through Alpari to practise before you start trading.

You can even install a robot Expert Advisor on your demo account, and learn about how to use these tools to either identify suitable opportunities or carry out the trade for you.