5 Ways Data Science Is Changing Financial Trading (2024)

Big data is on a path to changing everything. From advertising and technology to healthcare and our daily lives, information is making an impact.

We finally have the technology and means to collect infinite amounts of data from all facets of life. Plus, we can put it all together to be easily understood and implemented. The changes this information creates can make nearly anything more efficient, including trading.

Financial trading is a precise job that can’t afford many mistakes before falling apart. That’s why people are starting to implement data and artificial intelligence to help out. That way, everything can be done faster and better — without cutting corners.

Here are just a few examples of how data science is making massive changes in the financial trading industry.

Data about financial trading doesn’t just cover prices and fluctuations. It also tries to understand why costs fluctuate the way they do. Rates are often a reflection of supply and demand. Social and political trends can also affect sales. However, the reasons behind the supply and demand could be assessed and possibly fixed.

This data collection process paves the way for creating predictive models. Data can start observing trends while machine learning spots early patterns humans could easily miss. The prediction that something’s going to rise or fall can lead to safe, smart decision making in the future.

The massive amounts of data make the financial trading world more predictable. As a result, stock trading has made some significant changes. Artificial intelligence can now act as personal stock advisers.

The software can observe patterns, trends and likely outcomes in regards to money. The AI can make these assumptions thanks to the correlations across underlying stocks and how previous patterns work with current trends.

AI’s impact on the stock market doesn’t stop with predicting where stocks will go, though. The data can tell you a reasonable trading price, no matter if you’re buying or selling. Using this information, you’re likely to take fewer risks and get higher returns. If you like to play the stock exchange safely, an AI adviser might be a good idea to look into.

Technology has advanced society immensely in the modern age by keeping everyone connected around the world.

A conversation between two people on different sides of the globe can be held instantly — unlike 40 years ago. The constant sharing has lead to rapid advancements, including the financial trading sector.

Financial trading has always been extremely fast-paced, especially when discussing the stock market. Now, you can get information back instantly, too. Real-time data can grant you better, faster decision making. Thanks to AI providing only essential and relevant information, errors are automatically reduced.

We’ve yet to really get a grasp on how machine learning is changing financial trading.

The first thing to understand is that the technology isn’t artificial intelligence, but rather a subset. Machine learning is the part the recognizes patterns and comes up with predictions based on amassed data.

We’ve already made leaps with machine learning. The reality, however, is that we’re still on the cusp of this technology’s full potential. Big companies are just now jumping on the AI train. In late 2019, JPMorgan implemented its first robot to complete trades across its global equities algorithms business.

JPMorgan is a big company, but it was not the pioneer of AI in the financial trade sector. A lot of companies work with AI to make the best financial trading decisions possible. Some of them continue to experiment with new ideas, pioneering steps the rest of the world is slowly starting to take.

Greenkey Technologies, based out of Chicago, has started using speech recognition and language processing with the interest of saving as much time on the trading floor as possible.

Meanwhile, Auquan out of London hosts a data science platform that allows anyone to showcase their algorithms and get ideas flowing. AITrading, also in London, uses AI to increase profit from trades and maximize opportunities. Needless to say, there is a lot of machine learning already happening in financial trading.

As we learn more about artificial intelligence and machine learning, we become more efficient in the work we’ve always done.

Financial trading has been around a long time and isn’t going anywhere anytime soon. If you want to remain sustainable, optimizing the process is the only leap forward that’s possible to make.

When it comes to this much money in the trade sector, you can’t afford to make mistakes or find problems at the last minute.

Working with the best information on hand — and software able to detect hidden patterns — is always the right call.