How is Big Data Analytics Used for Stock Market Trading?


The subject of big data analytics applications in stock market trading can be seen by different users differently.

On the one hand, the data analysts and data collection officers will be concerned about correct modeling and collecting the correct data. On the other hand, investors want results.

So how is big data analytics applied in stock market trading?

To picture what goes on better, think of the people who are the brain behind the data modeling and analytics try to understand key decisions that experts make, and why they make these decisions.

With this knowledge, they’re able to create tools that can aid the trader. Later on, with enough data and visualization, the impact of data analytics can produce even greater value.

Here is how;

1. Model expert performance

The first step in using big data analytics is getting to know which data is should be collected and modeled. Here the computers learn from experts with the aid of the data experts.

2. Create a clearer picture of expert decisions and why they work

With enough real-time application, the well-designed system should be able to aid in presenting information well enough to investors and they can see patterns and begin to learn from the big data.

Here individuals will get great data visualization and may be able to make insightful decisions about which signals and indicators perform better.

3. Gives traders insights on where to look

At this stage, with tools for visualization and reporting up and running, you would expect the experts to know if the model needs update and traders may already have some insights of things to improve and where to look in search for greater performance.

4. Gives Resources for AI to learn

So, you have a great business intelligence tool that has worked for some time and has been used in predicting trade decisions. The next stage will be to prepare all the real-world data that you have gathered and try to use it to teach the machine instead of doing it through only database analytical tools.

AI can perform better than only database systems because it can go a level deeper than the set operation and search operation of the database. But the most important thing is getting the training routine right.

5. Use AI and Machine Learning to predict the market

Finally, you can get the machine to help make those insightful selections and sorting decisions for you. You’ve had enough data to test its ability to help in making trades with all the parameters. The real test comes when you use AI in predicting which stocks to buy or sell.

Traders can plug into their computers today and feel more confident using data analytics tools that help them in their day to day trading.


Tools like Power BI are available free and it gives traders the ability to create stock market reports and analysis. Business intelligence tools like Power BI gives traders and stockbrokers more power and advantage in the financial market.

AI use with most of these tools and they are improving faster. In the future, it will become a big asset for companies who invest in them.

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