Imagine being able to go about your day and know that a computer is making you money. You don’t need to sit in front of it, you can go golfing or into the office and know that back home you are potentially scoring extremely valuable stocks. This is now being accomplished through trading algorithms.

Algorithms are a clear set of instructions telling a computer what to do and when to do it. Algorithmic trading is a new use of Big Data in finance. The theory behind algorithmic trading is that a computer is set up with algorithms giving defined rules and parameters on when to trade or sell. Computers can scan through stocks and pick out stocks that have dropped or risen in price to buy or sell at the precise time to ensure optimal earnings.

Through this process investors are learning how to rely on these algorithms to make trading decisions and act much quicker than any human can. Using computers also takes the human emotion element out of the equation, leaving objective data to make decisions.  Although this sounds like an intriguing way to make money, one must also be very cautious when trusting a computer with their money. Investors are encouraged to learn coding to make their own customized algorithms and systems that have set perimeters and conditions. This would be the only way to securely trade without a high risk of a possibly devastating malfunction.

This trading process is just another way Big Data is revolutionizing the financial industry. To learn other ways Big Data is influencing the Finance industry make sure you read Business Optimization, Customer Satisfaction and ROI. 

Big Data

Change Is Great Be First Free Book

Big Data Book - First 3 Chapters Free!

Ready for painless change?

For a limited time we are offering our book "Change is Great, Be First" by Richard Batenburg.

Please fill out the form to join our mailing list and receive the first 3 chapters of the book for free.

Be sure to confirm your email address.

Success! Now check your inbox and confirm your email address to receive the book.