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Why Big Data is the Key to Algo Trading?

Capital Markets CIO Outlook | Friday, October 23, 2020

Big data incorporation in algo trading is resulting in highly optimized insights and recommendations for traders.

FREMONT, CA: Algorithmic trading is guided by a computer program that follows a pre-defined set of instructions or algorithms to execute a trade. Theoretically, algo trading can generate profits at a pace and frequency that is impossible for a human trader to match. Investment firms use algorithmic trading to derive business investment decisions based on insightful data. Analytics and risk assessment are essential components of any investment decision. Advanced analytics

will also offer significant insights to the investors who are relying on algo trading for their investment decisions. With a massive amount of data generated in the market, big data can offer immense value to the analytics efforts.

With a highly dynamic market space and minimal tolerance for errors, real-time analytics offers a precise report of the market proceedings to the algo traders. It has to be done so quick that trade decisions must be made in near real-time. It is almost impossible for the analytics solution to recommend optimized insights to the traders without the help of big data technology. At present, algorithmic trading has become almost synonymous with big data with the rise in the advancement of trading solutions. The automated systems enable algorithms to process financial trades at lightning speed.

Investment firms can utilize big data capabilities to incorporate massive amounts of historical data. Such data is used by the firms to test their strategies before those strategies can be used in real market scenarios. With big data, traders can get a better idea over the useful data that must be fed to the trading algorithms. Clear data-based decisions can enable the traders to make logical decisions without letting human emotions to impact their trading decisions. Further, big data may extract useful data that spans over a wide range of industries. For instance, big data can offer alternative data that can be fed to the trading algorithm enabling them to consider greater risks. Trading algorithms that make decisions based on refined data sets are bound to have better chances of success.

Thus, big data has a massive potential to enhance the trading algorithms as the algorithms will offer highly optimized trading recommendations to the traders.