Three Ways on how Big Data Analytics can be Beneficial for Financial Trading

Since algorithmic trading does not have any restrictions, it can use structured and unstructured data to perform tasks like tracking social media activity, news analysis, and producing stock market data.

Fremont, CA: Data analytics is the method of gathering, analyzing, and processing data and is used extensively by various industries. Big data analytics processes vast and unorganized datasets which is impossible for legacy software. Also, it proves profitable for industries that rely on changing consumer behavior because it produces useful insights.

Big data analytics ensures obtaining correct insights so that analysts and traders can make smart decisions as financial trading is controlled by algorithms' computational powers. Here are three ways how big data analytics can be beneficial for financial trading services:

Machine Learning

Adopted by just a few firms, machine learning includes computers or systems learning to carry out tasks without human intervention. The computer can learn from past errors, evaluate the situation of investment, and make decisions for investments using machine learning. As this technology is still at the nascent stage, the implementation of big data analytics in machine learning has a positive prospect.

Algorithmic Trading

Algorithmic trading includes the computational process through algorithms that produce profits at a speed and frequency which surpasses human capability. By incorporating big data analytics into algorithmic trading, individual traders can gather powerful insights. And since algorithmic trading does not have any restrictions, it can use structured and unstructured data to perform tasks like tracking social media activity, news analysis, and producing stock market data.

Technical Analysis using Big Data

Existing financial trade analysis not only evaluates the asset price and behavior but also involves examining the social and political trends, recognizing the support and resistance level, and checking clients or stock market behavior. Because many components are gathered for improved data analytics, the data produces is tremendous.

Consolidating big data into the technical analysis will encourage precise predictions to help traders and investors to plan out an approach that can reduce the risk related to financial trading.