A STUDY ON BIG DATA ANALYTICS IN CAPITAL MARKET

Abstract

Today’s capital market industry is facing new and increasing challenges, including tighter regulations, higher capitalization rates, changing customer demographics and pressure to grow revenue. Overcoming the obstacles and capitalizing on new opportunities in capital markets demands the right technology to deliver trusted, timely and authoritative capital markets data without increasing data management costs. Big Data’s embrace of existing data models and potentially new ones appears, in the eyes of many data architects, to qualify it for consideration as a solution to this kind of data consistency issue. To accumulate capital, generate high portfolio returns for investors and mitigate risks within regulatory boundaries, financial institutions need high-performance IT infrastructures that meet complex analytical and “Big Data” requirements. With a Big Data platform, stock market traders and investment portfolio managers can process vast amounts of unstructured data to identify the best companies in which to invest. Unstructured public information like company news, product reviews, supplier data and price list change can be processed en masse as Big Data, producing mathematical models that help traders decide which stock to buy or sell. This article addresses the following research questions: (i) How does Big data create value for Capital Market? and (ii) What are the Implementations of Big Data Analytics in the Capital Market Industry?