Get rich on the stock market using Big Data Analytics

By Muqbil Ahmar

Who hasn’t heard of people reaping millions on the stock market overnight? What do winners do differently that distinguishes them from losers? They performers are able to predict stock behavior accurately by successfully interpreting stock data coming from all sources and have the ability to deduce relevant patterns from it. To do it consistently one would either require pure brilliance or knowledge systems cultivated over years of experience on the stock market or just be pure lucky.

Wouldn’t it be incredible if one could make accurate stock market predictions regularly? Is it possible? Yes, it is. And the best part is that you don’t need long years in the trade or an Intelligence Quotient of more than 9. Today, modern technology such as Big Data and Analytics can aid financial institutions as well as individuals make sound investment decisions, which yield consistent returns, by giving them insight into the data.

Big Data and Cloud are essential to your well-being
Increasingly greater number of people are investing in bonds and mutual funds to save taxes. At times, the financial well-being of families depends on good returns from investments. In order to reap good returns, an investor needs to have sound knowledge about the functioning of the stock market to be able to make sound decisions. But individual investors often don’t have the financial heft of big institutions to hire data scientists. In such a situation, these technologies become indispensable as they don’t break the bank.

How does it work?
With the ever-expanding capabilities of computers to handle data, automated computer programs perform stock trading at the best possible prices at speeds that a human broker cannot. This is achieved by feeding Big Data from various sources into algorithms and statistical models, which analyze it. Enormous amounts of historical data are fed into complex mathematical models. Algorithms such as Apriori, FPGrowth (Frequent Pattern Growth) in conjunction with analytical statistical methods such as Lift, Kulc, IR, and Chi-square decipher the patterns deciphered to provide accurate predictions of stock behavior. The greatly refined statistical methods factor in real-time news, updates from social media apart from the frequently changing stock data. And since the process is automated, there is no possibility of human error or manipulation—making investments less risky.

While predictive Analytics is beyond the reach of small investors, there are reasonably priced applications that abstract intricate data through mathematical tools. Some applications have the ability to perform high-speed Analytics on historical and real-time stock data to provide in-depth understanding of how a particular stock is behaving. Then this information is co-related with sentiment analysis from social media inputs so that a 360-degree analysis can be achieved on stocks. This data is huge, consisting of billions of records of stock ticker information and live twitter feeds.

However, the usage of Big Data Analytics in the Indian scenario remains limited.

“New technology such as Big Data Analytics are gaining traction in the market. The process has definitely started but there is a long way to go. There is still lack of awareness about such technology in India, whereas in the Western world, it is used quite frequently. I would suggest investors to start relying on such fool-proof methods. There is a need for raising awareness, standardization of tools and setting up of cross-functional Big Data Analytics teams to push growth in this direction,” said Somesh Misra, VP, Operations, Deskera, a software company producing Analytics tools.

Big Data: structured or unstructured
According to a study, the New York Stock Exchange generates 1 terabyte of data every day. The study also found that 92 percent of world data traffic is due to 2.5 quintilion bytes of data created on a daily basis. It is humanly impossible to decipher such humongous volumes of data. Investment banks and asset management firms hire Analytics tools and specialized teams to analyze and interpret such huge volumes of data to make good investment decisions. A major chunk of such data is of little value, is unstructured, and cannot be fit into a predetermined mathematical model. It is only a small part of the data that is structured and which can be managed through relational databases and spreadsheets. Analytics tools weed out the non-actionable data and then run the remaining through algorithms.

No wonder stock markets and financial institutions such as banks and insurance firms are increasingly relying on such Analytics tools for active risk management.

Big Data Analytics reforming industries
The application canvas of Big Data Analytics is boundless. It has already started affecting a number of industries. It is actively changing the landscape of several sectors such as Healthcare, Insurance, and Financial markets. According to a survey conducted by Deskera among small and medium enterprises 67 percent believed that enterprises having an Analytics strategy may have a competitive edge in the market.

With over 10 years of experience in the field of journalism, the author is a Senior Editor at Deskera, a business software company. 

Updated Date: Jun 23, 2016 14:01 PM

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