Big Data & Robotics — Tool that may aid you trade better

B Gopkumar

Investing in stocks has been a bitter experience for retail investors to date. In fact, the direct participation of retail investors in the stock market has sharply dipped. Of course, one of the reasons is lack of access to proper research before investing and blindly following “tips or advice” from friends and other participants.

Stock market investing is still a segment where technology and mobility are yet to result into significant convenience for a large set of investors, especially in the retail segment.

The existing technology or powerful trading terminals have been out of reach of retail investors owing to their cost as well as technical know-how. Information and knowledge assistance gets limited to a few elite institutional investors. This disparity is also visible in the investing behaviour of the institutional and retail segments.

In the past few months, we have already seen how technology, access and mobility have initiated a revolution in the way Indian banks transact -- from cheques to cards to mobile wallets as well as pay-through-phone terminals. The banking industry, once considered immune to technology disruption, is already staring at the block-chain technology.

Technology doesn’t only offer convenience but more importantly, bestows an opportunity to assimilate, analyse and compare diverse data points to predict changes or improve behaviour.

Stock markets have always been at the forefront of technological adoption when it comes to managing the backend (transactions, settlement and risk management). However, when it comes to facilitating behavioural changes among the investors or delivering on the narrative of informed investing, the technology has been largely scattered, expensive or simply inconvenient for mass adoption. But then, the change is inevitable and what’s imminent is the advent of big data and analytics aimed at the retail investors. Powered by robotics and a customer-friendly interface, vast amounts of data can be processed and be made accessible towards benefiting the investment behaviour.

Understanding Big Data & Analytics and Robotics

We live in the AG (After Google) age, where access to any information is only a search away. In fact, free financial data on almost every publicly traded company is available on various portals. Big data solutions use these data sets that are too large and complex to manipulate or interrogate with customary methods or tools. To define big data, it’s a science of examining raw data with the purpose of drawing conclusions about that information. The adoption of big data continues to redefine the competitive landscape of industries. Financial services, in particular, have widely adopted big data analytics to make better investment decisions with consistent returns.

In the stock market, data analysis and analytics are used more as a technical analysis tool to check historical data to identify similar patterns or signal and see how prices have responded to it. Trades are taken based on the ‘history-repeats-itself’ strategy. Most technical analysts who trade on pattern recognition also work on similar logic. But data analytics help investors execute the trade on a real-time basis and on multiple stocks. These analytics do not rely on price alone, but uses other variables such as volume, delivery data, technical signals and market sentiments while executing trades. Risk management is also taken care of by the software which brings in the discipline and removes the emotional quotient from the trade. Robotics and analytics go a step ahead and start predication based on the big data collected.

Programmes are now able to read and interpret news and initiate a trade. With Google, other openly available information from social media sites is used as a source of information which the software then interprets as either being bullish or bearish. Big brokerage firms use these big data and analytics during the quarterly earnings season, as market generally tend to give a knee-jerk reaction when the numbers are announced and there is a variation to analyst estimates.

Become an ‘evolved trader’

Data analysis separates the grain from the chaff, analyses and compares the data on a historic basis and executes trades accordingly.

Globally, big brokerage houses use such software to trade on proprietary funds or to deploy funds in discretionary trades through a portfolio management service or through creation of a hedge fund structure. In India, similar structures are beginning to sprout. We believe sooner or later everyone would think of ways to use big data to predict stock market movement in an effort to cash in on a near-certain future or to run from a stock market crash before it hits. We believe that retail investors should get ready for the change.

The author is CEO, broking and distribution business, Reliance Capital. The views expressed in this article are his own.