India has around 10 crore registered stock market customers and around 17 crore Demat accounts with many clients holding more than one Demat account. Soaring stock market indices and changing investor behaviour, especially after demonetisation and Covid years, have contributed immensely to the new-found love of Indian investors for stocks. Around 4,900 stock brokers cater to approximately 4.46 crore active users, according to the NSE. New DIY investors bet on discount brokers and various sources for money- making ideas, whereas experienced and well-heeled investors bank on traditional full-service brokers to deal in stocks. Many investors, especially the new ones, believe that Big Data and its mining will help them make smarter investment decisions and maximise profits in the coming years.
What is big data? How ‘big’ is it? How can this humongous data pile be analysed to get valuable insights? How will it help investors make smart decisions? Let us delve deeper to understand this better.
We live in an interconnected world where everyone is connected via the internet and is always transacting or consuming something online. All these activities generate unimaginable amounts of data – structured, unstructured, semi-structured – that is growing at a magnitude that most of us can’t even comprehend. For example, we deal with Megabytes (MB) and Gigabytes (GB) on a daily basis. But here we are talking about data in Terabytes and Petabytes. That is the world of big data.
As you would have guessed, it isn’t humanly possible to clean up, format, analyse, and use the data on a real-time basis to make the investment journey better. We need to seek the help of machine learning, artificial intelligence, and special tools to make sense of diverse data sets and enhance the speed and capability of the decision-making process. ‘Big Data’ should become ‘Smart Data’ to magnify the wealth generation process for regular investors.
Large institutions are already building, albeit in a small way, new investment models using Big Data analytics. Brokerages and investment managers use a huge quantum of financial data, already available in real- time, for efficient fund management. Readily available information like financial reports, earnings reports, disclosures, historical records, and market behaviour, among other things, can be analysed in a structured manner, accelerating the decision-making process. Many institutions have started using data-oriented models to evaluate securities based on real-time events.
Institutions are investing in analytics to evaluate the impact of various factors on stock prices. Portfolio managers are building investment models to assess risk in real time and using data to test their investment hypotheses. Indian mutual funds, portfolio management services (PMS), and brokerages are adopting data-driven fund management solutions, while fintech firms are leveraging this to offer diverse investing options. There is a growing consensus that data-driven models may emerge as an alternative to traditional alpha generation for investors.
The growing prominence of big data analytics will be crucial in guiding investment decisions in the years ahead. Sophisticated predictive models, risk assessment tools, and behavioural analysis will enable investment experts to anticipate and respond to shifting market dynamics. Indeed, these professionals are already experimenting with such cutting-edge techniques, poised to achieve meaningful breakthroughs in the near future.
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However, the question to ask is – can managers truly remove all emotion from their investment decisions by relying solely on dispassionate data analysis? While abundant data sets and advanced analytical tools may expedite decision-making, they will not eliminate the need for human intervention.
Experienced professionals will continue to add value and make a meaningful impact through their in-depth knowledge and the application of robust processes, even as data-driven decision-making becomes more prevalent.
Views expressed by Sandeep Chordia, Chief Operating Officer (COO), Kotak Securities
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