THE GIST of Editorial for UPSC Exams : 08 JANUARY 2019 (Disruption of mutual funds through algorithmic models)

Disruption of mutual funds through algorithmic models

Mains Paper 5: Science and Technology
Prelims level: algorithmic models
Mains level: Awareness in the fields of IT, Space, Computers, robotics, nano-technology, bio-technology and issues relating to intellectual property rights

Context

•  Algorithmic or automated trading refers to using a computer program that automatically submits trades to an exchange without any human intervention.
•  This ensures that human beings’ emotions are not triggered while making the investment or trading calls and, instead, the computer program is able to place trades with a level of speed and precision that a human could not hope to achieve.

Impacts of Algorithmic trading

•  Algorithmic trading is popular among institutional investors in India and covers 35-40% of the turnover on our exchanges.
•  Early in 2018, the Securities and Exchange Board of India (Sebi) had probed the algorithmic trading platform available on the NSE and had found that some investors had unfair access to market information and trading systems.
•  Since then, Sebi has instituted a stronger regulatory framework for such trading.
•  Globally, traditional asset management could well be an industry ripe for technological disruption by using smart algorithms.
•  Algorithms armed with computing power can extract value from big data by recognizing and unearthing patterns from the ever-changing construct of financial markets, thereby making the human “investment officer” obsolete.

Exploration in behavioural science

•  Khan has been on a course of exploration in behavioural science, financial theories and quantitative models, the result of which, he claims, is an algorithm-based investment model suited to the global long-term investor.
•  According to him, the model is grounded in the fundamental performance of companies and in the behavioural constructs of stock price movements.
•  These behavioural constructs are not based on technical analysis, but on the long-term statistical data behind stock performance.
•  By contrast, pure algorithmic trading focuses on short-term market anomalies or arbitrage opportunities.
•  Considering the speed of development in Artificial Intelligence, Khan believes that large-scale analysis of historical fundamental performance and behavioural constructs is now technologically feasible. Moreover, the absence of asset managers and their minions from such “algorithmically managed” investments will mean that fund costs are kept low for the investor. The “secret sauce” will lie in the algorithmic model’s construct.
•  Khan says that industry leaders such as Larry Fink of BlackRock, Inc. and Paul Tudor Jones of Tudor Investment Corp. have seen the light and are opening up more of their portfolios to algorithmic long-term investment.
•  The Indian asset management industry on the other hand, he says, has been extremely slow and hesitant to adopt to the changing trends shaping global markets.

Conclusion

•  The technology roadmap he plans is to scale his algorithms to provide a robust mechanism to innovate and roll out multiple thematic “quant” and “smart Beta” strategies that can be offered as funds.
•  ETFs and index funds are depending on the maturity of specific buyers.
•  By go to the market approaching both institutional investors, such as family offices and pension funds, as well as small to medium-size funds, including existing registered investment companies and “long-only” hedge funds.
•  The startup’s idea seems a fine one, but the actual technological and operational execution of it is where success will lie. This will be Khan’s real challenge

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Prelims Questions:

Q.1) Which of the following areas employs blockchain technology?
1. Automobile
2. Bitcoin
3. Electronic voting machine
4. Aerospace

Select the correct answer using the code given below.
(a) 1 and 3 only
(b) 2 and 3 only
(c) 1, 3 and 4 only
(d) 2 and 4 only

Answer: B

Mains Questions:
Q.1) Algorithms can spot patterns from the ever-changing construct of financial markets, making the investment officer obsolete. Examine this statement.