Weakening the faith of gullible investors

Indian stock indices hit fresh high; eyes now on inflation data, Q4 earnings --- Representational Photo

Surfacing of irregularities at the country’s stock exchanges is not something new. It’s only the matter of time that the scams are unearthed and culprits, especially the white collar criminals, are spotted and booked.

But not before the damage has been done extensively, more particularly to common gullible investors who remain unaware of the tricks played by the influential market players, both inside and outside the system.

   

For instance, the market players such as Harshad Mehta and Ketan Parekh are big names when it comes to the exploitation of the system from the outside.

Scams have also been surfacing up which demonstrate how the people inside the system have been playing fraud by misusing their authority to make profits for themselves.

The latest scam in the series has surfaced up at the country’s largest stock exchange, National Stock Exchange (NSE), in which its former MD & CEO, Chitra Ramkrishna, has been sent to 14-day judicial custody by a Delhi Court in connection with the co-location scam case. Chitra Ramkrishna was MD & CEO of the NSE from April 2013 to December 2016.

Notably, the Central Bureau of Investigation (CBI) is probing the alleged improper dissemination of information from the computer servers of the market exchanges to the stock brokers.

In the co-location facility offered by NSE, brokers could place their servers within the stock exchange premises giving them faster access to the markets. It is alleged that some brokers in connivance with insiders abused the algorithm and the co-location facility to make windfall profits.

Allegedly select players obtained market price information ahead of the rest of the market, enabling them to front run the rest of the market. The alleged connivance of insiders by rigging NSE’s algo-trading and use of co-location servers ensured substantial profits to a set of brokers.

In such a situation, the trading members were able to capitalize on the advance knowledge and the overall default amount through NSE’s high-frequency trading (HFT) is estimated to be Rs.500 billion over five years.

Notably, today stock trading is now being done in one thousandth of a second through computer-driven advanced trading techniques such as high-frequency trading (HFT) and Algo (algorithmic) trading.

With the help of algorithmic and high-frequency trading strategies, stock traders are getting faster access to streaming real-time market data and are executing orders in milliseconds.

What’s Algo trading? Let me borrow a simple definition. Algo trading is an automated trading system that utilizes very advanced pre-programmed mathematical models for making transaction decisions in stocks, currencies or commodities. It simply refers to the use of automation for trading in stock markets.

This entails execution of a trading strategy using a computer programme (algorithm). Algorithms are used for speedy execution of trades and faster identification of arbitrage opportunities.

This kind of trading involves two stages: identification of a buying or selling opportunity which entails what and when to buy or sell and how the trade will be executed.

What is high-frequency trading (HFT)? There’s not too much of a difference between Algo and this kind of trading. While Algo trading uses pre-programmed mathematical models to track real time market data, HFT employs superfast computers to track even the minutest price discrepancy in stocks, currencies and commodities, and execute orders in a millionth part of a second in order to make profit by quickly buying and selling stocks at the slightest price differential. This means while every HFT is algorithmic, every algorithmic trade is not necessarily high frequency.

It’s worth mentioning that this automated trading system came under sharp criticism of common retail investors who stated that this kind of technology breeds discrimination between rich brokers and common investors.

The main argument has been that algorithmic trading has created inequality because small investors can’t afford such trading software. This has invited debate where technology savvy stock traders call the inequality argument as frivolous.

On one hand, fears of misuse of these technologies and large institutional investors getting undue advantage over small investors who lack access to these sophisticated technologies has always loomed large. On the other hand, these computer-driven advanced trading techniques are bringing more volume and liquidity in the equity market.

Now, let’s have a broader look at the menace of insider trading. All of us know about the unpredictable and ever changing nature of the stock market. It’s the market which lives with a life of its own, reacts to situations and leaves investors either reaping profits or with nothing at all. Though there are certain economic and financial indicators like inflations, interest rate scenarios etc that contribute to the movement of stock prices, a lot remains hidden behind this price movement game.

A listed company’s corporate information is one of the most vital things for an investor. Stealing of this corporate information especially by those who are custodians of such information and passing it on illegally to the selected people is one of the oldest crimes in the world of investments.

Insider trading is viewed as a serious white-collar crime. It ‘implies buying, selling and dealing in shares and securities of a listed company by insiders such as directors, designated officers of management team, employees of the company or any other connected persons such as auditors, consultants, lawyers, analysts who possess material inside information which is not available to general investors’.

This trading takes place when those privileged with confidential information about important events use the special advantage of that knowledge to reap profits or avoid losses illegally and unethically on the stock market, to the detriment of the source of the information and to the typical investors who buy or sell their stock without the advantage of inside information.

For example, if one of the top executives of a company shares with you some kind of material information of the company which is yet to be made public and can have impact on the share price of the company, you are now every bit as much an insider as he is, with respect to that information.

Firstly, it is illegal on part of the management executive to share the company’s material information with you before it becomes public knowledge. Secondly, it is equally illegal for you to do so because you are now a “temporary insider”.

This remains true regardless of how many times the information is passed. Legally, anyone who has material information is prohibited from trading, based on that knowledge, until the information is available to the general public.

Meanwhile, the surfacing of the latest scam at NSE involving its former MD & CEO Chitra Ramkrishna allegedly abusing the market dynamics through Algo and High Frequency Trading system has put a big question mark on the transparency of this automated trading platform.

The misuse of this highly technology-driven system by the insiders has badly hurt the common retail investors’ interests. In the emerging situation, where some insiders have turned white collar criminals, there are a few genuine questions: How deep is the rot? How safe and transparent is this automated trading system?

To conclude, in investment matters this kind of grave irregularities always leave a negative impact on both the small investors and the markets. Since there is no fair play involved in insider trading and no fair demand and supply of stocks, it is all detrimental to the functioning of a healthy stock market.

This white collar crime weakens the faith of investors in the system and the menace could keep off people from investing. This could ultimately harm the economy as a whole.

(The views are of the author & not the Institution he works for)

Disclaimer: The views and opinions expressed in this article are the personal opinions of the author.

The facts, analysis, assumptions and perspective appearing in the article do not reflect the views of GK.

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