Between April 30 and May 7, the Securities and Exchange Board of India or Sebi issued a series of orders in response to an extremely complicated scandal that happened in 2013-’14. This affected an important segment of the financial markets, and the regulator handed out stringent punishments.
The average investor has very little understanding what this is all about. So what follows is a basic explanation of what is said to have occurred, what Sebi did in response, and some implications.
The regulator has imposed what amounts to huge fines of about Rs 1,000 crore on the premier National Stock Exchange (Rs 624 crore at 12% compound interest from April 2014). This is based on Sebi’s calculations of the profits NSE made from co-location charges. The NSE had already been ordered to put this cash aside. (Most of the fines mentioned in the orders are “disgorgements”, based on what the regulator reckons offenders made in terms of profits from unfair practices.)
Sebi has also denied the NSE access to capital markets for six months, holding up the stock exchange’s IPO plans. The regulator has also blacklisted a telecom service provider, fined brokerages, and punished multiple individuals, including several former and current NSE officers, and several technical advisors to the NSE.
What is this about? Skip the next few paragraphs if you know what colocation is.
What is co-location?
Let us start with basic physics, because that underpins the business model. Like light, electronic signals travel at roughly 300,000 km/sec in vacuum. The speed drops to around 20 cm per nanosecond (one millionth of a second) or by about one-third in an optic-fibre network.
So, if you connect up two computers with 10 metres of cable and transfer data from one to another, that data will take a minimum of 50 nanoseconds to travel. If those two computers are a kilometre apart, the data will take at least 5,000 nanoseconds. In practice it will probably take longer.
That time difference is appreciable. It can be monetised. Tiny time differences caused by signals going from one point to another is a key element of the Global Positioning System or GPS, and of radar systems. All modern locational and navigational programmes depend on small time differences for mapping and calculations.
This is a vital factor in modern financial trading. Financial exchanges generate huge quantities of data. Fast computers take that data, run it through neural nets and other algorithms, and look for patterns that can be traded for profits.
Any trader with faster access to that data has an edge over competitors. Hence, traders pay a premium to have trading stations located next to the servers of financial exchanges. That is co-location. To speed data access up yet another notch, the trader who “co-locates” wants to use dedicated optic fibre networks. Such uncluttered networks are sometimes called Dark Fibre (this can also simply mean existing but unused optic fibre capacity on a network).
Apart from speed of access, better algorithms are important. One way to develop better trading programmes is to pump more data into a neural network. Neural networks are gluttons for data. Given more data, a neural net may find new patterns to trade.
Financial exchanges do not release all the data they generate. Anybody who receives access to some extra data could gain an edge. Somebody who receives data quicker, and has access to more data as well, has even more edge.
A level playing field
Now add another dimension – that of the concept of a level-playing field. Trading is a zero-sum game. One trader’s gain is offset by the counterparty’s loss. An efficient market is one, where by definition, a large number of people receive the same information simultaneously and they can trade it with equal efficiency. That way, the playing field is level.
It is the regulator’s brief to keep things as level as possible. The instant co-location happens, the trading environment ceases to be a level playing field. The co-located trader cannot only trade more efficiently; it can indulge in various practices that border on the abusive.
For example, it can put out a vast number of orders very quickly, and immediately cancel some of them, while analysing the responses. This sort of high-frequency trading can help a trader discover best price. Co-locators can also collaborate to create “dark pools” where block trades can take place off-exchange. Again, this discriminates against ordinary non-co-located traders.
Exchanges like co-location because it is a great revenue stream. But financial exchanges and regulators have to decide how much in the way of co-location practices are acceptable, and which trading methods could cross the line in terms of gouging profits out of non-co-located investors.
This is the first time the Sebi is attempting to establish these boundaries in practice.
The NSE co-location case has led to multiple separate orders and at least two appeals so far.
One of the problem areas was that, according to Sebi, the NSE mishandled the dark fibre at its disposal. This gave preferential co-location access to two brokers, Way to Wealth and GKN Securities, who were serviced by a service provider, Sampark Infotainment, which was not cleared by NSE.
The brokers have been fined and barred from taking on new clients while Sampark has been barred from providing services to market players for two years. The NSE has been told to get the network architecture audited every six months. In addition, another broker, OPG has also been punished. OPG has been fined, it is forbidden to take on new clients and its proprietors have also been punished.
The NSE has also been separately fined Rs 62.5 crore plus interest. The NSE Chief Executive Officers of that period, Ravi Narain and Chitra Ramakrishna, have been fined 25% of their compensation during that period and, along with several others, been barred from working in the markets.
Now we come to the question of confidential data. The NSE gave data to a firm, Infotech Financial Services, for academic purposes of research and in order to create a liquidity index for NSE. That firm is run by Dr Sunita Thomas, who is the wife of Suprabhat Lala, an assistant vice president of NSE.
Sunita Thomas is also the sister of Dr Susan Thomas, an economist who has advised the NSE for years and written multiple papers on various aspects of financial markets.
Susan Thomas is the wife of Dr Ajay Shah, professor at National Institute of Public Finance and Policy and another eminent economist, who has been closely associated with the NSE. (Disclosure: Ajay Shah is a personal friend).
One of the Sebi orders cites “conflict of interest” and says that data could have been “collusively” used to design algorithms that led to personal gain. So these individuals have also been punished by being barred from working in capital markets for two years.
The Securities Appellate Tribunal has granted interim relief to Ajay Shah, Sunita Thomas, Suprabhat Lala, and Infotech Financial Services, by staying the Sebi ban. The contention in the appeal was that the data supplied by the NSE was in the public domain and that, in their long history of association with the capital markets, they had never been accused of wrongdoing. Ravi Narain has also separately appealed against the Sebi orders.
Implications for the future
Co-location and algorithm-based trading are here to stay. The orders do give us a chance to understand how future regulation in these areas might proceed. Sebi will apparently try and prevent co-locators from gaining excessive advantage over other co-locators. How it will define “excessive” in this case, will be crucial since practices will also change as the technology improves.
Sebi will look at possible conflicts of interests in areas such as research and technical advice. It will also consider the implications of exchanges releasing confidential data to a restricted group. This of course, does not pertain only to co-location and algorithmic trading.
This is only the beginning of regulation in this area. Given the likelihood of major changes in Indian data storage policies, the Sebi (and obviously, the exchanges it regulates) will have to keep reviewing and making changes to policy.
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