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India: Big Potential for Algorithmic Trading

India: Big Potential for Algorithmic Trading

July 22, 2010 0 Comments

I spent last week in India, a country that, by any standards, is growing fast.  Its population has doubled in the last 40 years to 1.2B and economic growth has averaged more than 7% per year since 1997.  It’s projected to grow at more than 8% in 2010. By some measures, India has the 4th biggest economy in the world. 

Progress Software has a significant presence in India. In fact, people-wise, it’s the biggest territory for Progress outside the US with over 350 people. Hyderabad is home to a big development centre and Mumbai (Bombay) has sales, marketing and a professional services team.

The primary purpose of my visit was to support an event Progress organised in Mumbai on Thursday of last week on the subject of algorithmic trading. It was also our first real launch of Progress and Apama, our Complex Event Processing (CEP) platform, into the Indian capital markets. We had a great turnout, with over 100 people turning up. I spoke about what we did in capital markets and then participated in a panel session where I was joined by the CTO of the National Stock Exchange, the biggest in India, a senior director of SEBI, the regulator, and representatives from Nomura and Citigroup. A lively debate ensued.

The use of algorithmic trading is still fairly nascent in India, but I believe it has a big future. I’ll explain why soon, but I’d like first to give some background on the Indian electronic trading market, particularly the equities market, which is the largest.

Watch my Interview on NDTV Profit >

The market: India has several, competing markets for equities, futures and options, commodities and foreign exchange too.  In equities, the biggest turnover markets are run by the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE), with market shares (in the number of trades) of 74% and 26% respectively. Two more equity exchanges are planning to go live soon – the Delhi Stock Exchange is planning to relaunch and MCX is also currently awaiting a licence to launch. This multi-market model, only recently adopted in Europe for example, has been in place in India for many years.

It was only two years ago that direct market access (DMA) to exchanges was allowed. Although official figures don’t exist, the consensus opinion is that about 5% of volume in equities is traded algorithmically and between 15% and 25% in futures and options. Regulation in India is strong - no exchange allows naked access and the BSE described to me some of the strongest pre-trade risk controls I’ve come across - collateral checks on every order before they are matched. The NSE has throttling controls which imposes a limit on the number of orders a member organisation can submit per second. Members can be suspended from trading intra-day if this is exceeded. The NSE also forces organisations who want to use algorithms to go through an approval process. I’ll say more about this later. Controversially, the NSE will not allow multi-exchange algorithmic strategies so cross-exchange arbitrage and smart-order routing cannot take place. Lastly, a securities transaction tax (STT) is levied on all securities sales.

So, with the above restrictions, why do I think that the Indian market for algorithmic trading has massive potential?

The potential: The Indian market is very big. Surprisingly so to many people. Taking figures from the World Federation of Stock Exchanges (thus I’m not counting trading on alternative equity venues such as European multi-lateral trading facilities), the Indian market, in dollar value, may still be relatively modest – it’s the 10th largest. However, when you look at the number of trades, India’s the 3rd largest market, only beaten by the US and China. The NSE, for example, processes 10 times the number of trades as the London Stock Exchange. So why isn’t more traded in dollar terms? That’s because trade sizes on Indian exchanges are very small. The median figure worldwide is about $10K per trade. The figure in India is about $500 per trade, a 20th of the size. In summary, surely the task of taming the complexity of this number of trades and the orders that go with them is ideal for algorithmic trading to give an edge? To compare to another emerging, “BRIC”, economy, that of Brazil, where the number of firms using Apama has gone from zero to over 20 in as many months, the dollar market size is fairly similar but the number of equity trades in India is 33 times more. The potential in India is therefore enormous.

India is already there in other ways. All exchanges are offering co-location facilities for their members and debate has already moved on to that common in more developed markets on whether this gives certain firms an unfair advantage or not and whether co-location provision should be regulated.

The challenges: There are some difficulties. The STT is seen by some as an inhibitor. However, its effect is offset somewhat by the fact that securities traded on exchange are not subject to capital gains tax.

The NSE process for approving algorithms is more controversial. Firms that want to algorithmically trade must show to the NSE that certain risk safeguards are in place and “demonstrate” the algorithm to the exchange. As the biggest exchange, the NSE wields considerable power and thus its decision to vet algorithms puts a brake on market development. I believe this process to be unsustainable for the following reasons:

  1. As the market develops there will simply be too many algorithms for the NSE to deal with in any reasonable timeframe. Yes, India is a low-cost economy, but you need highly trained people to be able to analyse algorithmic trading systems. You can’t simply throw more people at this. Firms will want to change the way algorithms work on a regular basis. They can’t do this, with this process in place.
  2. It raises intellectual property issues. Brokers will increasingly object to revealing parts of their algorithms and their clients, who may want to run their alpha seeking algorithms on a broker-supplied co-location facility, will most definitely object.
  3. It puts the NSE in an invidious position. Eventually an algo will “pass” the process and then go wrong, perhaps adversely affecting the whole market. The NSE will have to take some of the blame.
  4. Competition will force the NSE’s hand. The BSE is trying to aggressively take back market share and other exchanges are launching which will not have these restrictions.

It strikes me that the NSE should spend its efforts into ensuring that it protects itself better. Perhaps a reasonable comparison is a Web site protecting itself from hacking and denial of service attacks. If they can do it, so can an exchange. And it would offer much better protection for the exchange and the market in general.

In conclusion: I’m convinced of the growth potential in India for algorithmic trading. The market is large, the user base is still relatively small and many of the regulatory and technical prerequisites are in place. There are some inhibitors, outlined above, but I don’t think they’ll hold the market back significantly. And finally, why should India not adopt algo trading when so many other, and diverse, markets have?

Progress has its first customers already in India. I look forward to many more.

Giles Nelson

View all posts from Giles Nelson on the Progress blog. Connect with us about all things application development and deployment, data integration and digital business.

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