It’s been at least a year since the Securities and Exchange Board of India (Sebi) allowed brokers to offer direct market access (DMA) and algorithmic trading facilities to institutional clients, but this alternative means of trade execution has found few takers. The percentage of trades done on both stock exchanges is minuscule, as institutional investors have preferred the traditional route of placing their orders with brokers, who, in turn, enter them into the exchange’s system.
But some action can be soon expected, with foreign brokerages gradually offering their proprietary algorithmic trading products for Indian markets.
Credit Suisse’s advanced execution services (AES) unit announced the launch of algorithmic trading in Indian equities last month. It has been offering DMA to its clients since September 2008. Other big global names in electronic trading such as Goldman Sachs, JPMorgan and Citigroup are in the process of launching algorithmic trading services in India, while a few such as Merrill Lynch are already offering the service. The entry of top foreign players is a welcome step, since their clients are already using the same programmes for trade execution in other markets. For them, a launch in India would just be an extension of what they are already doing in other markets.
Why the delay? Ian Smith, head of AES product (Asia- Pacific) at Credit Suisse, says, “As a market leader in algorithms, it is key that our full suite of strategies are provided to our clients, with the best possible performance from Day 1. This takes time to model and implement the necessary changes required to take full advantage of the micro-structure of a new market.”
Timing was also an issue. Sebi approved DMA and algorithmic trading in April 2008, and thanks to the steep fall in equities in 2008, few clients were willing to make investments in trading technology. Rashesh Shah, chairman and chief executive of Edelweiss Capital Ltd, says that the securities transaction tax imposed in the Indian markets has reduced the prospects for arbitrageurs and high-frequency traders, and this has impacted algorithmic trading to some extent.
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Edelweiss has been offering these services since last year, but a very small proportion of its clients use them. Shah also says that latency on Indian exchanges is fairly high and the country needs to improve its sophistication for algorithmic trading to pick up here. Latency is the time delay in information reaching from a trader’s system to the exchange’s system. Low latency is critical for algorithmic trading, and exchanges, brokers and traders worldwide are investing millions of dollars to enhance trading efficiency.
These shortcomings, notwithstanding, there is ample room for electronic trading services to grow in the country. Smith says, “The Indian markets are a unique challenge in Asia for algorithmic trading. The tight spreads, low visible liquidity on the bid and offer, and high trade rate all require a lot of effort and skill to execute a good trade. Algorithmic trading provides that ability at machine speeds.”
To be sure, Credit Suisse’s AES product includes liquidity-seeking strategies such as Guerrilla and Sniper, which slice large orders into smaller unnoticeable sizes and execute client orders as and when liquidity is available. Another strategy, called Inline, seeks to minimize implementation shortfall, or in other words reduce the difference between the price at which a client decides to trade and the actual execution cost. In the Indian context, where market depth is relatively low for the majority of stocks, such products can be very useful.
Besides, since liquidity is available on two venues, at least as far as the cash market is concerned, there can be strategies that route orders to the best venue in terms of price. With hundreds of options being traded at any given time, it’s impossible for a human trader to keep track of all related contracts. But with automated trading, institutional investors, who trade on the options market, can benefit from price changes in related contracts.
Getting in shape: The Bombay Stock Exchange building in Mumbai Ashish Shah / Mint
One of the criticisms to Sebi’s manner of adopting algorithmic trading was the requirement that the algorithms would be scrutinized by the market regulator and the stock exchanges before permission was granted. The argument was that brokers and clients would not want to share proprietary information and hence this requirement could hinder the growth of these services.
But brokers aren’t required to share the nuts and bolts of their programme and so it’s not that critical proprietary information is at risk. They need to essentially disclose the objective of the algorithm and how it seeks to execute it. As Smith says, “I think it is sensible due diligence. Once algorithmic trading is a more accepted and a mainstream method of executing in India, Sebi may well relax this policy, but they always need to understand the trading methods of the exchange participants. Explaining the concepts of AES is not a hindrance.”