Views from India: An Algo Roundtable

Brian Ross of FIX Flyer talks to Buy- and Sell-side presenting the latest lessons on high frequency trading and algorithms from the Indian market.
India’s capital markets are experiencing increased interest from local and global firms and new rules are set to attract high frequency trading (HFT).
The capital markets regulator, the Securities and Exchange Board of India (SEBI), the exchanges, brokers and many investors are in favor of abolishing Securities Transaction Tax (STT). Eliminating STT will have a positive impact on market turnover, will help high frequency traders to be more profitable and, at the same time, narrow spreads should drive up trading volumes.
STT has been levied for all trades, domestic or foreign, on all transactions in either equities or derivatives markets since 2004. At the time, the purpose was to generate tax revenue and to protect market integrity by slowing down the pace of technological advancements of a few, well-funded players. Revenue generated by STT amounted to around USD 1.5bn in 2011.
It is widely expected that STT will be eliminated this spring, bringing new opportunities for HFT in one of the world’s biggest and fastest growingcapital markets.
To better understand the situation, we asked five panelists who are leading the charge in HFT in India, to share their insights with us.
You never forget your first algo. When you first got involved in algorithmic trading, what problem were you trying to solve? What was your decision process, and what technologies did you use?

Sanjay Rawal, Open Futures:
We started off using algos for trading purposes and the first one we built was for a specific type of arbitrage that was getting difficult to run using manual input. We used third party software for the exchange connectivity and wrote our algo in C#.
Vishal Rana, IIFL Capital:
My first experience with HFT was trying to create a straight-arb model on a real-time basis. Although it was a simple model, the most difficult thing was to clean the data. We got the data dumps and it took a lot of effort to clean it. Most of the coding was done using C++.
Rohit Dhundele, Edelweiss:
At the onset of the project, the easiest yet most important task was gathering the business intelligence to be subsequently converted to algorithms. Some of the more intricate decisions were the selection of order, execution and risk management systems to ensure a stable back-bone to the platform. Other equally important criteria were a flexible programming environment and a friendly interface for users. To achieve these objectives, we had to decide whether to build or buy this technology.
At Edelweiss, we realized relatively quickly that there is a sweet spot between the two extremes of in-house vs. outsourced solutions. We have since been following this model – combining the best of both worlds, which has helped us deliver customized solutions within acceptable turnaround times, whilst still protecting our IP.
Sanjay Awasthi, Eastspring Investments (Singapore) Limited:
In the Indian markets, propelled as they are by rapid information dissemination systems, anonymity becomes a key factor in determining efficient trading. It was this need for anonymity that propelled us towards algorithmic trading. Continued use and familiarity lead to further benefits by way of better execution control. Algorithmic trading has thus become an important part of our execution arsenal.
Chetan Pandya, Kotak Securities:
The first algo I worked upon and put in production was calendar rolls for derivatives. Our trading desk had huge positions to roll from the current month to the next and manual execution was leading to slippages and erroneous executions at times. Using the 2 legged order of NSE we created a simple algorithm which would roll the position at desired spread.
My first observation regarding algorithmic trading was to appreciate the difference between an individual trading manually versus a machine trading automatically. There are so many things that come naturally to a human being but needs to be told to the machine. Sometimes I wonder whether an algorithm can fully replace a human being ever.  There are those nuances of the market and events that lead to erratic market behaviour that cannot be fully programmed for reaction.
Also, I had to ensure that there is no room for error when you are trading using an algo platform, primarily because of the sheer number of orders that it can process in a single second and also the inability to spot something going awry with the naked eye given the sheer speed. Hence, I had to also think of risk management capabilities of the Algorithmic platform while needing to ensure that risk management does not lead to inefficient execution due to latency.
In terms of technology, we were limited to applications that conformed to our market regulations. Once we had the base framework and architecture ready, we integrated it rapidly with our existing applications for order routing and downstream workflows.
There has been a great deal of press about HFT, in some cases, suggesting that it is unfair or even illegal. After the ‘flash crash’ in the USA and similar ones in Europe and Asia, how concerned are Indian exchange operators about HFT? What are your thoughts on HFT? How will SEBI move to address HFT?

SR: I think the exchange operators themselves are not against HFT and that they would like to see continued participation from HFT players. SEBI will certainly look towards regulation of HFT. I believe that as algos get more sophisticated, the market place will look unbalanced and therefore SEBI will be forced to look more closely at HFT. I believe that the opposition will come more from exchange participants rather than from investors, who will benefit from HFT.
RD: As has been pointed out, there has been much negative press recently concerning usage of HFT techniques. There have been a considerable number of studies conducted around the flash-crash and to the best of my knowledge none of them has confirmed a ‘one-to-one’ correlation between the two. The concerns might well have been blown out of all proportion; however they are not completely unsubstantiated.
HFT firms trade at lightning fast speed, create high throughputs and earn wafer thin margins on every trade. It is akin to flying a jet a couple of inches above the ground; there is little scope for error. Consequently, an error in the HFT domain can have an extensive impact. I hope this is not being misconstrued; low frequency traders are also capable of creating mayhem.
Such events directly impact the quality of liquidity available and have consequences reaching wide and deep into the trading eco-system. Given the risks involved, it is only prudent for the regulators and exchanges to interfere through proper risk management systems and processes. To banish HFT and similar products altogether is not the solution as there are proven benefits of these trading styles, moreover there is space for everyone in capital markets. SEBI has already expressed similar concerns and will act in tandem with the exchanges.
SA: As a predominantly long term fund house, we at Eastspring Investments (Singapore) Limited constantly strive to reduce the impact costs of trade execution for our clients. To this end, any measure that enhances liquidity and reduces spreads in the market is welcome. I believe HFT mandates changes in the market microstructure, which increases depth in the market and helps long-only funds, like us, to reduce impact cost. Without getting into the debate of the good and bad of HFT, I think any new trading strategy and its proliferation will alter market patterns. This requires us all to adapt our trading strategies in order to best satisfy the interests of our clients. It is important that there is a level playing field for all types of investors and that there are adequate systems and regulatory safeguards in place to protect the integrity of the market.
More specifically, in the Indian context, the market microstructure in both the cash and the derivative markets is ideally suited for HFT. The only major impediment is that the securities lending and borrowing market in its present form has not really taken off.
CP: SEBI is rightly worried about the rapid proliferation in usage of algorithms. We expect the regulators to come out with a more comprehensive risk management framework. In my view, HFT will form a significant part of trading in India in future. How and when this will happen and what will trigger this is anybody’s guess. While technologically we will be, or possibly already are ready, there will need to be changes in regulations to support HFT in India. As you are aware, foreign institutional investors today have to give and take delivery of each trade that they do on the exchanges and intra-day netting off is not permissible, which clearly is not supportive of the HFT philosophy.
What are the challenges of using algos on multiple exchanges in India? Is this kind of arbitrage or Smart Order Routing technology going to take off?

SR: If we get far larger volumes on BSE, which they are working very hard towards, we will see an explosive growth in Smart Order Routing (SOR). But the exchanges will have to allow not only SOR , but also allow for using market data feeds, so that more sophisticated algos can be run for valuing futures as well as options. I believe that it will lead to higher volumes on both exchanges, but rather more for the larger player than the smaller player.
VR: The biggest challenge we are facing is that respective exchanges have not opened their APIs to each other, so different algos need to be run for the exchanges and the same algo does not work across the exchanges. Eventually they will have to open their APIs and SOR will pick up.
RD: Prior to defining challenges with respect to SOR in India, perhaps it will be better to put this technology into perspective vis-à-vis developed markets. The trading landscape in these markets is significantly different from India due to the presence of dark pools and ECNs over and above the exchange platforms. The total number of such liquidity pools, which at times runs into doubledigits, makes efficient trading across venues a colossal task.
SOR consists of advanced quantitative techniques backed by sophisticated technologies for optimizing volumes, price impact, speed and trading costs across all possible venues. In India, the landscape is straightforward: there are two major exchanges and only lit-liquidity which makes the work of decision support systems relatively straightforward. While business objectives are simpler in India, the initial implementation will face challenges from a technology standpoint. Reconciliation of varied native formats for market broadcast and permissible order types across exchanges will be at the fore. Inter exchange arbitrage will also have to deal with dissimilar latency across venues due to their geographical separation. Notwithstanding the constraints, SOR does move the market microstructure towards efficiency and therefore will experience wider acceptance from the market community over the next few years as brokers, exchanges and vendors move up the learning curve.
SA: Algorithms were basically sell-side tools and thanks to new technology, they are now available to the buy-side as well. So to successfully use algorithms, the buy-side has to acquire and adapt sell-side skills as well.
CP: This is related to challenges of market microstructure, margining requirements, clearing and settlement challenges and transaction charges in India. While SOR is in place, my belief is it has yet to take off in a big way thanks to the above mentioned limitations. But I am sure that this will pick up as we go ahead as people in market are definitely looking at alpha. If they see returns in these strategies then challenges will also get addressed for sure.
What are the tax and fee implications for HFT in India? For exchanges and brokers?

VR: Transaction costs are an obstacle for HFT, hence the micro high frequency trading or very high frequency trading is still not taking place; the threshold levels to trade are still very high.
SA: Algorithms are just tools, the use of which is a function of various factors including the desired outcome and other benchmarks. At Eastspring Investments (Singapore) Limited, we use implementation shortfall as a benchmark to measure execution performance. So the choice of a volume-based or a price-based algorithm depends on the size of the order and the trading pattern of the stock and other benchmarks that may be applicable.
The choice of the algorithm is also highly situation specific and in the future we should see the evolution of intelligent parameter building, based on market microstructure studies and other research. This will result in algorithms being framed to apply in an automated fashion to a variety of situations.
In Asia, and in India specifically, there needs to be further research on the market microstructure before such parameter defining and algorithm building begins. Several broking bodies do invest resources in this type of research. Market microstructure research combined with proper historical transaction cost analysis will pave the way for customized solutions. That is where I see the industry moving to in the near future.
CP: There are multiple taxes and fees levied by the regulator/government on the exchange transactions and they vary for Equity and Derivatives segment. The Exchanges levy transaction fees which is a major source of revenue for them while the Government levies Securities Transaction Tax, stamp duty on exchange transactions and service tax on commission charged by brokers. These taxes make certain types of strategies unviable. HFT will also face this hurdle of high taxes and charges.
Is low-latency a requirement for many algorithms?
SR: Without question. Most strategies, including trend following will not work without low latency. The incumbent players will not leave enough on the table for others to get, if you are unable to compete on latency.
RD: Yes, low latency is a prerequisite for many but not all algorithms. As a general principle, each trade should reach the venue as quickly as possible; there cannot be a down-side to being first to reach the order book. But there are costs, exorbitant at times, of maintaining a low latency infrastructure and the cost vs benefit will not work out for all trading styles.
Low latency is a crucial ingredient only for trades where many market participants are chasing a similar metric, for example, arbitrage. In short, investing in a low-latency system should be driven by the traders positioning in the market and not because the term is in-vogue on public forums.
CP: Low latency is a prime requirement in derivatives where at times it becomes an all or none game for certain type of executions. The cash execution algorithms market is slowly but surely moving to low latency. With a gradual increase of alpha seeking algorithms, low latency will be the need of the hour.