Algo Trading facilitates transaction decision making in the financial markets using advanced mathematical tools. It is also known as Algorithmic trading, automated trading and black box trading. Algo Trading generates a model to place buy or sell order of a specific quantity that automatically generates the time and size of orders based on the specified parameters and constraints of the algorithm. It is Black Box trading that no one else knows about the strategy followed by trader and has been pre-programmed using logic to generate both buy and sell signals automatically.
In Indian stock markets, Algo Trading was first allowed in 2008 and now Algo trade volume accounts for 40% of total trade in the cash segment in NSE and BSE in March 2015.It is allowed by SEBI in all segments — equities, derivative and commodities.
High Frequency Algo Trading react very fast to events in the market and is the biggest contributor of liquidity to the markets by reducing bid-ask spreads. It helps to find out the best price which is being offered and traded.The computers, through Algo trading, can do millions and billions of transactions in click of seconds with better connectivity, accuracy and processing speed, compared to an ordinary human trader. It improves trade volumes and price efficiency, and reduces market volatility. It is very difficult for an ordinary trader to keep track of market of each minute but Algo Trading (through computers) enables so. In this ever changing trading environment with a lot more traders in the market to push competition and consciousness about trading cost, only those traders can capture the maximum orders who can innovate their services and fetch early mover advantage.
But it also poses risks in the form of increased probabilities of error trades and market manipulation. It got a boost with the introduction of direct market access (DMA) – electronic ways of interacting with the stock markets, when ‘co-location’ was allowed in India. Co-location is a platform or exchange which allows some traders, usually large traders, to place their computer servers next to the exchange server for a price. This leads to installing a two-queue system for traders, one with a co-location advantage and another without co-location advantage which means those who can pay get the advantage in trading. Algo trading also encourages malpractices like spoofing and quote stuffing which means placing orders with no intention of executing them and creating an illusion of demand to get favorable prices.
The best execution through use of algorithmic tools depends on clear understanding of portfolio management strategies, objectives, pre-defined models, constraints, cost issues, balancing timing and integration of Order Management Systems, close relationships with algorithmic trading providers and thorough post-trade analysis and feedback. But all these factors put together still can’t beat ‘Trader’s Gut Feel’.
Like any other industry, things evolve and change but one who adapt with the changes by learning new skills survives. People always exhibit resistance to change but there is rule of survival of fittest. At last, any trading strategy that aims to manipulate the markets can be executed algorithmically as well as manually and it is the trading strategy which aims to manipulate, and not the platform. Thereby, Algo trading with the ability to turn the information into intelligent trading decisions, can prove to be the next best stroke in the financial industry.
This blog is written by Neha Jain, Student of MBA FA (2014-16) batch, ICoFP Delhi Campus.
