Investors are always looking for new vehicles to make money. They move from one financial instrument to another in search of the pot of gold at the end of the rainbow. But most investments are not very stable and they offer more opportunities to lose money than to make it. While equity trading has been around for many years and has proven itself to be somewhat secure and stable, traders continue to be search for the most risk-laden instruments and take their chances on winning big.
Truth be told, there really are very few trading vehicles out there these days and they seem to be dwindling from year to year as regulators and government authorities uncover their deviant nature and come down on those that offer them.
India is one of the few emerging markets that have been offering computerized trades and it is now discovering that there are limits to how far it can go.
The world of binary options has come under scrutiny of late and algorithmic trading is the next trading instrument to go under the radar.
Algo-Trading
Algorithmic trading, often called automated trading, black-box trading, or simply algo-trading, became a tool for institutional investors in the beginning of the 1990s. It is the process of using computers programmed to follow a defined set of instructions for placing a trade in order to generate profits at a speed and frequency that is impossible for a human trader. The defined sets of rules are based on timing, price, quantity or any mathematical model.
Since the main ingredient in trading profit and loss is personal choice and decision making, algo-trading makes markets more liquid by offering trading in a more systematic manner by ruling out human emotional impacts. By and large, the main objective of algo-trading is not necessarily to maximize profits but rather to control execution costs and market risk.
Algorithmic trading around the globe has become a business estimated at $400 to 600 million per year.
How it Works
Here’s an example of how algo-trading works:
A trader buys 100 shares of a stock when its 50-day moving average goes above the 200-day moving average. He then sells 100 shares of the stock when its 50-day moving average goes below the 200-day moving average. Anyone with tech savvy could write a computer program which would automatically monitor the stock price (and the moving average indicators) and place the buy and sell orders when the defined conditions are met. This eliminates the need for the trader to put in the orders manually or to watch for live prices and graphs. The algorithmic trading system automatically does it for him, by correctly identifying the trading opportunity.
There are other benefits to algo-trading. One could assume that the trades are executed at the best possible prices, at desired levels and at the best times possible. There is less risk of manual errors in placing trades and reduced transaction costs. In addition, the algorithm can be backtested based on available historical and real time data.
Today’s version of algo-trading uses high frequency trading (HFT), which capitalizes on placing a large number of orders at very fast speeds across multiple markets and multiple decision parameters, based on pre-programmed instructions.
Too Fast Speed
The high speed involved with HFT is what has some regulators cracking down on brokers offering algo-trading.
India is one of the few emerging markets that have been offering computerized trades and it is now discovering that there are limits to how far it can go. In the last five years, high-speed and algorithmic traders have become a dominant force on Indian exchanges, spurred on by competition between the nation’s top exchanges that have successfully cut transaction times to tiny fractions of a second.
The question of high-speed strategies is by no means unique to India but the country stands out for its rapid growth of computerized trading and its heavy role in local markets. India is home to some of the world’s biggest technology companies and engineering universities and its natural fit for computerized investment strategies has made the nation’s high-frequency and algorithmic transactions accountable for 40 percent of total volumes, the highest proportion in the developing world and up from the low single digits five years ago.
Both exchanges now offer co-location services which allow traders to use their computers in exchange data centers so they can execute faster. Last October, the BSE (one of the two exchanges) reduced its average processing time for trades to 6 microseconds from 300 milliseconds, the fastest worldwide.
Bourses Calling for More Regulation
The country’s largest brokerages are now calling for tighter regulation and the bourses are starting to explore whether speed traders should be reined in.
According to Ashishkumar Chauhan, BSE’s chief executive officer, India has been among the world leaders in setting regulatory standards for high-speed trading. He claims the exchanges are doing a lot of HFT compared to the size of market and that a clear understanding of the risks involved are required.
At the National Stock Exchange of India (NSE), officials are contemplating higher fees for customers who have a high ratio of orders to trades and would introduce measures to discourage investors from pushing too much data traffic to its venues. In addition, the Securities and Exchange Board of India, which issued broad guidelines on computerized trading in 2012 and 2013, said in December that it is considering new restrictions, but has so far taken no action.