PAGE 11
DISRUPTIVE INNOVATION iNM Volume- 9 equity markets. Likewise, HFT has grown in futures markets— to roughly 80 % of foreign exchange futures volume and two-thirds of both interest rate futures and Treasury 10-year futures volumes.
of a company which is trading at 100 rupees each.
The trader Quotes to buy another 1000 shares at 101 rupee each. The HFT machines record the new price as 101, the trader then quickly sells his 1000 shares and makes a profit of 1000 which he wouldn’ t have otherwise. So the HFTs have their own flaws. Recently the revenue of HFTs are very low. But rapid innovations taking place in this sector will turn the situation.
Next evolution of algorithmic trading depends on smarter machines, allowing a broader class of trades to reap the benefits of automation and sophistication. Machine accessible data, big data and Artificial intelligence are shaping the future of algorithmic trading. The agility and the accuracy of the trading will improve.
Growing public discontent with algorithmic trading may lead to regulations on the use of automatic data feeds or smart machines in executing trades, which may lead to reverting some parts of market-making activities to manual processes. The main focus areas for HFTs are price discovery and order execution. These HFT machines do not look for the intrinsic value of the shares, rather they focus more on market information. They assimilate the market informations at a faster pace and execute the orders rapidly. But it is also subjected to flaws, Say a trader has 1000 shares
The development of smarter, faster machines in algorithmic trading will have implications on the market structure in terms of volume, liquidity, volatility and spread.