Algorithmic Trading has come a long way, from reading the tick data days to being latest buzz on the trade markets. Has your firm captured the essence of this new artificial intelligence?
The black-box trading was a hush-hush scenario until a year ago, as only a few trading firms offered them to their clients.Nevertheless, today, you can receive a bevy of free algo trading. Therefore, when a firm announces the discovery of the next generation of trading platform, the financial services industry ears perk up. Here it is about interpreting newsflow the moment it is delivered from the horse’s mouth.
“A client depends on a sell-side firm to execute its order on its behalf according to certain benchmarks. But, when it comes to a strategy, the Algorithmic Trading system actually generates the orders. Some hedge funds do this.”
For level-one sell side firms, automated trading has become a crucial part of their existence. These firms employ algorithm trading as the basic strategy to gain momentum in the markets across the globe.
How does this artificial intelligence work? Algorithmic trading is standardized by Volume-weighted average price (VWAP) it divides the total value of trades by the total volume over a period. Interestingly, European-banking conglomerate UBS utilizes algo trading for its 40% clientele. Other giant corporations who are testing the unique capabilities of robo trading include JPMorgan Chase, Credit Suisse and Dresdner Kleinwort Wasserstein.
You think only brokerage firms and banking institutions are eagerly investigating the technology?
Dow Jones the financial news boffin is secretive about performing tests on the news-reading solution with several chief sell side firms. Meanwhile, Thomson Press corroborates- it is examining the concept with clients.
Despite the term “newsflow algorithm” akin to Algorithmic Trading, it is believed that the system will hold an immense value to the financial industry for order-generating strategies. The automated trading will consider newsflow amongst a wide array of information available for influence trading activities.
Volume and time are important factors considered by a simple algo trading. Conversely, complicated algorithms would allow several hundreds of real-time factors to arrive at a profitable investment decision. For instance, Credit Suisse swanks about an automated trading system that takes care of 3,000 data points every 10 seconds.
One-third of European and American stocks were driven by autopilot i.e., algorithms in 2006. In 2009, HFT firms accounted their 73% of US equity trading volume to the artificial intelligence.
NASDAQ, BATS and Direct Edge have gained a larger market share as compared to NYSE. Their success is attributed to algorithmic trading that enables them to reduce processing fees and commissions.
Thus, the development of automated trading has prompted a reduction in trade size and increased trade volume, leading to investment that is more profitable. And, profitable investments obtain a larger chunk of market share for automated brokerage and financial firms, as compared to old school of thought.