When looking back at the market, ten years ago algo-trading barely existed, but according to research done by a Boston-based consulting firm called the Aite group, one third of all trading decisions in the U.S. markets are now made by machines. The Aite group predicts that by 2010 more than half of trading decisions will be made this way. One really interesting statistic that I mentioned in class was that Deutsche Bank in London has over 70 percent of spot trades carried out each day without any human intervention. The impact of algo-trading is that even if an individual does not own any shares, more than likely shares within your pension fund are being bought and sold using algo-trading.
Algo-trading is an efficient practice considering that computers can make multiple trades, monitor thousands of stocks and do it all at a remarkable speed. Another point is that transactions made by machines can also be done without anyone even noticing! Considering that the market is also reacting to purchases and sales of one another, there is significant profit potential when transactions are not noticed. When a person sees a stock change price, they might react in a few hundred milliseconds. A computerized trader is at least 10 times faster! These few hundred milliseconds might seem trivial, but if the price changes by a fraction of a percent in the split-second before a trade worth several millions, it could mean a difference of tens of thousands of dollars. Ideally a computerized trader offers a trader low latency market access, which means that there is little delay between placing an order and seeing it fulfilled.
Another advantage to an increase in computerized trading is the use of Stealth- trading. Many of the leading brokerage firms now have computers running volume-weighted average price (VWAP) algorithms. The algorithms break up big transactions into significantly smaller and separate transactions so that the rest of the market does not detect what a company may be doing. In an attempt to diffuse the use of these algorithms, Pattern-Spot software works to detect algos trying to sneak in transactions. This type of software also attempts to determine what is going on with these algos by studying the size of transactions.
The final point of this article which I found to be the most interesting were recommendations on how to beat algo-trading in markets. One of the most important concepts is to go with your gut feeling by making predictions in regards to where the market will be going. This of course means using some computerized data to help distinguish additional data needed. Another strategy suggested is looking for signs of liquidity. This means looking for the presence of buyers and sellers for specific stocks can open up a chance for a trade ahead of algo-trading. Unfortunately, signs of liquidity have also opened the door for new types of algo-trading called “sniper” algos which wait for a suitable buyer or seller to emerge and then conduct the trade as fast as possible, before the price can be affected by other traders.
After reading this article, it amazed me to see how much of an impact computerized algorithms have on the stock market. However, one important thing to realize is that human traders can make up for lack of data with instinct and experience. These components are what essentially designed these type of programs in the first place.
Matthews, Robert. "Where have all the traders gone?." New Scientist 194,260602 June 2007 42-45. 13 Noc 2007