09 - 10 September, 2013
The Westin St. Francis, San Francisco, CA

Trading Technologies

Algo Trading


Click Here to Watch the Exclusive Video

In this exclusive video, Rebellion Research CEO, Spencer
Greenberg, says that the difference between high frequency
trading and what Rebellion Research does is that HFT
focuses on trading as fast as possible, while Rebellion does
the complete opposite. 

In this video, you’ll hear Greenberg explain the potential for 
new trading technologies (if a camera can recognize a
smile on a face, what can a trading machine “recognize”? ).
Following form, he also challenges some of the age-old,
conventional ideas about equity trading saying we have to
reconsider some of these precepts.



In today’s worldwide markets, many of the trades each day are executed with the aid of computer-assisted trading technologies. One such technology is called algorithm trading or algo trading, for short. A recent report by the CME Group suggests that at least 45% of all trades executed via their platform are based on algorithms. They also estimate that the total percentage of algorithm-based stock trades, executed worldwide, may be as high as 75%. Many buy side institutional investors, such as mutual funds and hedge funds, use algorithmic trading to spread their risk over many smaller trades rather than a single large order. Market makers and other sell side institutions use algorithm-based scenarios to generate and execute orders automatically and to add liquidity to the market.

In an algo trading strategy, the timing and the size of each trade is determined by patterns in the market that are recognized through the statistical analysis performed by the appropriate algorithm. Before any trade is executed based on an algorithm, it must be tested to determine its reliability, speed of execution and performance. The most common way of doing this check is called back testing.

This method of testing trading algorithms attempts to replicate historical data, such as price, volume and market breadth, in an attempt to identify how a particular algorithm would have performed under different trading scenarios. Some algo trading strategies are very complex. The testing of the myriad number of calculations involved in these strategies is usually done through computer simulations as each possible outcome must be tested before an algorithm is used in a live market.

Once trading algorithms are put into place, traders and programmers work to determine that that they are performing optimally. Tests are conducted verifying the speed of execution, the best possible routing of orders, the reliability of the supporting infrastructure and the actual return on investment of the trading algorithm. Based on this analysis, the strategy is then tweaked for optimal performance.

Advanced trading technologies have greatly expanded the capabilities and productivity of traders. It is vitally important that these strategies be thoroughly tested before and continuously updated after they are implemented.

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