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02 May 2016

Machine Learning For Stock Trading Strategies

The idea of using computers to trade stocks is hardly new. Algorithmic trading (also known as algo trading or black box trading which is a subset of algo trading) has been around for well over a decade and rapidly gaining in popularity. Here’s a look at algorithmic trading as a percentage of market volume:

Source: Morton Glantz, Robert Kissell. Multi-Asset Risk Modeling: Techniques for a Global Economy in an Electronic and Algorithmic Trading Era.
 
If that trend continues, then this means that today upwards of 90% of trading is being conducted by computer programs. One thing to notice about algorithmic trading is that it has been moving in the direction of shorter and shorter holding times. High frequency trading (HFT) is a subset of algorithmic trading in which stocks are bought and then sold in fractions of a second. This strategy is a form of arbitrage in which the HFT algorithm spots a price discrepancy and then quickly capitalizes on it. As you would expect, HFT trading profits are becoming smaller and smaller but the volume of trades are still dominating the overall market:


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