These ELP strategies can also be signal detectors.
For example, when ELP strategies are adversely affected by a price that changes the current bid/ask spread, this may indicate the presence of a large institutional block order.
An HFT can then use this information to initiate an active strategy to extract alpha from this new information.
Active HFTs monitor the routing of large orders, noting the sequence in which venues are accessed. Once a large order is detected, the HFT will then trade ahead of it, anticipating the future market impact that usually accompanies sizable orders.
The HFT will close out their position when they believe the large order has finished. The result of this strategy is that the HFT has now profited from the impact of the large order. The concern for the institutional investor, that originally submitted the large order, is that their market impact is amplified by this HFT activity and thus reduces their alpha. The most sophisticated HFTs use machine learning and artificial intelligence techniques to extract alpha from knowledge of market structure and order flow information.