Hyde Park Global Bets on Adaptive Models to Trade Arbitrage Strategies in Milliseconds

Because no formula is going to work all the time, Hyde Park Global develops adaptive models, using a genetic algorithm (i.e, such as mutations and crossover), which are designed to respond to changing market conditions in real time, Afshar explains. While he refers to this as machine-based learning, he points out that the machines don’t actually learn. Rather, “They recalibrate themselves within the parameters that you have identified,” Afshar says, adding that they rely on data and quotes from previous trades to recalibrate.

Sounds just like what we began doing in ~2004.  It is *very* easy to do this poorly and we put in *years* of working on #1) a process to enable us to use these techniques properly, #2) An incorporation and understanding of the state of the art technologies (multi-objective optimization, boosting/ bagging, SVMs, fuzzy rule induction, etc). #3) specific implementations of the core machine learning techniques specialized for automated trading.

My basic belief is that these patterns of machine learning will continue to drive the state of the art of extracting money from the global markets.

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