Automated traders now have access to unprecedented levels of market data. Thom Hartle, Director of Marketing, CQG, conducts a theoretical comparison between two trading systems to explore how order book data can be leveraged for optimal trade performance.

Using Order Book Data to Improve Automated Model Performance

Thom Hartle

The advent of electronic trading platforms for futures and cash markets has created greater market transparency. The availability of this level of market information has led to innovative ways of tracking the actions of traders within an exchange’s electronic order book. Historically, traders only had the last price as the first input to an automated trading model. Today, we can ascertain whether the last price was generated by a trade at the bid price (selling) or a trade at the ask price (buying). The question is: can that information be an additional filter as an aid to improving trade performance?

This article compares the effectiveness of two trading systems. One system uses a price-based oscillator for the entry signal generator; the second uses an executed volume-based oscillator for the entry signal generator. The core market situation we shall explore is as follows: the market trend direction is identified, then an oscillator is employed to initialise entry signals following an indication that a countertrend movement is complete and the price action is moving in the direction of the trend. The market tested is the E-mini S&P futures.