Improving execution quality with CME’s MBO data-set

Improving execution quality with CME’s MBO data-set

One of the key challenges for any algorithmic trading firm is understanding why fill ratios aren’t optimised. Now, with the launch of a new data set by the CME Group, traders can access unprecedented transparency over their orders, improving the accuracy and returns of their strategies.

In Q4 2016, CME started the roll out of Market by Order (MBO) functionality alongside the existing Market by Level or Market by Price offering. 

MBO data disseminates individual orders and quotes at every price level in a given instrument and for the first time gives traders a view of exactly where their order is in the queue. In the MBL format traders can only identify which price level their order is in, not its position in that level.

The data set was launched for Nymex and Comex contracts in Q4 2016 and will be rolled out to more instruments across the CME group in 2017.

Unparalleled transparency

For traders, the MBO data offers an opportunity for unparalleled gains in both understanding and improving execution quality. Traders can use the data to simulate execution methods, tweak algorithms and then analyse actual execution performance.

“The key thing about the MBO data is that it offers the ability to see where your orders are with complete transparency so you don’t have to make assumptions as to where you are in any given level,” says Stuart Farr, president of technology firm Deltix, which has developed software to process and analyse the MBO data.

“Using the MBO view you know exactly where your order is so you can run more precise simulations of order execution and with more precise simulations you can fine-tune your algo. Once you have deployed that algo you will be able to analyse the actual performance with significantly more granularity and understand why executions are or are not happening as expected,” he says.

MBO data also offers a view across a greater number of levels than MBL, which provides prices and the quantity of bids and offers at that price for a maximum of ten levels.

Farr says: “MBO shows the individual order sizes that make up the total quantity at a price including the priority in the queue. Each order has a quote ID, which the trader can use to identify their order in the order book and hence the precise position in the queue.”

Any trader that struggles to fully understand why limit orders are not getting filled despite being sent into the market at the best bid or offer will benefit from the MBO data. So too will intra-day trading firms looking to improve the profitability of their strategies.

“Currently firms have no answers to the key question of why fill ratios are not where they want them to be. Using the MBO data they identify exactly why it is they are not being filled,” says Farr.  

Better fill rates and prices

On a recent Webinar with FOW, Deltix used its simulation software to analyse hundreds of thousands of orders to compare simulations using MBO data alongside the MBL data.

The majority of orders were filled at the same time across the two data sets but in a number of instances MBO-based fills were quicker with some taking a tenth of the time it took to fill an MBL-based order.

“MBO based orders fill faster or at the same time as MBL based orders with no exceptions,” says Ilya Gorelik, CEO of Deltix.

In addition, in the simulation there were a number of instances in which an MBO-based order was filled whereas an MBL-based order was cancelled.

“In our simulations around 1% of orders are filled but this can make a huge impact to the strategy,” says Gorelik. “Also in the simulation, 15% of the orders were filled at a better price using MBO-data.”

Data requirements

MBO data is available on the same feed as historic MBL data but has messaging of around 20-30% above current levels for the existing instruments that CME is disseminating the MBO data for.

When it launches the tool on more liquid contracts the amount of data needed to be processed is likely to increase further, potentially causing a strain on existing infrastructures.

Farr says that firms need to ensure they have the data processing capacity to capitalise on the MBO data set. “There is a non-trivial increase in data volumes from using the MBL data,” he says. “You can’t just plug in your existing systems and expect them to be able to absorb this amount of data.

“Firms need to focus on their technology and whether it is capable of dealing with the amount of data, how that data is being consumed and whether it is being processed without delays or buffering.” 

CME’s MBO data represents a step change in transparency over execution quality. Using the data firms, can significantly improve their algorithmic trading strategies with higher fill ratios and better price of fills. To find out more on how you can capitalise on the new data set and for a demo of some of the Deltix tools, listen to the full webinar at






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