CME Outage, Quant Models, and Prices

 

Prices are the lifeblood of any quant model. If you have the wrong input, you will get incorrect predictions. In the case of an outlier, a single incorrect price may generate misleading signals about future opportunities, so any model should be thoroughly reviewed to assess its sensitivity to wayward signals. 

If there are incorrect inputs, the model output should be adjusted to reflect the change in data when a replacement is made. Users have to be alerted to any changes. These are easy cases to deal with. There are also more difficult issues, such as data oddities or anomalies. 

For example, the CME outage during the Thanksgiving period is a market anomaly that has to be addressed, especially given that it occurred at month-end. To provide context, there was an 11-hour system outage ending at 1335 GMT. It was during the Thanksgiving break, which is associated with low trading volume in the US, but it impacted all global markets on a Friday, a month-end. An outage will lead to a change in trading and a surge upon reopening. Hence, the inputs for open, high, low, and close will be distorted from what they would be in the absence of an outage. This will lead to slightly different signals generated from any model. 

So what should a modeler do about this? One response is that the price is the price and to do nothing. It is reasonable and defensible, yet it may seem odd not to account for some distortion; however, there is no way to determine the impact of any outage. What would be the right price? Another option is to drop the price to the last close. This can be defended, but replacing data seems somewhat arbitrary. 

The best response is to focus on the output and look at the marginal trade signals generated. Does it matter? An output sensitivity analysis can be conducted to see what happens with the new prices, rather than looking at what would have happened if no change had been made. If there are small marginal changes, then keep the latest prices. If there is a large set of new signals, investigate further on why and flag the changes. The prices can be kept, but the flagged trades can be ignored. However, this creates another set of problems if the trade is closing an existing position. When do you exit the old position?

These real-life problems tell the user that there is no such thing as a fully automated system.