Identifying Market Spoofing with Data Visualizations

I love data and data visualizations. They can give deep insight into problems and behaviours, and they can make you interested in something you previously thought dull.

I came across the article “How to Catch a Spoofer” from Bloomberg, by Matthew Leising, Mira Rojanasakul and Adam Pearce. The article gives a fascinating view into the trading activity on the Chicago futures exchange, and how to identify “spoofing” within trading activity. The visualizations take a combination of a difficult concept and large volume of data, and extract genuine, novel insights.

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Time Travel with Reactive Extensions

The Reactive Extensions (Rx) library is one of those tools that opens up your mind to new ways of thinking about your how your data and application work together. In this post I’m going to talk about an easy technique you can use to replay time series data as if it were live.

Replaying time with HistoricalScheduler

Schedulers in Rx are a deep subject, but one of the things schedulers are responsible for is managing how time based operations run. All time based operations in Rx, like Timeout, Delay, etc allow you to provide your own scheduler.

HistoricalScheduler inherits from VirtualTimeScheduler, and that name gives us an idea what we can do with it. VirtualTimeScheduler gives us control of time – at least as far as our code goes. You can’t go back in time and buy stocks to become rich, but you can make your code think it’s doing that.

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