BrokerTec
Cboe Futures Exchange (CFE)
Cboe U.S. Equity Options
Chicago Board of Trade (CBOT)
COMEX
Fenics
ICE Futures U.S.
Minneapolis Grain Exchange (MGEX)
Montréal Exchange (MX)
New York Mercantile Exchange (NYMEX)
Nodal Exchange
1In development.
2Access provided via FIX bridge through CN First International Futures Limited.
3Access provided via FIX bridge through local brokers, including Samsung Futures.
In our previous two blog posts, Make Surveillance Smarter and Eliminate Blind Spots With TT Score and Supercharge Your Spoofing Surveillance with TT Score, we described how TT Score utilizes advanced machine learning technology to detect and score complex patterns of manipulative and disruptive trading activity, including but not limited to spoofing, layering, flipping, vacuuming and momentum ignition.
In this post, we will discuss the next phase of TT Score’s evolution, which is the integration of TT Score with the TT platform.
On a blustery wet Tuesday night, 170 traders from all over Australia piled into the WeWork venue to attend the latest Chat with Traders event, hosted by Aaron Fifield.
I enjoy events like this, as it gives us here in TT Sydney a great chance to catch up with existing customers on a social basis. It also creates the opportunity for us to speak to the newer entrants to the market as well as people who trade different asset classes. Personally, there was also a second winning card at this event, and that came in the form of John Moulton aka Rambo. I’ve known John for 29 years, firstly having worked together on the SFE trading floor trading and for the past 10 years as a user of TT’s trading software.
This article was originally published by the National Society of Compliance Professionals. It was co-authored by Jay Biondo, Product Manager, Surveillance, Trading Technologies, along with James G. Lundy, Partner, and Nicholas A.J. Wendland, Counsel, both of Drinker Biddle & Reath LLP.
Trading Technologies’ TT Score is an ideal trade surveillance and compliance solution for detecting trading activities that could potentially be flagged as spoofing by regulators. By using machine learning technology, TT Score identifies patterns of behavior that may prompt regulatory inquiries so that quick corrective action may be taken before the activity becomes an issue for the firm.