
Market manipulation: An adversarial learning framework for detection and evasion
X Wang and MP Wellman
29th International Joint Conference on Artificial Intelligence, Special Track on AI in FinTech, pages 4626–4632, 2020.
Abstract
We propose an adversarial learning framework to capture the evolving game between a regulator…

Algocracy Podcast
Uday Rajan and I appeared on the Algocracy and Transhumanism Project Podcast, hosted by John Danaher, to talk about our recent article on the ethics of automated trading.

Credit networks paper presented at Allerton conference
An Empirical Game-Theoretic Analysis of Credit Network Formation

2012 Trading Agent Competition Results
TAC-12 is now (mostly) history. The Ad Auction (AA) and Supply Chain Management (SCM) divisions had their semifinals and finals in Valencia earlier this month. Results are posted on the TAC web site. The PowerTAC finals were postponed to September.
Our…

The Microsecond Market
IEEE Spectrum has a nice feature article (written by David Schneider) in their June 2012 issue about high-frequency trading and the latency arms race in particular. The article quotes me advocating discrete-time markets.

Going to Liverpool
Visiting the CS dept, will talk about EGTA for Canonical Auction Games.

Trading Agents lecture published
Morgan & Claypool has just published my volume Trading Agents, in its “Synthesis Lecture” series.
Check out the description here.

2010 Trading Agent Competition Results
The eleventh annual Trading Agent Competition was completed earlier this month at the ACM EC-10 conference in Cambridge, Massachusetts. TAC-10 featured three games: the supply chain management (SCM), market design (reverse TAC, or "CAT"),…

Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition
E-commerce increasingly provides opportunities for autonomous bidding agents: computer programs that bid in electronic markets without direct human intervention. Automated bidding strategies for an auction of a single good with a known valuation are fairly straightforward; designing strategies for simultaneous auctions with interdependent valuations is a more complex undertaking. This book presents algorithmic advances and strategy ideas within an integrated bidding agent architecture that have emerged from recent work in this fast-growing area of research in academia and industry.
The authors analyze several novel bidding approaches that developed from the Trading Agent Competition (TAC), held annually since 2000. The benchmark challenge for competing agents—to buy and sell multiple goods with interdependent valuations in simultaneous auctions of different types—encourages competitors to apply innovative techniques to a common task. The book traces the evolution of TAC and follows selected agents from conception through several competitions, presenting and analyzing detailed algorithms developed for autonomous bidding.
Autonomous Bidding Agents provides the first integrated treatment of methods in this rapidly developing domain of AI. The authors—who introduced TAC and created some of its most successful agents—offer both an overview of current research and new results.

Threads of Research on Generic CDA Strategies
Research on trading strategy for generic continuous double auctions (CDAs) seems to take place on four parallel and minimally interacting threads. By “generic CDA”, I mean models of two-sided continuous trading of an abstract good, as distinct…