Learning to Manipulate a Financial Benchmark
M Shearer, G Rauterberg, and MP Wellman
Proceedings of 4th ACM International Conference on AI in Finance (ICAIF'23), pages 592–600, November 2023.
Abstract
Financial benchmarks estimate market values or reference rates used in a wide variety…
Stability Effects of Arbitrage in Exchange Traded Funds: An Agent-Based Model
M Shearer, D Byrd, TH Balch, and MP Wellman
2nd ACM International Conference on AI in Finance (ICAIF), Article No.: 49, pages 1–9, November 2021.
Abstract
An index-based exchange traded fund (ETF) with underlying securities that trade on…
Learning-Based Trading Strategies in the Face of Market Manipulation
X Wang, C Hoang, and MP Wellman
ACM International Conference on AI and Finance, October 2020.
Abstract
We study learning-based trading strategies in markets where prices can be manipulated through spoofing: the practice of submitting spurious…
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…
Generating Stock Market Data
CSE news item on our AAAI-20 paper, describing a GAN model for financial market order streams.
Generating realistic stock market order streams
J Li, X Wang, Y Lin, A Sinha, and MP Wellman
34th AAAI Conference on Artificial Intelligence, pages 727-734, Feb 2020.
Abstract
We propose an approach to generate realistic and high-fidelity stock market data based on generative adversarial…
A Cloaking Mechanism to Mitigate Market Manipulation
X Wang, Y Vorobeychik, and MP Wellman
27th International Joint Conference on Artificial Intelligence, pages 541–547, July 2018.
Abstract
We propose a cloaking mechanism to deter spoofing, a form of manipulation in financial markets. The…