activity
20192026
most citedABIDES: Towards High-Fidelity Market Simulation for AI Research

35 citations · 46 across the 5 of their papers we have counts for

collaborators

5 papers

q-fin.TR2026

Velocity- and Regime-Aware Detection of Intraday Options Market Manipulation, with Explainable Attribution

Alex Chen, Maria Hybinette

Intraday market manipulation is hard to detect because its footprint is brief, buried in millions of quotes, and statistically similar to ordinary volatility. Detectors reach high…

q-fin.CP2025

Is All the Information in the Price? LLM Embeddings versus the EMH in Stock Clustering

Bingyang Wang, Grant Johnson, Maria Hybinette +1

This paper investigates whether artificial intelligence can enhance stock clustering compared to traditional methods. We consider this in the context of the semi-strong Efficient M…

q-fin.TR2020

The Importance of Low Latency to Order Book Imbalance Trading Strategies

David Byrd, Sruthi Palaparthi, Maria Hybinette +1

There is a pervasive assumption that low latency access to an exchange is a key factor in the profitability of many high-frequency trading strategies. This belief is evidenced by t…

q-fin.TR2019★ 11 cited

How to Evaluate Trading Strategies: Single Agent Market Replay or Multiple Agent Interactive Simulation?

Tucker Hybinette Balch, Mahmoud Mahfouz, Joshua Lockhart +2

We show how a multi-agent simulator can support two important but distinct methods for assessing a trading strategy: Market Replay and Interactive Agent-Based Simulation (IABS). Ou…

cs.MA2019★ 35 cited

ABIDES: Towards High-Fidelity Market Simulation for AI Research

David Byrd, Maria Hybinette, Tucker Hybinette Balch

We introduce ABIDES, an Agent-Based Interactive Discrete Event Simulation environment. ABIDES is designed from the ground up to support AI agent research in market applications. Wh…