82 citations · 194 across the 14 of their papers we have counts for
15 papers
Multi-Agent Reinforcement Learning for Market Making: Competition without Collusion
Ziyi Wang, Carmine Ventre, Maria Polukarov
Algorithmic collusion has emerged as a central question in AI: Will the interaction between different AI agents deployed in markets lead to collusion? More generally, understanding…
ARL-Based Multi-Action Market Making with Hawkes Processes and Variable Volatility
Ziyi Wang, Carmine Ventre, Maria Polukarov
We advance market-making strategies by integrating Adversarial Reinforcement Learning (ARL), Hawkes Processes, and variable volatility levels while also expanding the action space…
Robust Market Making: To Quote, or not To Quote
Ziyi Wang, Carmine Ventre, Maria Polukarov
Market making is a popular trading strategy, which aims to generate profit from the spread between the quotes posted at either side of the market. It has been shown that training m…
An Empirical Analysis on Financial Markets: Insights from the Application of Statistical Physics
Haochen Li, Yi Cao, Maria Polukarov +1
In this study, we introduce a physical model inspired by statistical physics for predicting price volatility and expected returns by leveraging Level 3 order book data. By drawing…
Error in the Euclidean Preference Model
Luke Thorburn, Maria Polukarov, Carmine Ventre
Spatial models of preference, in the form of vector embeddings, are learned by many deep learning and multiagent systems, including recommender systems. Often these models are assu…
Denoised Labels for Financial Time-Series Data via Self-Supervised Learning
Yanqing Ma, Carmine Ventre, Maria Polukarov
The introduction of electronic trading platforms effectively changed the organisation of traditional systemic trading from quote-driven markets into order-driven markets. Its conve…