31 citations · 63 across the 39 of their papers we have counts for
51 papers
FactorBench: A Portfolio-Aware Benchmark for Automated Factor Mining
Zhuohan Wang, Carmine Ventre
Factor mining seeks to discover signals from financial data that predict future asset returns and guide portfolio construction. Automated factor mining now spans genetic programmin…
SAiFE-gym: Model-based Environments for Automated Market Making with Concentrated Liquidity
Georgios Chionas, Charalampos Kleitsikas, Stefanos Leonardos +2
We present SAiFE_gym, a Python module that provides a collection of simulation environments for studying trading problems in Constant Product Markets (CPMs) with Concentrated Liqui…
NFT-Based Reward Mechanisms: Sybil Farming, Vesting, and Stochastic Verification
Marco Alberto Javarone, Stefanos Leonardos, Carmine Ventre
We study NFT-based reward mechanisms in which a user can create multiple identities and submit fraudulent claims that mature a reward subject to vesting. We assume that the issuer…
Eliciting ESG Preferences for Reinforcement Learning-Based Portfolio Optimization
Giovanni Dispoto, Marcello Restelli, Carmine Ventre
Modern portfolio management increasingly demands a balance between traditional risk-adjusted returns and strict Environmental, Social, and Governance (ESG) mandates. Current Reinfo…
Concentrated Liquidity Provision: a Reinforcement Learning Perspective
Georgios Chionas, Charalampos Kleitsikas, Stefanos Leonardos +2
Automated market makers (AMMs) are a cornerstone of decentralised finance (DeFi). Constant product markets with concentrated liquidity, such as UniswapV3, are now a well-establishe…
FlowLOB: Efficient and Controllable Limit Order Book Generation with Flow Matching
Zhuohan Wang, Andreea Bacalum, Ollie Olby +2
Limit order book (LOB) simulators are most useful to practitioners when they combine realistic market dynamics, computationally efficient sampling, controllable scenario generation…
Diffusion Models in Finance: A Survey
Zhuohan Wang, Carmine Ventre
Diffusion generative models have rapidly emerged as powerful tools for modeling complex financial data. Their appeal is both structural and practical: they offer stable likelihood-…
Interbank Lending Games
Jinyun Tong, Bart de Keijzer, Haoxiang Wang +1
We define and study a lending game to model the interbank money market, in which lending banks strategically allocate their cash to borrowing banks. The interest rate offered by ea…
DiffLOB: Diffusion Models for Counterfactual Generation in Limit Order Books
Zhuohan Wang, Carmine Ventre
Modern generative models for limit order books (LOBs) can reproduce realistic market dynamics, but remain fundamentally passive: they either model what typically happens without ac…
Blockchain Monetary Policy, Strategic Participation, and the Dynamics of Decentralization
Diodato Ferraioli, Paolo Penna, Manvir Schneider +1
Blockchain systems must navigate a fundamental tradeoff between rewarding capable participants for performance and preserving a sufficiently decentralized distribution of stake. We…
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…
DiffVolume: Diffusion Models for Volume Generation in Limit Order Books
Zhuohan Wang, Carmine Ventre
Modeling limit order books (LOBs) dynamics is a fundamental problem in market microstructure research. In particular, generating high-dimensional volume snapshots with strong tempo…
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…
Performative Market Making
Charalampos Kleitsikas, Stefanos Leonardos, Carmine Ventre
Financial models do not merely analyse markets, but actively shape them. This effect, known as performativity, describes how financial theories and the subsequent actions based on…
Bitcoin's Edge: Embedded Sentiment in Blockchain Transactional Data
Charalampos Kleitsikas, Nikolaos Korfiatis, Stefanos Leonardos +1
Cryptocurrency blockchains, beyond their primary role as distributed payment systems, are increasingly used to store and share arbitrary content, such as text messages and files. A…
The Effectiveness of Golden Tickets and Wooden Spoons for Budget-Feasible Mechanisms
Bart de Keijzer, Guido Schäfer, Artem Tsikiridis +1
One of the main challenges in mechanism design is to carefully engineer incentives ensuring truthfulness while maintaining strong social welfare approximation guarantees. But these…
Asymptotic Extinction in Large Coordination Games
Desmond Chan, Bart De Keijzer, Tobias Galla +2
We study the exploration-exploitation trade-off for large multiplayer coordination games where players strategise via Q-Learning, a common learning framework in multi-agent reinfor…
From Competition to Centralization: The Oligopoly in Ethereum Block Building Auctions
Fei Wu, Thomas Thiery, Stefanos Leonardos +1
Block production on the Ethereum blockchain has adopted an auction-based mechanism known as Proposer--Builder Separation (PBS), where validators outsource block creation to builder…
Scalable Signature-Based Distribution Regression via Reference Sets
Andrew Alden, Carmine Ventre, Blanka Horvath
Distribution Regression (DR) on stochastic processes describes the learning task of regression on collections of time series. Path signatures, a technique prevalent in stochastic a…
A Financial Time Series Denoiser Based on Diffusion Model
Zhuohan Wang, Carmine Ventre
Financial time series often exhibit low signal-to-noise ratio, posing significant challenges for accurate data interpretation and prediction and ultimately decision making. Generat…
An Algorithmic Theory of Simplicity in Mechanism Design
Diodato Ferraioli, Carmine Ventre
A growing body of work in economics and computation focuses on the trade-off between implementability and simplicity in mechanism design. The goal is to develop a theory that not o…
Algorithms for Claims Trading
Martin Hoefer, Carmine Ventre, Lisa Wilhelmi
The recent banking crisis has again emphasized the importance of understanding and mitigating systemic risk in financial networks. In this paper, we study a market-driven approach…
Willy Wonka Mechanisms
Thomas Archbold, Bart de Keijzer, Carmine Ventre
Bounded rationality in mechanism design aims to ensure incentive-compatibility for agents who are cognitively limited. These agents lack the contingent reasoning skills that tradit…