About Me
I am an Assistant Professor of Finance at Durham University Business School. I obtained my Ph.D. in Financial Economics from Goethe University Frankfurt in April 2023.
Research Interests
- Financial Technology
- Blockchain Economics, Decentralized Finance
- Corporate Finance, Corporate Governance
- Data Science, Machine Learning, Artificial Intelligence (AI)
Publications
Conflicts of Interest and Market Failures in Unregulated Capital Markets: Evidence from ICO Analysts
Chapter in Blockchain Scholars Book, edited by Daniel Liebau and Simon Trimborn, Springer Nature , 2026
Conflicted Analysts and Initial Coin Offerings
Management Science 69 (11), 6641-6666 , 2023
This paper studies the contribution of analysts to the functioning and failure of the market for initial coin offerings (ICOs). The assessments of freelancing analysts exhibit biases because of reciprocal interactions of analysts with ICO team members. Even favorably rated ICOs tend to fail raising some capital when a greater portion of their ratings reciprocate prior ratings. Ninety days after listing on an exchange, the market capitalization relative to the initial funds raised is smaller for tokens with more reciprocal ratings. These findings suggest that conflicts of interest help explain the failure of ICOs.
Working Papers
Finance beyond Traditional Intermediaries: Trading and Lending in Tokenized Real Estate
Asset tokenization and decentralized finance restructure key intermediation functions. Liquidity is provided by pooled capital, which is governed by automated market-making rules, rather than by dealer balance sheets. Credit is extended against overcollateralized positions, with algorithmic enforcement, rather than by banks. We study these mechanisms in RealT’s tokenized real estate ecosystem. We show that when assets are tokenizes they depend on local house price growth. Using on-chain microdata that link secondary-market trades to borrowers’ collateral and debt positions, we show that borrowing activity is associated with higher buy-side price premia.
Decentralized Autonomous Organizations
Decentralized autonomous organizations (DAOs) implement governance by code, i.e., participants make collective decisions under specified mechanisms, and outcomes are enforced on public blockchains. Many of these mechanisms (including delegation, participation incentives, dynamic voting rules, prediction markets, and AI agents) have previously been only theorized or tested in limited settings. As such, DAOs provide evidence on institutional design and governance trade-offs that would otherwise be difficult to observe. In this paper, we review these designs and synthesize evidence on stability and economic effects. Where documented, DAOs mobilize millions of dollars and coordinate investment, although most activity remains on-chain. In general, governance by code appears most effective in environments with repeated decisions and rapid feedback, where participants learn from realized outcomes and adapt governance in response to user preferences. Integration into broader ecosystems through partnerships and functional dependencies can further strengthen network effects. We conclude with directions for future research.
Media: YouTube
Delegated Control, Agency Conflicts and Governance Cycles in Token-Based Platforms
Token-based platform governance has evolved into a mediated voting system, in which users outsource voting to specialized agents. While this vote delegation can improve governance efficiency, it also reintroduces agency conflicts. We develop a dynamic principal-agent model in which agents are initially unknown and exert effort to build reputation. However, as perceived quality (reputation) rises, users rationally reduce active oversight. This decline in monitoring increases agents’ returns to opportunism and misconduct, eventually leading to governance failures and agent turnover. To mitigate these governance cycles, we show that designs that slow reputation accumulation and use token-based compensation improve the platform’s stability.
How Do Shareholder Defaults Influence Corporate Governance in DeFi Lending?
We analyze user voting participation in governance on token-based digital platforms and show how this behavior changes under financial stress. Using novel user-proposal-level data from 10 DeFi lending platforms, we find that borrowers (financially exposed users with collateralized positions) engage more actively in governance than passive token holders. Voting activity increases significantly before a potential liquidation, when users have the most at stake, as they try to protect their financial health. After liquidation, voting participation declines significantly. These findings suggests that token-based governance helps mitigate platform-user conflicts but tends to become more short-term driven when linked to active platform use.
