Abstract
Technological progress and digitalization have always affected the way markets are organized and trading takes place. In very recent years a potentially breakthrough advancement has been brought by blockchain technology. In particular, Decentralized finance (DeFi) is an emerging financial technology based on secure distributed ledgers, which makes it possible to exchange financial products without the need of intermediaries or organized exchanges. The use of decentralized exchanges is nowadays mostly limited to the exchange of cryptocurrency, but it is foreseeable that its use might also revolutionize the exchange and trading activity of more traditional asset classes. While decentralized markets represent an intriguing development of market structure, the implications of the new structure for the role of information in the price discovery process, the measurement, control, and determinants of liquidity and transactions costs, as well as the implications for the efficiency, welfare, and how markets should be designed have not yet been sufficiently explored. Moreover, the systemic implications of the adoption of DeFi and in general of unregulated exchanges are not understood, but are clearly extremely important. The Financial Stability Board has very recently issued a document highlighting the importance of the assessment of risks to financial stability from crypto-assets and DeFi. The aim of this research project is to contribute to fill the gap in the understanding of the market microstructure of decentralized exchanges and of the channels of propagation systemic risk brought by this new technology. This will be done by performing a strict comparison of centralized (CEX) and decentralized exchange (DEX), with the aim of highlighting the specificity of DeFi. In some cases the comparison will consider the same asset (e.g. a crypto-currency exchange rate) traded in centralized and decentralized exchanges, while in others we will consider the comparison across different asset classes. We will consider analytical and computational models of different market structures. As an important example of regulation analysis we will investigate the role of tick size, its optimal dimension both for a single asset and across different securities. We then consider economic and econometric models to understand and quantify systemic in crypto markets as well as risk spill-overs from crypto markets to core financial markets. Moreover, an objective of this research project is an empirical and model-based reassessment of traditional risk-mitigation and regulation approaches that have traditionally characterized financial securities trade and regulation. New emerging business models originated by the so-called ‘Fintech Revolution’ will require new analysis and regulation methods to safeguard investor protection from systemic and liquidity risks and guarantee that financial markets foster equitable and sustainable long-term economic growth. Achieved Results Financial markets are undergoing profound transformations driven by digitalization, artificial intelligence, and blockchain technologies. New forms of trading, decentralized finance, and tokenized assets are creating unprecedented opportunities, while also introducing new risks for market stability, liquidity, and financial regulation. Against this background, the project aimed to improve the understanding of how these innovations affect financial markets and to identify market designs and technological solutions capable of enhancing efficiency, transparency, and resilience. The research combined complementary perspectives. On the one hand, it investigated the microstructure of financial markets, studying how trading mechanisms, liquidity, and algorithmic strategies influence price formation in both traditional centralized exchanges and decentralized blockchain-based markets. On the other hand, it adopted a broader macro-fintech perspective, exploring how blockchain technologies and tokenization can reshape production networks, financial intermediation, and access to capital for firms. The expected outcome of the project was to develop new theoretical models, empirical evidence, and policy-relevant insights capable of supporting the design of more efficient financial markets and of contributing to the safe adoption of emerging financial technologies. The project achieved significant results along both research directions. A first group of results concerns centralized financial markets. The research developed new statistical models of limit order books to better understand how liquidity evolves over time and how it affects the costs of executing large transactions. The analyses showed that adaptive mechanisms of liquidity provision can substantially influence market impact and execution costs. Experimental studies in laboratory also provided the first evidence on how liquidity spillovers across related markets can contribute to the formation of financial bubbles. Additional research demonstrated that rapid changes in market liquidity may create opportunities for price manipulation. Furthermore, the project investigated the behaviour of artificial intelligence trading agents based on deep reinforcement learning. The results revealed that these agents may autonomously learn trading strategies that resemble collusive behaviour, reaching outcomes that are more profitable than competitive equilibria. These findings are particularly relevant given the increasing adoption of AI-based trading systems by the financial industry and the growing attention of regulators to their potential effects on market fairness and stability. A second major area of investigation focused on decentralized finance (DeFi) and cryptocurrency markets. Researchers analysed the dynamics of newly issued crypto tokens traded on decentralized exchanges such as Uniswap and Pump.fun, where liquidity is often extremely limited and prices are highly volatile. The project identified several forms of manipulation, including so-called honeypots, rug-pulls, and sandwich attacks, and studied the factors determining whether newly created tokens become successful. For more mature cryptocurrencies simultaneously traded on centralized and decentralized exchanges, extensive empirical analyses uncovered new statistical regularities in prices and trading volumes that can be linked to sophisticated liquidity manipulation strategies. To better understand these phenomena, the project developed an agent-based model representing both centralized and decentralized markets, including arbitrageurs, liquidity providers, and other market participants. This framework allowed researchers to propose innovative market designs based on dynamic transaction fees, capable of reducing the losses typically incurred by liquidity providers and improving the overall functioning of decentralized exchanges. The project also generated important contributions to market design. New theoretical analyses examined how trading rules influence liquidity provision, price formation, and investor welfare. The research showed that the optimal minimum price increment ("tick size") depends on market characteristics rather than following a universal rule, providing useful guidance for regulators and exchange operators. Additional work proposed innovative auction mechanisms designed to improve transparency, reduce opportunities for manipulation, and limit the costly competition for execution speed that characterizes many modern electronic markets. The second research direction investigated the broader implications of blockchain technologies and tokenization for the organization of economic activity. The project developed new theoretical models showing how decentralized business networks can improve access to finance while remaining exposed to systemic cascades of shocks generated by their complex network structure. These results highlighted the importance of decentralized governance mechanisms capable of coordinating risk sharing among participants. Particular attention was devoted to the valuation of blockchain-based tokens. By constructing a large database of Ethereum ERC20 tokens, the project identified three fundamental drivers of token values: transaction activity, productive and developmental factors, and token supply dynamics. Remarkably, these empirical findings provide strong support for recent theoretical models of token valuation developed in the academic literature. Finally, the project examined the implications of introducing a tokenized digital euro, particularly for business-to-business payments and supply-chain finance. The analyses highlighted both the opportunities and the challenges associated with tokenized money, showing how it could improve liquidity management and facilitate access to financing for networks of small and medium-sized enterprises, while also identifying the liquidity and solvency issues that financial institutions should carefully address. Overall, the project has produced a coherent body of theoretical, empirical, and experimental results that significantly advance our understanding of modern financial markets. Beyond their academic value, these findings provide practical insights for regulators, financial institutions, technology developers, and policymakers seeking to foster innovation while preserving market integrity, financial stability, and investor protection. The scientific results of the project have been published in 16 papers submitted or already printed in international journals and volumes. The research team has presented the results in more than 40 talks in international workshops and conferences and in universities or institutions. Finally, the project teams have organized 5 workshops on the above-mentioned topics.
Project details
Unibo Team Leader: Fabrizio Lillo
Unibo involved Department/s:
Dipartimento di Matematica
Coordinator:
ALMA MATER STUDIORUM - Università di Bologna(Italy)
Total Eu Contribution: Euro (EUR) 200.200,00
Total Unibo Contribution: Euro (EUR) 96.950,00
Project Duration in months: 24
Start Date:
28/09/2023
End Date:
28/02/2026
