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I am an interdisciplinary researcher. My research broadly falls in the area of Complex Systems theory. Complexity aims to understand how microlevel interactions of heterogeneous constituents, who react and adapt to each other and the environment they create, may lead to the emergence of aggregate behaviour that is non trivially predictable from the behaviour of the individual components. Within this broad area my interests have shifted over the years from applications to protein folding and spin glass models, to pattern formation, and, predominantly, to finance and economics. These apparently different topics all relate in some way to the collective behaviour of heterogeneous agents, where agents can be as diverse as amino-acids in a protein, spins, particle of sands, or human beings.

I have been a leading contributor to the development of an approach to complexity in financial markets and economic networks. I have been a pioneer in applying Agent Based Models to uncover the mechanisms that can lead to large fluctuations in financial markets, and to the emergence of systemic risk in interbank markets, as well as to identify regulatory approaches to control these risks. I have applied novel network techniques and big data tools to analyze high frequency financial data and other large datasets. I am the author of more than 50 publications on leading journals in Economics, Finance and Physics and regularly presents my work at international conferences as a keynote or invited speaker.

My current research uses complexity approaches to understand issues in market microstructure, financial stability and systemic risk. I have been doing theoretical, empirical, numerical (Agent Based models) and experimental work in these areas.

Recent projects include the BA/LeverhulmeTrust SG funded “Experiment and Computational Models of Over The Counter Markets “. This work explores how private information percolates through Over the Counter (OTC) markets. Despite the relevance of OTC markets, very few studies have explored how the distribution of trading links affects the way in which uninformed traders learn the private information of insiders, influencing in turn the efficiency and fairness properties of these markets. Our laboratory and computational experiments provide support to the theory that information diffusion is affected by the network structure and by the number and position of insiders. We show that learning is a collaborative, network process, enabled by synergistic interactions rather than by independent, pairwise interactions with better informed agents, and eased by clustering rather than by node degree or centrality. The project also provides a methodological contribution by exploring the synergies between experiments and computer simulations in analysing economic phenomena.

Another project I have recently completed, in collaboration with Jofre-Bonet, Banal-Estanol, Vassallo and Tumminello, looks at how the productivity of UK Universities has changed in response to the REF exercises. We exploit a large database that contains all publications in Economics, Business, Management, and Finance available in Scopus since 2001. We use a synthetic control method to compare the performance of each of the universities based in the UK with counter-factual similar units constructed combining US universities. Our results indicate that the REF increases significantly the research production of the UK universities. The overall number of publications in the UK grew, relative to the control group, across the whole 2009-2014 assessment period but especially towards the end (2012-2014). Still, research productivity, measured by the number of publications per author, did not change, as the number of authors also increased. However, the proportion of publications in top journals increased significantly increased in each of these two areas.

During my recent sabbatical leave I have started working on different aspects of sustainable finance including: (i) indentify policy interventions to encourage Environmental, Social and Governance (ESG) responsible investment, (ii) assess the resilience of supply chains to ESG risks and (iii) identify peer effects in ESG engagement in supply chains.

My previous work has focused on the role played by interbank lending during the subprime crisis. I have introduced methods that can quantify trust and its dynamics using network based measures. I have developed systemic risk indicators, and methods for identifying systemically important banks, based on the topological properties of the network of trades, and its dynamical evolution. I have studied how banks funding rates are affected by banks’ location in the interbank network. I have developed Agent based models (ABM) that can help us understanding what the role interbank exposure may have on the propagation of the financial crisis, and the channels of contagion from the financial sector to the real sector.
Another stream of my research focuses on the role of market microstructure on market quality and the pricing of some exotic options.