Contributions published at Banking (Stefano Battiston)

We develop a framework to analyse the credit default swap (CDS) market as a network of risk transfers among counterparties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counterparties: (i) Ultimate Risk Sellers (URS), (ii) Dealers (indirectly connected to each other), (iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counterparty risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011–2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and that the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.

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In this video, I briefly explain my PhD research work which I have been doing at the University of Zurich, Department of Banking and Finance, as a part of the Marie Curie program BigDataFinance: http://bigdatafinance.eu/

The long-lasting socio-economic impact of the global financial crisis has questioned the adequacy of traditional tools in explaining periods of financial distress as well as the adequacy of the existing policy response. In particular, the effect of complex interconnections among financial institutions on financial stability has been widely recognized. A recent debate focused on the effects of unconventional policies aimed at achieving both price and financial stability. In particular, Quantitative Easing (QE, i.e., the large-scale asset purchase programme conducted by a central bank upon the creation of new money) has been recently implemented by the European Central Bank (ECB). In this context, two questions deserve more attention in the literature. First, to what extent, by injecting liquidity, the QE may alter the bank-firm lending level and stimulate the real economy. Second, to what extent, the QE may also alter the pattern of intra-financial exposures among financial actors (including banks, investment funds, insurance corporations and pension funds) and what are the implications in terms of financial stability. Here, we address these two questions by developing a methodology to map the macro-network of financial exposures among institutional sectors across financial instruments (i.e., equity, bonds and loans) and we illustrate our approach on recently available data (i.e., data on loans and private and public securities purchased within the QE). We then test the effect of the implementation of ECB’s QE on the time evolution of the financial linkages in the macro-network of the euro area as well as the effect on macroeconomic variables, such as output and prices.

We address the question of how can publicly accessible information be used to make a map of the political actors and their leanings, that would benefit both policy makers and stakeholders in the European Commission’s ‘Better regulation agenda’ and contribute to social stability. We explore this possibility by using data from the Transparency Register and the open public consultations of the European Commission in the area of Banking and Finance. We compare lobbying organizations active in this area according to three criteria: (i) their formal categorization in the Transparency Register, (ii) their self-declared goals and activities, and (iii) their leanings towards policy issues as derived from their responses to public consultations. We combine methods from information retrieval, text mining, and network analysis to obtain insights on the policy arena. We find that constructing a similarity network based on preference patterns adds a crucial dimension in the understanding of how lobby organizations engage in the policy making process.

Existing approaches to assess the economic impact of climate policies tend to limit their analysis to estimating the direct effect of a policy on the specific institutional sector targeted by the policy itself (e.g. banks, firms), thus underestimating its overall effect. In order to fill this gap, we develop a methodology, based on financial networks, to analyse the transmission throughout the economy of positive or negative shocks induced by the introduction of climate policies. In particular, this methodology allows to identify the feedback loops between the financial sector and the real economy through direct and indirect chains of financial exposures across multiple financial instruments (i.e. loans, equity, bonds, and life insurance). We illustrate the methodology on empirical data of the Euro Area. We focus on policy-induced shocks that affect directly either the banking sector or the non-financial firms, and we analyse the most relevant feedback loops that can reinforce the effect of such shocks. This analysis helps to understand the conditions for virtuous or vicious cycles to arise in the finance-climate nexus and to improve the assessment of the economic impact of climate policies.

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The recent credit crisis of 2007/08 has raised a debate about the so-called knife-edge properties of financial markets. The paper contributes to the debate shedding light on the controversial relation between risk-diversification and financial stability. We model a financial network where assets held by borrowers to meet their obligations, include claims against other borrowers and securities exogenous to the network. The balance-sheet approach is conjugated with a stochastic setting and by a mean-field approximation the law of motion of the system's fragility is derived. We show that diversification has an ambiguous effect and beyond a certain levels elicits financial instability. Moreover, we find that risk-sharing restrictions create a socially preferable outcome. Our findings have significant implications for future policy recommendation.

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“Who owns the information, he owns the world”. This phrase became famous in 1815 when Rothschild family managed to earn about 3 billion British Pounds and became the owners of a large part of the British economy in one day, simply by having a bit more information about results of the famous Waterloo battle than other traders. Today huge companies, such as Google, Bloomberg or Facebook one way or another make their money processing and selling structured information such as political news or users behaviour to other companies and individuals. There is no need to say that these days clear and instantly delivered information is more important than ever. Apparently, there are hundreds or thousands methods and types of information which can be extracted from the big amounts of data.

The latest impressive technological advancements in the telecommunications domain have entailed the involvement of new network operators and over-the-top (OTT) providers that offer their services over the existing networks. This entry of new stakeholders has changed the Internet dynamics and triggered a long-standing conversation on whether different types of data in the network should be prioritized, also known as the network neutrality debate. On the one hand, OTT providers benefit from the current neutral Internet policy of not discriminating against any application or content in order to transfer their data for free, whereas network providers would like to seize the business opportunity and create revenues by supporting the prioritized delivery of data. In this article, we want to shed light on the emerging Internet ecosystem and the conflicting interests of its stakeholders. To that end, we first identify the different Internet players and describe their interrelationships. Furthermore, in an effort to offer a new perspective on the network neutrality debate, we propose two novel econometric models that employ recent financial data to capture the relationship between the OTT revenues and the financial gains and investments of the telecommunication operators. Our empirical results provide tangible answers to fundamental questions that had not been answered before, showcasing that OTT and telecommunication providers have aligned interests and their collaboration could be beneficial to both parties.

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Step-in risk guidelines could be taken more seriously in the EU than in the US

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The Global Crisis highlighted how linkages between banks and shadow banking entities can lead to the amplification of shocks across borders and sectors, prompting policymakers to seek to improve the monitoring framework for assessing the interconnectedness of the shadow banking system. This column documents the cross-sector and cross-border exposures of EU banks to globally domiciled shadow banking entities. Among the findings are that 60% of these exposures are to shadow banking entities domiciled outside the EU and hence outside its supervisory powers, and that approximately 65% of the exposures are to non-money market fund investment funds, finance companies, and securitisation entities.

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