Contributions published at Banking (Stefano Battiston)

A new study published in the journal Science highlights the opportunity to complement current climate mitigation scenarios with scenarios that capture the interdependence among investors’ perception of future climate risk, the credibility of climate policies, and the allocation of investments across low- and high-carbon assets in the economy.

Researchers at the University of Zurich show how climate mitigation scenarios can be improved by taking into account that the financial system can play both an enabling or a hampering role on the path to a sustainable economic system.

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A new study published in the journal Science, highlights the opportunity to complement current climate mitigation scenarios with scenarios that capture the interdependence among investors’ perception of future climate risk, the credibility of climate policies, and the allocation of investments across low- and high-carbon assets in the economy.

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A new study published in the journal Science highlights the opportunity to complement current climate mitigation scenarios with scenarios that capture the interdependence among investors' perception of future climate risk, the credibility of climate policies, and the allocation of investments across low- and high-carbon assets in the economy.

A new study published in the journal Science, highlights the opportunity to complement current climate mitigation scenarios with scenarios that capture the interdependence among investors' perception of future climate risk, the credibility of climate policies, and the allocation of investments across low- and high-carbon assets in the economy.

We study how the practice of collateral rehypothecation impacts the generation of liquidity and the emergence of systemic liquidity risk, and how both depend on the structure of the financial network. We build a basic model where banks interact via chains of “repo” contracts (i.e. repurchasing agreements) and use their proprietary collateral or re-use the collateral obtained by other banks via “reverse repos”. We then extend the model to allow banks to determine endogenously the optimal amount of collateral to rehypothecate, based on the equilibrium level of Value-at-Risk. In this framework, we first show how total collateral volume and its velocity are affected by characteristics of the network such as the length of rehypothecation chains and the existence of closed (i.e. cyclic) chains of contracts, the presence of sink nodes (wherein collateral remains trapped), the direction of collateral flows, and the density of the network. We then demonstrate that a trade-off between liquidity and systemic risk exists for certain classes of networks structures. On the one hand, we show that structures where collateral flows are concentrated among fewer densely connected nodes allow for larger collateral volumes, even at low levels of network density. On the other hand, the same networks are also more exposed to larger cascades of collateral hoarding, as a result of localized liquidity shocks.

The market infrastructure reform carried out in the aftermath of the 2008 financial crisis mandates the central clearing of standardized over-the-counter derivatives. We investigate how this reform can impact on the valuation of derivative contracts and how it can lead to unintended value redistribution effects among market participants. The transition to central clearing changes both the counterparty risk and the funding costs associated with a derivative position. By developing a theoretical model of derivative contract valuation, we clarify how these changes affect the expected value adjustments for a particular dealer and identify the three channels of value redistribution. Moreover, we find that, through these value adjustments, mutualization of risks and collateral in a central clearing counterparty can lead to externalities among the members.

We introduce a general model for the balance‐sheet consistent valuation of interbank claims within an interconnected financial system. Our model represents an extension of clearing models of interdependent liabilities to account for the presence of uncertainty on banks' external assets. At the same time, it also provides a natural extension of classic structural credit risk models to the case of an interconnected system. We characterize the existence and uniqueness of a valuation that maximizes individual and total equity values for all banks. We apply our model to the assessment of systemic risk and in particular for the case of stress testing. Further, we provide a fixed‐point algorithm to carry out the network valuation and the conditions for its convergence.

Over the last decades, both advanced and emerging economies have experienced the emergence of the phenomenon known as financialization, that, until some time ago, was generally considered beneficial for the economy. The 2007-2008 crisis and the severe post-crisis recession called into question the assumptions underlying the positive perception of the role played by financialization in the economy. In particular, the effects of financialization on financial stability and inequality are now widely recognized. A recent debate focused on the effectiveness of unconventional monetary policy tools in transferring their effects on the financial sphere to the economic sphere (e.g., via stimulating the transmission of resources from the banking system to the real economy). Among these unconventional policy measures, Quantitative Easing (QE) 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 QE may generate net flows of additional resources to the real economy. Second, to what extent QE may also alter the pattern of intra-financial exposures among financial actors and what are the implications in terms of financialization. Here, we address these two questions by mapping and analyzing the euro area multilayer macro-network of financial exposures among institutional sectors across financial instruments (i.e., loans, bonds, equity, and insurance and pension schemes) and we illustrate our approach on recently available data. We then test the effect of the implementation of ECB’s QE on some novel measures of financialization that we derive from the time evolution of the financial linkages in the multilayer macro-network of the euro area.

Networks of portfolio holdings exemplify how interdependence both between the agents and their assets can be a source of systemic vulnerability. We study a real-world holdings network and compare it with various alternative scenarios from randomization and rebalancing of the original investments. Scenarios generation relies on algorithms that satisfy the global constraints imposed by the numbers of outstanding shares in the market. We consider fixed-diversification models and diversification-maximizing replicas too. We extensively analyze the interplay between portfolio diversification and differentiation, and how the outreach of exogenous shocks depends on these factors as well as on the type of shock and the size of the network with respect to the market. We find that real portfolios are poorly diversified but highly similar, that portfolio similarity correlates with systemic fragility and that rebalancing can come with an increased similarity depending on the initial network configuration. We show that a large diversification gain is achieved through rebalancing but, noteworthy, that makes the network vulnerable in front of unselective shocks. Also, while the network is riskier in the presence of targeted shocks, it is safer than its random counterparts when it is stressed by widespread price downturns.

We study financial networks and reveal a new kind of systemic risk arising from what we call default ambiguity — that is, a situation where it is impossible to decide which banks are in default. Specifically, we study the clearing problem: given a network of banks interconnected by financial contracts, determine which banks are in default and what percentage of their liabilities they can pay. Prior work has shown that when banks can only enter into debt contracts with each other, this problem always has a unique maximal solution. We first prove that when banks can also enter into credit default swaps (CDSs), the clearing problem may have no solution or multiple conflicting solutions, thus leading to default ambiguity. We then derive sufficient conditions on the network structure to eliminate these issues. Finally, we discuss policy implications for the CDS market.

Network theory proved recently to be useful in the quantification of many properties of financial systems. The analysis of the structure of investment portfolios is a major application since their eventual correlation and overlap impact the actual risk by individual investors. We investigate the bipartite network of US mutual fund portfolios and their assets. We follow its evolution during the Global Financial Crisis and study the diversification, as understood in modern portfolio theory, and the similarity of the investments of different funds. We show that, on average, portfolios have become more diversified and less similar during the crisis. However, we also find that large overlap is far more likely than expected from benchmark models of random allocation of investments. This indicates the existence of strong correlations between fund investment strategies. We exploit a deliberately simplified model of shock propagation to identify a systemic risk component stemming from the similarity of portfolios. The network is still partially vulnerable after the crisis because of this effect, despite the increase in the diversification of multi asset portfolios. Diversification and similarity should be taken into account jointly to properly assess systemic risk.

We study the interplay between two channels of interconnectedness in the banking system. The first one is a direct interconnectedness, via a network of interbank loans, banks' loans to other corporate and retail clients, and securities holdings. The second channel is an indirect interconnectedness, via exposures to common asset classes. To this end, we analyze a unique supervisory data set collected by the European Central Bank that covers 26 large banks in the euro area. To assess the impact of contagion, we apply a structural valuation model NEVA [barucca 2016], in which common shocks to banks' external assets are reflected in a consistent way in the market value of banks' mutual liabilities through the network of obligations. We identify a strongly non-linear relationship between diversification of exposures, shock size, and losses due to interbank contagion. Moreover, the most systemically important sectors tend to be the households and the financial sectors of larger countries because of their size and position in the financial network. Finally, we provide policy insights into the potential impact of more diversified versus more domestic portfolio allocation strategies on the propagation of contagion, which are relevant to the policy discussion on the European Capital Market Union.