PUBLICATIONS
A multi-way analysis of international bilateral claims
published in Social Network
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The paper presents a new methodology aimed at detecting the modularity structure of an evolving weighted directed network, identifying communities and central nodes inside each of them, and tracking their common activity over time. The method is based on tensor factorization and it is applied to the Consolidated Banking Statistic, provided by the Bank of International Settlements. Findings show that data are well represented by three communities. The temporal pattern of each community varies according to the events involving the member nodes, showing a decrease of activities during crisis periods, such as the 2008 financial crisis and the European sovereign debt crisis
Booms and bust in a housing market with heterogeneous agents
published in Macroeconomic Dynamics
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We develop a dynamic partial equilibrium model of the housing market, in which the dynamics of the house price is determined by the interaction between chartists and fundamentalists. The model endogenously generates episodes of boom and bust in the house price and can replicate the recent US house price dynamics, and points to endogenous and exogenous behavioral factors as the main determinants of such dynamics.
Coexistence of equilibria in a New Keynesian model with heterogeneous beliefs
published in Chaos Solitons & Fractals
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The recent macroeconomic literature has been stressing the importance of considering heterogeneous expectations while addressing monetary policy. In this paper we consider a standard New Keynesian model, described by a two-dimensional non linear map,to analyze the bifurcation structure when agents have heterogeneous expectations and update their beliefs based on past performance. Depending on the degree of reactivity of the monetary policy to inflation and output deviations from the target equilibrium, different kind of dynamics may occur. We find that multiple equilibria and complicated dynamics, associated to codimension-2bifurcations, may arise even if the monetary policy is set to respond more than point for point to inflation, as theTaylor principle prescribes. We show that if the monetary policy accommodates for a sufficient degree of output stabilization, complicated dynamics can be avoided and the number of coexisting equilibria reduces.
Discovering SIFIs in Interbank Communities
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This paper proposes a new methodology based on non-negative matrix factorization to detect communities and to identify central nodes in a network as well as within communities. The method is specifically designed for directed weighted networks and, consequently, it has been applied to the interbank network derived from the e-MID interbank market. In an interbank network indeed links are directed, representing flows of funds between lenders
and borrowers. Besides distinguishing between Systemically Important Borrowers and Lenders, the technique complements the detection of systemically important banks, revealing the community structure of the network, that proxies the most plausible areas of contagion of institutions' distress.
Financial market predictability with tensor decomposition and links forecast
published in Applied Network Science
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Inspecting financial markets from a complex network perspective means to extract relationships and interdependencies from stock price time series. Correlation networks have been shown to adequately capture such dependence structures between financial assets. Moreover, researchers have observed modifications in the correlation structure between stock prices in the face of a market turbulence. This happens because financial markets experience sudden regime shifts near phase transitions such as a financial crisis. These abrupt and irregular fluctuations from one state to another lead to an increase of the correlation between the units of
the system, lowering the distances between the stocks in a correlation network. The aim of this paper is to predict such abrupt changes by inferring the forthcoming dynamic of stock prices through the prediction of future distances between them. By introducing a tensor decomposition technique to empirically extract complex relationships from prices’ time series and using them in a portfolio maximization application, this work first illustrates that, near critical transitions, there exit spatial signals such as an increasing spatial correlation. Secondly using this information in a
portfolio optimization context it shows the ability of the methodology in forecasting future stock prices through these spatial signals. The results demonstrate that an optimization approach aiming at minimizing the interconnectedness risk of a portfolio by maximizing the signals produced by tensor decomposition induces investment plans superior to simpler strategies. Trivially speaking portfolios made up of strongly connected assets are more vulnerable to shock events than portfolios of low interconnected assets since heavily connected assets, being close to a transition
point, carry a significant amount of interconnectedness risk, i.e. tail events propagate
more quickly to these assets.
Discovering SIFIs in Interbank Communities
published in Plos-one
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Inflation Targeting, Recursive Inattentiveness, and Heterogeneous Beliefs
published in Journal of Money Credit and Banking
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We consider a monetary authority that provides an explicit inflation target in order to align expectations with the policy objective. However, biased perceptions of the target may arise due to imperfect information flows. We allow agents to revise expectations over time and we model their recursive choice among prediction strategies as an optimization problem under rational inattention. We then investigate whether a simple policy rule can steer the economy toward the targeted equilibrium. Our findings suggest that determinacy under rational expectations may not be sufficient to reach the target. Instead, monetary policy should be fine-tuned to correct agents’ biased beliefs.
Graphical Network Models for International Financial Flows
published in Journal of Business and Economics statistics
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The late-2000s financial crisis stressed the need to understand the world financial system as a network of countries, where cross-border financial linkages play a fundamental role in the spread of systemic risks. Financial network models, which take into account the complex interrelationships between countries, seem to be an appropriate tool in this context. To improve the statistical performance of financial network models, we propose to generate them by means of multivariate graphical models. We then introduce Bayesian graphical models,which can take model uncertainty into account, and dynamic Bayesian graphical models, which provide a convenient framework to model temporal cross-border data, decomposing the model into autoregressive and contemporaneous networks. The article shows how the application of the proposed models to the Bank of International Settlements locational banking statistics allows the identification of four distinct groups of countries, that can be considered central in systemic risk contagion.
Managing monetary policy in a New Keynesian model with many beliefs types
published in Economic letters
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This paper considers a standard New Keynesian model with heterogeneous expectations on the future level of inflation and output. A biased perception of the target pursued by the Central Bank may arise due to idiosyncrasies in information processing, leading to heterogeneous beliefs about the target. We consider an arbitrarily large number of agents’ beliefs and apply the concept of Large Type Limit. We find that an increase in the sensitivity of agents in selecting the optimal prediction strategy or in the spread of beliefs is crucial for the extent of the Central Bank to stabilize the economy. When the predictors are largely dispersed around the target, the Taylor principle is a requisite for stability since it prevents the selffulfilling reinforcement mechanism between the realizations of the relevant macroeconomic variables and the forecasts of the agents. When the set of beliefs is somehow anchored to the target, stability can be achieved with weaker monetary policy.
Monetary Feedback rules and equilibrium determinacy in pure exchange overlapping generation model published in Macroeconomic dynamics
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This paper considers a pure exchange overlapping generations model in which the money-growth rate is endogenous and follows a feedback rule. Different specifications for the monetary policy rule are analyzed, namely a so-called current, forward, or backward-looking feedback rule, depending on whether the monetary authority uses the actual, expected, or last observed values of the inflation rate to set the monetary policy. We study how the responsiveness of the policy rule with respect to inflation affects the determinacy of the monetary equilibrium. A policy rule is called aggressive (moderate) if it responds strongly (moderately) to inflation deviations from the target. We show how aggressive feedback rules, depending on the considered timing, can reinforce mechanisms that lead to indeterminacy or may lead the inflation rate to fluctuate around the monetary equilibrium at which monetary policy is aggressive. A leaning against the wind policy seems to be more desirable from an equilibrium determinacy point of view. On the contrary, a leaning with the wind policy could not be the recommended policy for the Central Bank.
Monetary Feedback rules and equilibrium determinacy in pure exchange overlapping generation model published in Macroeconomic dynamics
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This paper considers a pure exchange overlapping generations model in which the money-growth rate is endogenous and follows a feedback rule. Different specifications for the monetary policy rule are analyzed, namely a so-called current, forward, or backward-looking feedback rule, depending on whether the monetary authority uses the actual, expected, or last observed values of the inflation rate to set the monetary policy. We study how the responsiveness of the policy rule with respect to inflation affects the determinacy of the monetary equilibrium. A policy rule is called aggressive (moderate) if it responds strongly (moderately) to inflation deviations from the target. We show how aggressive feedback rules, depending on the considered timing, can reinforce mechanisms that lead to indeterminacy or may lead the inflation rate to fluctuate around the monetary equilibrium at which monetary policy is aggressive. A leaning against the wind policy seems to be more desirable from an equilibrium determinacy point of view. On the contrary, a leaning with the wind policy could not be the recommended policy for the Central Bank.
Shareholding relationships in the Euro Area banking market: A network perspective published in Physica A
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In this paper we analyze the topological properties of the network of the Euro Area banking market network, with the primary aim of assessing the importance of a bank in the financial system with respect to ownership and control of other credit institutions. The network displays power law distributions in both binary and weighted degree metrics indicating a robust yet fragile structure and a direct link between an increase of control diversification and a rise in the market power. Therefore while in good time the network is seemingly robust, in bad times many banks can simultaneously go into distress. This behavior paves the way for Central bank’s actions. In particular we investigate whether the Single Supervisory Mechanism introduced by the European Central Banks and based on banks’ total asset is a good proxy to quantify their systemic importance. Results indicate that not all the financial institutions with high valued total assets are systemically important but only few of them. Moreover the network structure reveals that control is highly concentrated, with few important shareholders approximately controlling a separate subset of banks.
Shareholding relationships in the Euro Area banking market: A network perspective published in Physica A
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In this paper we analyze the topological properties of the network of the Euro Area banking market network, with the primary aim of assessing the importance of a bank in the financial system with respect to ownership and control of other credit institutions. The network displays power law distributions in both binary and weighted degree metrics indicating a robust yet fragile structure and a direct link between an increase of control diversification and a rise in the market power. Therefore while in good time the network is seemingly robust, in bad times many banks can simultaneously go into distress. This behavior paves the way for Central bank’s actions. In particular we investigate whether the Single Supervisory Mechanism introduced by the European Central Banks and based on banks’ total asset is a good proxy to quantify their systemic importance. Results indicate that not all the financial institutions with high valued total assets are systemically important but only few of them. Moreover the network structure reveals that control is highly concentrated, with few important shareholders approximately controlling a separate subset of banks.
Structural changes in cross-border liabilities: A multidimensional approach
published in Physica A
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We study the international interbank market through a geometric analysis of empirical data. The geometric analysis of the time series of cross-country liabilities shows that the systematic information of the interbank international market is contained in a space of small dimension. Geometric spaces of financial relations across countries are developed, for
which the space volume, multivariate skewness and multivariate kurtosis are computed. The behavior of these coefficients reveals an important modification acting in the financial linkages since 1997 and allows us to relate the shape of the geometric space that emerges in recent years to the globally turbulent period that has characterized financial systems since the late 1990s. Here we show that, besides a persistent decrease in the volume of the geometric space since 1997, the observation of a generalized increase in the values of the multivariate skewness and kurtosis sheds some light on the behavior of cross-border interdependencies during periods of financial crises. This was found to occur in such a systematic fashion, that these coefficients may be used as a proxy for systemic risk.
The interconnected nature of financial systems: Direct and common exposures
published in Journal of Banking and Finance
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To capture systemic risk related to network structures, this paper introduces a measure that complements direct exposures with common exposures, as well as compares these to each other. Trying to address the interconnected nature of financial systems, researchers have recently proposed a range of approaches for assessing network structures. Much of the focus is on direct exposures or market-based estimated networks, yet little attention has been given to the multivariate nature of systemic risk, indirect expo- sures and overlapping portfolios. In this regard, we rely on correlation network models that tap into the multivariate network structure, as a viable means to assess common exposures and complement direct linkages. Using BIS data, we compare correlation networks with direct exposure networks based upon conventional network measures, as well as we provide an approach to aggregate these two components for a more encompassing measure of interconnectedness.
The interconnected nature of financial systems: Direct and common exposures
published in Journal of Banking and Finance
​
To capture systemic risk related to network structures, this paper introduces a measure that complements direct exposures with common exposures, as well as compares these to each other. Trying to address the interconnected nature of financial systems, researchers have recently proposed a range of approaches for assessing network structures. Much of the focus is on direct exposures or market-based estimated networks, yet little attention has been given to the multivariate nature of systemic risk, indirect expo- sures and overlapping portfolios. In this regard, we rely on correlation network models that tap into the multivariate network structure, as a viable means to assess common exposures and complement direct linkages. Using BIS data, we compare correlation networks with direct exposure networks based upon conventional network measures, as well as we provide an approach to aggregate these two components for a more encompassing measure of interconnectedness.
The topology of cross-border exposures: Beyond the minimal spanning tree approach
published in Physica A
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The recent financial crisis has stressed the need to understand financial systems as networks of interdependent countries, where cross-border financial linkages play the fundamental role. It has also been emphasized that the relevance of these networks relies on the representation of changes follow on the occurrence of stress events. Here, from series of interbank liabilities and claims over different time periods, we have developed networks of positions (net claims) between countries. Besides the Minimal Spanning Tree analysis of the time-constrained networks, a coefficient of residuality is defined to capture the structural evolution of the network of cross-border financial linkages. Because some structural changes seem to be related to the role that countries play in the financial context, networks of debtor and creditor countries are also developed. Empirical results allows to relate the network structure that emerges in the last years to the globally turbulent period that has characterized financial systems since the latest nineties. The residuality coefficient highlights an important modification acting in the financial linkages across countries in the period 1997–2011, and situates the recent financial crises as replica of a larger structural change going on since 1997.