394 research outputs found
Production networks and failure avalanches
Although standard economics textbooks are seldom interested in production
networks, modern economies are more and more based upon suppliers/customers
interactions. One can consider entire sectors of the economy as generalised
supply chains. We will take this view in the present paper and study under
which conditions local failures to produce or simply to deliver can result in
avalanches of shortage and bankruptcies across the network. We will show that a
large class of models exhibit scale free distributions of production and wealth
among firms and that metastable regions of high production are highly
localised
Systemic risk in a network fragility model analyzed with probability density evolution of persistent random walks
We study the mean field approximation of a recent model of cascades on
networks relevant to the investigation of systemic risk control in financial
networks. In the model, the hypothesis of a trend reinforcement in the
stochastic process describing the fragility of the nodes, induces a trade-off
in the systemic risk with respect to the density of the network. Increasing the
average link density, the network is first less exposed to systemic risk, while
above an intermediate value the systemic risk increases. This result offers a
simple explanation for the emergence of instabilities in financial systems that
get increasingly interwoven. In this paper, we study the dynamics of the
probability density function of the average fragility. This converges to a
unique stable distribution which can be computed numerically and can be used to
estimate the systemic risk as a function of the parameters of the model.Comment: 20 pages, 6 figure
The Community Structure of the Global Corporate Network
We investigate the community structure of the global ownership network of
transnational corporations. We find a pronounced organization in communities
that cannot be explained by randomness. Despite the global character of this
network, communities reflect first of all the geographical location of firms,
while the industrial sector plays only a marginal role. We also analyze the
network in which the nodes are the communities and the links are obtained by
aggregating the links among firms belonging to pairs of communities. We analyze
the network centrality of the top 50 communities and we provide the first
quantitative assessment of the financial sector role in connecting the global
economy
DebtRank: A microscopic foundation for shock propagation
The DebtRank algorithm has been increasingly investigated as a method to
estimate the impact of shocks in financial networks, as it overcomes the
limitations of the traditional default-cascade approaches. Here we formulate a
dynamical "microscopic" theory of instability for financial networks by
iterating balance sheet identities of individual banks and by assuming a simple
rule for the transfer of shocks from borrowers to lenders. By doing so, we
generalise the DebtRank formulation, both providing an interpretation of the
effective dynamics in terms of basic accounting principles and preventing the
underestimation of losses on certain network topologies. Depending on the
structure of the interbank leverage matrix the dynamics is either stable, in
which case the asymptotic state can be computed analytically, or unstable,
meaning that at least one bank will default. We apply this framework to a
dataset of the top listed European banks in the period 2008 - 2013. We find
that network effects can generate an amplification of exogenous shocks of a
factor ranging between three (in normal periods) and six (during the crisis)
when we stress the system with a 0.5% shock on external (i.e. non-interbank)
assets for all banks.Comment: 10 pages, 2 figure
A climate risk assessment of sovereign bonds' portfolio.
Aligning finance to sustainability requires metrics and methods to price forward-looking cli-mate risks and opportunities in financial contracts and in investors' portfolios. Traditionalapproaches to financial pricing cannot incorporate the nature of climate risks, i.e. deep uncertainty, non-linearity, complexity and endogeneity. To fill this gap, we develop a frameworkfor climate-financial risk assessment and management under uncertainty. We consider a riskaverse investor with an information set given by past market valuation, information on futureclimate economic shocks, and utility maximization based on the minimization of the ClimateValue at Risk (VaR) in presence of incomplete markets. We then consider a disorderly policy transition to 2°C scenarios that leads to unanticipated shocks in economic trajectories of fossil fuel and renewable energy sectors, estimated using Integrated Assessment Models. We model the shock transmission from the change in sectors' Gross Value Added to firms' profitability and to sovereign fiscal revenues. We then introduce the forward-looking climatepolicy shocks in sovereign bonds valuation introducing scenario- conditioned financial riskmetrics (Climate VaR, Climate Spread). We provide an application to OECD sovereignbonds of Austrian National Bank's portfolio. We find that investments' climate alignmentcan strengthen the sovereign fiscal and financial position by decreasing the climate spread. In contrast, misalignment can negatively affect countries' economic competitiveness and financial stability, and thus the performance of investors who own such bonds. Our analysissupports investors' portfolios risk management strategies in the low-carbon transition andand financial supervisors in the design of prudential risk measures
Two sides of the same coin: Green Taxonomy alignment versus transition risk in financial portfolios
We develop the first top-down method to estimate the greenness of financial portfolios, in terms of alignment to the EU Taxonomy for sustainable activities. We also develop a method to estimate, at the same time, the portfolio exposure to climate transition risk. We provide sector-level, standardized and transparent coefficients for both estimates, based on definitions of greenness and transition risk that are applicable across countries. We analyse the portfolios of Euro Area investors in 2022, based on the confidential Securities Holdings Statistics of the European Central Bank. We find that, overall, the greenness of Euro Area investors’ portfolios is lower than their exposure to transition risk (2.8% vs. 11.7%).
Across financial institutions, we estimate greenness and exposure to transition risk, respectively, at 3.2% and 12% for investment funds, at 0.8% and 5% for banks and at 4.8% and 15.1% for insurers. Our analysis also shows that investors with large amounts invested in green activities can have at the same time large exposures to transition risk
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