1,020,036 research outputs found
Strategic Payments in Financial Networks
In their seminal work on systemic risk in financial markets, Eisenberg and Noe [Larry Eisenberg and Thomas Noe, 2001] proposed and studied a model with n firms embedded into a network of debt relations. We analyze this model from a game-theoretic point of view. Every firm is a rational agent in a directed graph that has an incentive to allocate payments in order to clear as much of its debt as possible. Each edge is weighted and describes a liability between the firms. We consider several variants of the game that differ in the permissible payment strategies. We study the existence and computational complexity of pure Nash and strong equilibria, and we provide bounds on the (strong) prices of anarchy and stability for a natural notion of social welfare. Our results highlight the power of financial regulation - if payments of insolvent firms can be centrally assigned, a socially optimal strong equilibrium can be found in polynomial time. In contrast, worst-case strong equilibria can be a factor of ?(n) away from optimal, and, in general, computing a best response is an NP-hard problem. For less permissible sets of strategies, we show that pure equilibria might not exist, and deciding their existence as well as computing them if they exist constitute NP-hard problems
Diversification and Endogenous Financial Networks
We test the hypothesis that interconnections across financial institutions
can be explained by a diversification motive. This idea stems from the
empirical evidence of the existence of long-term exposures that cannot be
explained by a liquidity motive (maturity or currency mismatch). We model
endogenous interconnections of heterogenous financial institutions facing
regulatory constraints using a maximization of their expected utility. Both
theoretical and simulation-based results are compared to a stylized genuine
financial network. The diversification motive appears to plausibly explain
interconnections among key players. Using our model, the impact of regulation
on interconnections between banks -currently discussed at the Basel Committee
on Banking Supervision- is analyzed
Incentivizing Resilience in Financial Networks
When banks extend loans to each other, they generate a negative externality
in the form of systemic risk. They create a network of interbank exposures by
which they expose other banks to potential insolvency cascades. In this paper,
we show how a regulator can use information about the financial network to
devise a transaction-specific tax based on a network centrality measure that
captures systemic importance. Since different transactions have different
impact on creating systemic risk, they are taxed differently. We call this tax
a Systemic Risk Tax (SRT). We use an equilibrium concept inspired by the
matching markets literature to show analytically that this SRT induces a unique
equilibrium matching of lenders and borrowers that is systemic-risk efficient,
i.e. it minimizes systemic risk given a certain transaction volume. On the
other hand, we show that without this SRT multiple equilibrium matchings exist,
which are generally inefficient. This allows the regulator to effectively
stimulate a `rewiring' of the equilibrium interbank network so as to make it
more resilient to insolvency cascades, without sacrificing transaction volume.
Moreover, we show that a standard financial transaction tax (e.g. a Tobin-like
tax) has no impact on reshaping the equilibrium financial network because it
taxes all transactions indiscriminately. A Tobin-like tax is indeed shown to
have a limited effect on reducing systemic risk while it decreases transaction
volume.Comment: 38 pages, 9 figure
Optimal Fragile Financial Networks
We study a financial network characterized by the presence of depositors, banks and their shareholders. Belonging to a financial network is beneficial for both the depositors and banks' shareholders since the return to investment increases with the number of banks connected. However, the network is fragile since banks, which invest on behalf of the depositors, can gamble with depositors' money (making an investment that is dominated in expected terms) when not sufficiently capitalized. The bankruptcy of a bank negatively affects the banks connected to it in the network. First, we compute the social planner solution and the efficient financial network is characterized by a core-periphery structure. Second, we analyze the decentralized solution showing under which conditions participating in a fragile financial network is ex-ante optimal. In particular, we show that this is optimal when the probability of bankruptcy is sufficiently low giving rationale of financial fragility as a rare phenomenon. Finally, we analyze the efficiency of the decentralized financial network. Again, if the probability of bankruptcy is sufficiently low the structure of the decentralized financial network is equal to the e¢ cient one, yielding an ex- pected payo¤ arbitrarily close to the efficient one. However, the investment decision is not the same. That is, in the decentralized network some banks will gamble as compared to the socially preferred outcome.Financial Network;Moral Hazard;Financial Fragility
Financial asset bubbles in banking networks
We consider a banking network represented by a system of stochastic
differential equations coupled by their drift. We assume a core-periphery
structure, and that the banks in the core hold a bubbly asset. The banks in the
periphery have not direct access to the bubble, but can take initially
advantage from its increase by investing on the banks in the core. Investments
are modeled by the weight of the links, which is a function of the robustness
of the banks. In this way, a preferential attachment mechanism towards the core
takes place during the growth of the bubble. We then investigate how the bubble
distort the shape of the network, both for finite and infinitely large systems,
assuming a non vanishing impact of the core on the periphery. Due to the
influence of the bubble, the banks are no longer independent, and the law of
large numbers cannot be directly applied at the limit. This results in a term
in the drift of the diffusions which does not average out, and that increases
systemic risk at the moment of the burst. We test this feature of the model by
numerical simulations.Comment: 33 pages, 6 table
Networks of equities in financial markets
We review the recent approach of correlation based networks of financial
equities. We investigate portfolio of stocks at different time horizons,
financial indices and volatility time series and we show that meaningful
economic information can be extracted from noise dressed correlation matrices.
We show that the method can be used to falsify widespread market models by
directly comparing the topological properties of networks of real and
artificial markets.Comment: 9 pages, 8 figures. Accepted for publication in EPJ
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