Year-end Sale % OFF 
Abstract
The structure of networks plays a central role in the behavior of financial systems and their response to policy. Real-world networks, however, are rarely directly observable: banks’ assets and liabilities are typically known, but not who is lending how much and to whom. This paper adds to the existing literature in two ways. First, it shows how to simulate realistic networks that are based on balance-sheet information. To do so, we introduce a model where links cause fixed-costs, independent of contract size; but the costs per link decrease the more connected a bank is (scale economies). Second, to approach the optimization problem, we develop a new algorithm inspired by the transportation planning literature and research in stochastic search heuristics. Computational experiments find that the resulting networks are not only consistent with the balance sheets, but also resemble real-world financial networks in their density (which is sparse but not minimally dense) and in their core-periphery and disassortative structure.
Highlights
It is well known that the structure of financial networks is important in assessing systemic risk (Allen and Gale 2000; Freixas et al 2000; Lux 2017), but is important in other areas, such as market efficiency or payments processing
To solve it, borrowing from operations research literature for transportation problems, we introduce the permuted North-West-CornerRule in combination with Simulated Annealing, a stochastic optimization technique, which allows reliable solutions to be found within reasonable time. pNWCR provides a solution to an aggregate and static cost minimization problem, which is a solution from the viewpoint of a social planner and not necessarily equivalent to the optimal solution emerging from a disaggregated search of individual contractors in the interbank market
For the problem at hand, we suggest to turn this into a crucial feature of the optimization: we restate the search process as finding permutations of the lenders and borrowers, respectively, that minimizes the costs of a resulting pNWCR network
Summary
It is well known that the structure of financial networks is important in assessing systemic risk (Allen and Gale 2000; Freixas et al 2000; Lux 2017), but is important in other areas, such as market efficiency or payments processing (see Glassermann and Young 2015 for a review). In spite of its importance, the analysis of networks is made difficult by a lack of data for essential markets. For many crucial financial networks, a researcher only has the assets and liabilities of individual agents in a financial network, while the bilateral arrangements between individuals are missing. One strategy for dealing with the lack of network data is to use balance sheet information. The assets and liabilities are reported at an aggregate level, and the absence of granular information prohibits the reconstruction of actual links or contract sizes. Based on simplifying or plausibility assumptions, several methods exist to create or simulate networks that reflect at least the available information; the results reproduce stylized facts only to a varying degree
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
