Strong Approximations and Irrationality in Financial Networks with Financial Derivatives
Stavros D. Ioannidis, Bart de Keijzer, Carmine Ventre

TL;DR
This paper investigates the computational complexity and structural properties of financial networks with derivatives, focusing on the irrationality and approximation of solutions to the clearing problem, revealing new complexity classifications.
Contribution
It establishes FIXP-completeness for strongly approximate solutions and identifies structural conditions leading to irrational solutions in financial networks.
Findings
Weakly approximate solutions may misrepresent financial states.
Strong approximation is FIXP-complete.
Certain cycles in networks induce irrational recovery rates.
Abstract
Financial networks model a set of financial institutions (firms) interconnected by obligations. Recent work has introduced to this model a class of obligations called credit default swaps, a certain kind of financial derivatives. The main computational challenge for such systems is known as the clearing problem, which is to determine which firms are in default and to compute their exposure to systemic risk, technically known as their recovery rates. It is known that the recovery rates form the set of fixed points of a simple function, and that these fixed points can be irrational. Furthermore, Schuldenzucker et al. (2016) have shown that finding a weakly (or "almost") approximate (rational) fixed point is PPAD-complete. We further study the clearing problem from the point of view of irrationality and approximation strength. Firstly, we observe that weakly approximate solutions may…
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Taxonomy
TopicsBanking stability, regulation, efficiency · Credit Risk and Financial Regulations · Economic theories and models
