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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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1122 · Sep 201219922001200920172026
20 results for bailout stigma

Analyzes how financial network dependencies can lead to multiple equilibrium outcomes and optimal bailout strategies.

problem Multiple equilibrium outcomes in financial networks due to dependency cycles.
method Characterized necessary and sufficient conditions for bank solvency, and provided upper bounds on optimal bailout payments.
result Minimum bailout payments needed to ensure systemic solvency and prevent cascading defaults.

This paper proposes a novel PGO framework to optimize systemic risk bailouts using neural networks.

problem Optimal bailout strategies for mitigating systemic risk in financial systems.
method Prediction-Gradient-Optimization (PGO) framework, using neural networks to approximate and forecast the objective function.
result The PGO framework effectively manages systemic risk through online optimization.

Central bank optimizes bailout cash injection to limit defaults.

problem Optimizing cash injection to limit defaults in a system of mutual obligations.
method Proved convergence and solved a drift controlled Stefan problem using mean field control and policy gradient methods.
result Optimal strategies involve subsidizing banks with equity values in a time-dependent region.

Study uses machine learning to analyze Twitter sentiments about COVID-19.

problem Examining public concerns and sentiments about COVID-19 from Twitter.
method Machine learning (Latent Dirichlet Allocation) to identify topics and sentiments.
result Identified 13 topics and categorized into five themes, revealing dominant fears and mixed feelings.

Graph neural networks improve systemic risk measures for financial networks.

problem Computing systemic risk measures for graph-structured financial networks.
method Extended permutation equivariant neural networks (X-PENNs) for numerical approximation.
result Graph neural networks outperform other methods in approximating optimal allocations.

In this paper we study the financial repercussions of the destruction of two fully armed and operational moon-sized battle stations ("Death Stars") in a 4-year period and the dissolution of the galactic government in Star Wars. The emphasis of this work is to calibrate and simulate a model of the banking and financial …

2015-11-29abs ↗pdf ↗

The financial crisis showed the importance of measuring, allocating and regulating systemic risk. Recently, the systemic risk measures that can be decomposed into an aggregation function and a scalar measure of risk, received a lot of attention. In this framework, capital allocations are added after aggregation and can…

2016-07-12abs ↗pdf ↗

Controversies around race and machine learning have sparked debate among computer scientists over how to design machine learning systems that guarantee fairness. These debates rarely engage with how racial identity is embedded in our social experience, making for sociological and psychological complexity. This complexi…

2018-11-28abs ↗pdf ↗

Systemic risk refers to the risk that the financial system is susceptible to failures due to the characteristics of the system itself. The tremendous cost of systemic risk requires the design and implementation of tools for the efficient macroprudential regulation of financial institutions. The current paper proposes a…

2015-02-27abs ↗pdf ↗

During the last two years, Europe has been facing a debt crisis, and Greece has been at its center. In response to the crisis, drastic actions have been taken, including the halving of Greek debt. Policy makers acted because interest rates for sovereign debt increased dramatically. High interest rates imply that defaul…

2012-09-27abs ↗pdf ↗