University of Verona Researcher Discusses Research in Risk Management (A Semi-Markov Dynamic Capital Injection Problem for Distressed Banks): Insurance – Risk Management

2023 APR 13 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx Policy and Law Daily -- Researchers detail new data in risk management. According to news reporting from Verona, Italy, by NewsRx journalists, research stated, “Our study investigates the optimal dividend strategy for a bank, taking into account the potential for government capital injections.”

The news journalists obtained a quote from the research from University of Verona: “We explore different types of government interventions, such as liberal, transparent, or uncertain strategies, and consider both single and multiple types of interventions. Our approach differs from others as it focuses on interventions that aim to maintain the overall stability of the financial system, rather than just addressing banks that have already sought government assistance or are in dire need of it. Specifically, we focus on situations where the government is more likely to assist banks that have not requested its intervention or that are not too difficult to save. To accomplish this, we conduct a comprehensive examination of all possible scenarios involving a single, one-time capital injection and derive explicit solutions for the associated optimal control problem.”

According to the news reporters, the research concluded: “Furthermore, we expand the model to include semi-Markov dynamic capital injection processes and show that the optimal control is the unique viscosity solution of a Hamilton-Jacobi-Bellman equation. The government’s strategy also takes into account the bank’s solvency and any past government interventions.”

For more information on this research see: A Semi-Markov Dynamic Capital Injection Problem for Distressed Banks. Risks, 2023,11(4). (Risks - http://www.mdpi.com/journal/risks). The publisher for Risks is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/risks11040067.

Our news editors report that additional information may be obtained by contacting Luca Di Persio, Department of Computer Science, College of Mathematics, University of Verona, via Ca’ Vignal 2, 37129 Verona, Italy. Additional authors for this research include Luca Prezioso, Yilun Jiang.

ORCID is an identifier for authors and includes bibliographic information. The following is ORCID information for the author of this research: Luca Di Persio (http://orcid.org/0000-0002-0317-4351).

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