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Optimal risk and liquidity management with costly refinancing opportunities

Barth, Andrea; Moreno-Bromberg, Santiago (2014). Optimal risk and liquidity management with costly refinancing opportunities. Insurance: Mathematics and Economics, 57:31-45.

Abstract

In this paper we study risk and liquidity management decisions within an insurance firm. Risk management corresponds to decisions regarding proportional reinsurance, whereas liquidity management has two components: distribution of dividends and costly equity issuance. Contingent on whether proportional or fixed costs of reinvestment are considered, singular stochastic control or stochastic impulse control techniques are used to seek strategies that maximize the firm value. We find that, in a proportional-costs setting, the optimal strategies are always mixed in terms of risk management and refinancing. In contrast, when fixed issuance costs are too high relative to the firm’s profitability, optimal management does not involve refinancing. We provide analytical specifications of the optimal strategies, as well as a qualitative analysis of the interaction between refinancing and risk management.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Finance
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Social Sciences & Humanities > Economics and Econometrics
Social Sciences & Humanities > Statistics, Probability and Uncertainty
Scope:Discipline-based scholarship (basic research)
Language:English
Date:2014
Deposited On:20 Feb 2015 09:38
Last Modified:12 Mar 2025 02:40
Publisher:Elsevier
ISSN:0167-6687
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.insmatheco.2014.05.001
Official URL:http://www.sciencedirect.com/science/article/pii/S0167668714000547
Other Identification Number:merlin-id:10283
Project Information:
  • Funder: FP7
  • Grant ID: 247277
  • Project Title: STAHDPDE - Sparse Tensor Approximations of High-Dimensional and stochastic Partial Differential Equations
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