Frontiers of Interdisciplinary Research on Financial and Insurance Risk Management

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (1 July 2020) | Viewed by 7604

Special Issue Editors


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Guest Editor
Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada
Interests: distribution theory (e.g., dependence modeling, sums of random variables, factor models, measures of dependence); risk measurement (e.g., risk measures, risk capital allocations); insurance and economic pricing
School of Risk and Actuarial Studies, University of New South Wales, Sydney, NSW, Australia
Interests: actuarial mathematics; financial mathematics; stochastic control; game theory
Department of Statistics, Purdue University, West Lafayette, IN, USA
Interests: actuarial mathematics (e.g., risk measures, risk decomposition techniques, premium principles); probability theory (e.g., multivariate families of distributions, (tail) dependence, copulas); statistical analysis

Special Issue Information

Dear Colleagues,

The stability and sustainability of Financial Services and the major players therein is a necessary condition for the macroeconomic growth of any country. In order to instill security and warrant the aforementioned stability, sets of country-dependent laws, also known as regulations, have been developed. Be it Basel (banking) or Solvency (insurance), the regulations constantly evolve in order to reflect real-world changes. One major innovation in the regulatory regimes, which is an aftermath of the recent financial crisis, is the notion of enterprise risk management (ERM). Remarkably, today, ERM is viewed by the public authorities as a key framework to deal with risks. ERM is quite different from its predecessors, in that it calls for managing various risks simultaneously at the enterprise level and employing a unified multifaceted framework.

Speaking of academia, ERM, which effortlessly crosses the boundaries of a number of distinct scholarly disciplines, invites a holistic and interdisciplinary approach to exploring risk management. It is well known that interdisciplinary research comes with a lot of effort. With this Special Issue, we aim to share instances of successful interdisciplinary research that all focus on the problems of financial and insurance risk management. Both theoretical and empirical research contributions are welcome.

Prof. Edward Furman
Dr. Yang Shen
Dr. Jianxi Su
Guest Editors

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Keywords

  • Risk measures
  • Risk mitigation
  • Risk aggregation
  • Risk allocation
  • Catastrophic risk
  • Cybersecurity risk
  • Contagion risk
  • Systemic risk
  • Operational risk
  • Data science in risk management

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Published Papers (2 papers)

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Research

34 pages, 623 KiB  
Article
Effect of Variance Swap in Hedging Volatility Risk
by Yang Shen
Risks 2020, 8(3), 70; https://doi.org/10.3390/risks8030070 - 1 Jul 2020
Cited by 1 | Viewed by 4113
Abstract
This paper studies the effect of variance swap in hedging volatility risk under the mean-variance criterion. We consider two mean-variance portfolio selection problems under Heston’s stochastic volatility model. In the first problem, the financial market is complete and contains three primitive assets: a [...] Read more.
This paper studies the effect of variance swap in hedging volatility risk under the mean-variance criterion. We consider two mean-variance portfolio selection problems under Heston’s stochastic volatility model. In the first problem, the financial market is complete and contains three primitive assets: a bank account, a stock and a variance swap, where the variance swap can be used to hedge against the volatility risk. In the second problem, only the bank account and the stock can be traded in the market, which is incomplete since the idiosyncratic volatility risk is unhedgeable. Under an exponential integrability assumption, we use a linear-quadratic control approach in conjunction with backward stochastic differential equations to solve the two problems. Efficient portfolio strategies and efficient frontiers are derived in closed-form and represented in terms of the unique solutions to backward stochastic differential equations. Numerical examples are provided to compare the solutions to the two problems. It is found that adding the variance swap in the portfolio can remarkably reduce the portfolio risk. Full article
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12 pages, 394 KiB  
Article
Hedging with Liquidity Risk under CEV Diffusion
by Sang-Hyeon Park and Kiseop Lee
Risks 2020, 8(2), 62; https://doi.org/10.3390/risks8020062 - 5 Jun 2020
Viewed by 2847
Abstract
We study a discrete time hedging and pricing problem in a market with the liquidity risk. We consider a discrete version of the constant elasticity of variance (CEV) model by applying Leland’s discrete time replication scheme. The pricing equation becomes a nonlinear partial [...] Read more.
We study a discrete time hedging and pricing problem in a market with the liquidity risk. We consider a discrete version of the constant elasticity of variance (CEV) model by applying Leland’s discrete time replication scheme. The pricing equation becomes a nonlinear partial differential equation, and we solve it by a multi scale perturbation method. A numerical example is provided. Full article
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