1
|
Benkraiem R, El-Khatib Y, Fan J, Goutte S, Klein T. Optimal risk management considering environmental and climatic changes. Risk Anal 2024. [PMID: 38622068 DOI: 10.1111/risa.14306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
Climate change presents challenges to policy and economic stability, necessitating effective trading strategies to reduce environmental risks. This article addresses gaps in existing studies by using a Markov-switching model to consider climate risk. Backward stochastic differential equations are used to optimize utility with three hedging strategies based on the concept of risk aversion. Numerical scenarios confirm the model's superiority in incorporating exogenous events, with our risk-averse strategy outperforming classical approaches. Our strategy outperforms classical strategies by taking a flexible risk trading when investors face risk-averse behavior due to climate risk events. The findings presented in this article have important implications for the development of more resilient investment portfolios and can contribute to climate policy.
Collapse
Affiliation(s)
| | - Youssef El-Khatib
- Department of Mathematical Sciences, United Arab Emirates University, Al-Ain, Abu Dhabi, UAE
| | - Jun Fan
- University of Nottingham Ningbo China, Ningbo, China
| | - Stéphane Goutte
- Université Paris-Saclay, UMI SOURCE, IRD, UVSQ, Guyancourt, France
- Paris School of Business, Paris, France
| | - Tony Klein
- Faculty of Business and Economics, Technische Universität Chemnitz, Chemnitz, Germany
| |
Collapse
|
2
|
Ali MM, Fathelrahman E, El Awad AI, Eltahir YM, Osman R, El-Khatib Y, AlRifai RH, El Sadig M, Khalafalla AI, Reeves A. Epidemiology and Scenario Simulations of the Middle East Respiratory Syndrome Corona Virus (MERS-CoV) Disease Spread and Control for Dromedary Camels in United Arab Emirates (UAE). Animals (Basel) 2024; 14:362. [PMID: 38338005 PMCID: PMC10854904 DOI: 10.3390/ani14030362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 01/13/2024] [Accepted: 01/17/2024] [Indexed: 02/12/2024] Open
Abstract
Middle East Respiratory Syndrome (MERS-CoV) is a coronavirus-caused viral respiratory infection initially detected in Saudi Arabia in 2012. In UAE, high seroprevalence (97.1) of MERS-CoV in camels was reported in several Emirate of Abu Dhabi studies, including camels in zoos, public escorts, and slaughterhouses. The objectives of this research include simulation of MERS-CoV spread using a customized animal disease spread model (i.e., customized stochastic model for the UAE; analyzing the MERS-CoV spread and prevalence based on camels age groups and identifying the optimum control MERS-CoV strategy. This study found that controlling animal mobility is the best management technique for minimizing epidemic length and the number of affected farms. This study also found that disease dissemination differs amongst camels of three ages: camel kids under the age of one, young camels aged one to four, and adult camels aged four and up; because of their immunological state, kids, as well as adults, had greater infection rates. To save immunization costs, it is advised that certain age groups be targeted and that intense ad hoc unexpected vaccinations be avoided. According to the study, choosing the best technique must consider both efficacy and cost.
Collapse
Affiliation(s)
- Magdi Mohamed Ali
- UAE Ministry of Climate Change and Environment, Dubai 1509, United Arab Emirates;
| | - Eihab Fathelrahman
- Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University (UAEU), Al Ain 1551, United Arab Emirates; (A.I.E.A.); (R.O.)
| | - Adil I. El Awad
- Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University (UAEU), Al Ain 1551, United Arab Emirates; (A.I.E.A.); (R.O.)
| | - Yassir M. Eltahir
- Abu Dhabi Agricultural and Food Safety Authority ADAFSA, Abu Dhabi 52150, United Arab Emirates; (Y.M.E.); (A.I.K.)
| | - Raeda Osman
- Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University (UAEU), Al Ain 1551, United Arab Emirates; (A.I.E.A.); (R.O.)
| | - Youssef El-Khatib
- Department of Mathematical Sciences, College of Science, United Arab Emirates University (UAEU), Al Ain 1551, United Arab Emirates;
| | - Rami H. AlRifai
- Institute of Public Health, College of Medicine, and Health Sciences (UAEU), Al Ain 1551, United Arab Emirates; (R.H.A.); (M.E.S.)
| | - Mohamed El Sadig
- Institute of Public Health, College of Medicine, and Health Sciences (UAEU), Al Ain 1551, United Arab Emirates; (R.H.A.); (M.E.S.)
| | | | - Aaron Reeves
- Center for Public Health Surveillance and Technology, RTI International, Research Triangle Park, Raleigh, NC 27709, USA;
| |
Collapse
|
3
|
Breton JC, El-Khatib Y, Fan J, Privault N. A q-binomial extension of the CRR asset pricing model. STOCH MODELS 2023. [DOI: 10.1080/15326349.2023.2173231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Affiliation(s)
| | | | - Jun Fan
- University of Nottingham Ningbo, China
| | | |
Collapse
|
4
|
Khan T, Ullah R, Alwan BA, El-Khatib Y, Zaman G. Correlated stochastic epidemic model for the dynamics of SARS-CoV-2 with vaccination. Sci Rep 2022; 12:16105. [PMID: 36168022 PMCID: PMC9514201 DOI: 10.1038/s41598-022-20059-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 09/08/2022] [Indexed: 11/09/2022] Open
Abstract
In this paper, we propose a mathematical model to describe the influence of the SARS-CoV-2 virus with correlated sources of randomness and with vaccination. The total human population is divided into three groups susceptible, infected, and recovered. Each population group of the model is assumed to be subject to various types of randomness. We develop the correlated stochastic model by considering correlated Brownian motions for the population groups. As the environmental reservoir plays a weighty role in the transmission of the SARS-CoV-2 virus, our model encompasses a fourth stochastic differential equation representing the reservoir. Moreover, the vaccination of susceptible is also considered. Once the correlated stochastic model, the existence and uniqueness of a positive solution are discussed to show the problem’s feasibility. The SARS-CoV-2 extinction, as well as persistency, are also examined, and sufficient conditions resulted from our investigation. The theoretical results are supported through numerical/graphical findings.
Collapse
Affiliation(s)
- Tahir Khan
- Department of Computing, Muscat College, Muscat, Oman
| | - Roman Ullah
- Department of Computing, Muscat College, Muscat, Oman
| | - Basem Al Alwan
- Chemical Engineering Department, College of Engineering, King Khalid University, 61411, Abha, Saudi Arabia
| | - Youssef El-Khatib
- Department of Mathematical Sciences, UAE University, P.O. Box 15551, Al-Ain, United Arab Emirates.
| | - Gul Zaman
- Department of Mathematics, University of Malakand, Chakdara, Dir (Lower), Khyber Pakhtunkhawa, Pakistan
| |
Collapse
|
5
|
Jain S, El-Khatib Y. Stochastic covid-19 model with fractional global and classical piecewise derivative. Results Phys 2021; 30:104788. [PMID: 34567956 PMCID: PMC8453135 DOI: 10.1016/j.rinp.2021.104788] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/01/2021] [Accepted: 09/03/2021] [Indexed: 06/13/2023]
Abstract
Several methodologies have been advocated in the last decades with the aim to better understand behaviours displayed by some real-world problems. Among which, stochastics modelling and fractional modelling, fuzzy and others. These methodologies have been suggested to threat specific problems; however, It have been noticed that some problems exhibit different patterns as time passes by. Randomness and nonlocality can be combined to depict complex real-world behaviours. It has been observed that, covid-19 virus spread does not follow a single pattern; sometimes we obtained stochastic behaviours, another nonlocal behaviour and others. In this paper, we shall consider a covid-19 model with fractional stochastic behaviours. More precisely a covid-19 model, where the model considers nonlocalities and randomness is suggested. Then a comprehensive analysis of the model is conducted. Numerical simulations and illustrations are done to show the efficiency of the model.
Collapse
Affiliation(s)
- Sonal Jain
- Department of Mathematical Sciences, UAE University, P.O. Box 15551, Al-Ain, United Arab Emirates
| | - Youssef El-Khatib
- Department of Mathematical Sciences, UAE University, P.O. Box 15551, Al-Ain, United Arab Emirates
| |
Collapse
|
6
|
Khan T, Zaman G, El-Khatib Y. Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model. Results Phys 2021; 24:104004. [PMID: 33816091 PMCID: PMC7999738 DOI: 10.1016/j.rinp.2021.104004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 02/07/2021] [Accepted: 02/22/2021] [Indexed: 05/04/2023]
Abstract
In this article we propose a stochastic model to discuss the dynamics of novel corona virus disease. We formulate the model to study the long run behavior in varying population environment. For this purposes we divided the total human population into three epidemiological compartments: the susceptible, covid-19 infected, recovered and recovered along with one class of reservoir. The existence and uniqueness of the newly formulated model will be studied to show the well-possedness of the model. Moreover, we investigate the extinction analysis as well as the persistence analysis to find the disease extinction and disease persistence conditions. At the end we perform simulation to justify the investigation of analytical work with the help of graphical representations.
Collapse
Affiliation(s)
- Tahir Khan
- Department of Mathematics, University of Malakand, Chakdara, Dir (Lower), Khyber Pakhtunkhawa, Pakistan
| | - Gul Zaman
- Department of Mathematics, University of Malakand, Chakdara, Dir (Lower), Khyber Pakhtunkhawa, Pakistan
| | - Youssef El-Khatib
- Department of Mathematical Sciences, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates
| |
Collapse
|