Dynamic Portfolio Selection with Relative Value at Risk Constraint

Author(s):  
Xiuguo Wang
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Hung-Hsi Huang ◽  
Ching-Ping Wang

Abstract Most existing researches on optimal reinsurance contract are based on an insurer’s viewpoint. However, the optimal reinsurance contract for an insurer is not necessarily to be optimal for a reinsurer. Hence, this study aims to develop the optimal reciprocal reinsurance which satisfies the benefits of both the insurer and reinsurer. Additionally, due to legislative restriction or risk management requirement, the wealth of insurer and reinsurer are frequently imposed upon a VaR (Value-at-Risk) or TVaR (Tail Value-at-Risk) constraint. Therefore, this study develops an optimal reciprocal reinsurance contract which maximizes the common benefits (evaluated by weighted addition of expected utilities) of the insurer and reinsurer subject to their VaR or TVaR constraints. Furthermore, for avoiding moral hazard problem, the developed contract is additionally restricted to a regular form or incentive compatibility (both indemnity schedule and retained loss schedule are continuously nondecreasing).


2019 ◽  
Author(s):  
Sheshma Kiran Kumari ◽  
P. Kumar ◽  
J. Priya ◽  
S. Surya ◽  
A. K. Bhurjee

2001 ◽  
Vol 04 (03) ◽  
pp. 535-543
Author(s):  
ANDREAS DE VRIES

A connection between the notion of information and the concept of risk and return in portfolio theory is deduced. This succeeds in two steps: A general moment-return relation for arbitrary assets is derived, thereafter the total expected return is connected to the Kullback-Leibler information. With this result the optimization problem to maximize the expected return of a portfolio consisting of n subportfolios by moment variation under a given value-at-risk constraint is solved. This yields an ansatz to price information.


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