Research Articles >
College of Science >
Please use this identifier to cite or link to this item:
|Title: ||Valuation of surrender options based of an insured with multi-morbidity|
|Authors: ||Mac-Issaka, B.|
Okyere, G. A.
Kpamma, H. M.
Achamfour, J. B.
|Issue Date: ||8-Oct-2018|
|Publisher: ||Journal of Advances in Mathematics and Computer Science|
|Abstract: ||Embedded in Life insurance contracts are surrender options and also path dependency. Surrender
option stems from many reasons. Multi-morbidity increases the rate of mortality and a variety
of adverse health outcomes which may lead to surrendering. Poverty levels coupled with social
burdens can inform a multi-morbid person to surrender a life policy contract. The study seeks
determine and compare valuation of options of a multi-morbid person surrendering. In line with
this objective the multi-morbid survival rate of a policy holder was incorporated in the Black-
Scholes model for option pricing. The solution to the model come with its own complexities,
therefore the need to resort to numerical solutions for the option valuation. Further, a comparison
is made of two finite difference algorithm in solving the proposed Black-Scholes equation; the
Crank-Nicolson method and the Hopscotch method. Simulations of survival were performed to compute the survival rate. Numerical solution to the Black-Scholes model and the proposed
model indicates that the Crank-Nicolson method converges faster than the Hopscotch method for
the Black-Scholes whiles the Hopscotch method converges faster than the Crank-Nicolson for the
proposed modified Black-Scholes model. It was observed that the Hopscotch method converges
faster as the multi-morbid survival rate decreases below the short rate of the Black-Scholes model.|
|Description: ||An article published by Journal of Advances in Mathematics and Computer Science and also available at DOI: 10.9734/JAMCS/2018/43700|
|Appears in Collections:||College of Science|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.