Analytical Pricing of An Insurance Embedded Option: Alternative Formulas and Gaussian Approximation
DOI:
https://doi.org/10.26713/jims.v3i2.44Keywords:
Double-trigger option, State-price deflator, Black-Scholes return, Vasicek return, Lin normal tail probability approximationAbstract
Analytical pricing of a double-trigger option with the Black-Scholes-Vasicek (BSV) state price deflator is considered. In the context of market-consistent valuation of insurance liabilities, the option appears as embedded option of index-linked endowment policies that provide combined protection against inflation and a minimum interest rate guarantee by death. A first analytical pricing formula in terms of the standard bivariate normal distribution is derived. Then, using alternatively the canonical BSV deflator, a second integral representation is derived. Based on an elementary Gaussian integral in three variables a third integral decomposition is obtained and approximated by closed-form Gaussian expressions using a simple approximation by Lin of the normal tail probability integral. Similarly to the invariance of the Black-Scholes and Margrabe formulas with respect to the market prices of the risk factors, two of the alternative double-trigger option pricing formulas and the proposed Gaussian approximation also share this property. A numerical example rounds up the analysis by showing accuracy of the Gaussian approximation within some few negligible basis points.
Downloads
Downloads
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a CCAL that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.