Valuing rebate options and equity-linked products
Hangsuck Lee,
Himchan Jeong and
Gaeun Lee
The North American Journal of Economics and Finance, 2023, vol. 68, issue C
Abstract:
In this article, we propose rebate options with multi-step barriers, which are an extension of rebate options with a constant barrier. Despite the applicability and marketability of rebate options, there have been only a few research on obtaining analytical formulas. Accordingly, in this paper, we derive closed-form pricing formulas for these options under the Black–Scholes framework. The rebate options with multi-step barriers allow a flexible barrier structure, and thus we propose complex equity-linked products embedded with rebate options with barriers and derive pricing formulas for them. We conduct numerical studies on the pricing of rebate options with multi-step barriers, equity-linked securities, and equity-indexed annuities. The numerical studies validate the prices obtained from the pricing formulas.
Keywords: Rebate options; Reflection principle; Multi-step reflection principle; Equity-indexed annuities; Equity-linked securities (search for similar items in EconPapers)
JEL-codes: G13 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1062940823000918
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:68:y:2023:i:c:s1062940823000918
DOI: 10.1016/j.najef.2023.101968
Access Statistics for this article
The North American Journal of Economics and Finance is currently edited by Hamid Beladi
More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().