Black Scholes Option Sensitivity Using High Order Greeks
Yves Rakotondratsimba ()
Additional contact information
Yves Rakotondratsimba: ECE Paris Graduate School of Engineering
A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2014, pp 187-190 from Springer
Abstract:
Abstract Option high order sensitivities have been presented by Carr P. as Greeks for geeks, though other authors have analyzed and insisted on the need to go beyond to the Delta-Gamma approximation usually considered in the practice of risk management. Actually in the stress-testing framework, as is required under Basel 3 bank regulation, adding high order Greeks may contribute to a good prediction of the option PL under extreme shocks. We revisit the Black-Scholes high order Greek parameters by providing their explicit formulas and proofs, which are expected to be more accessible for many readers. Limit of the use of these sensitivities are also analyzed here. Actually our main contribution in this work is on the introduction of an unified sensitivity approach with the ones used for other classes of assets as interest rates and commodities. This may be useful in the Credit Adjustment Valuation computation and hedging, where all aspects of risk (equity, interest rate, credit, commodities, …) need to be simultaneously considered.
Keywords: Black-Scholes; Option; Sensitivities; P&L (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:spr:sprchp:978-3-319-05014-0_42
Ordering information: This item can be ordered from
http://www.springer.com/9783319050140
DOI: 10.1007/978-3-319-05014-0_42
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().