Black’s model in a negative interest rate environment, with application to OTC derivatives
Riccardo Bramante (),
Gimmi Dallago and
Silvia Facchinetti
Additional contact information
Riccardo Bramante: Università Cattolica del Sacro Cuore
Gimmi Dallago: Allitude S.p.A.
Silvia Facchinetti: Università Cattolica del Sacro Cuore
Computational Management Science, 2022, vol. 19, issue 1, No 2, 25-39
Abstract:
Abstract The most common application of Black’s formula is interest rate derivatives pricing. Black’s model, a variant of Black-Scholes option pricing model, was first introduced by Fischer Black in 1976. In recent market conditions, where global interest rates are at very low levels and in some markets are currently zero or negative, Black model—in its canonical form—fails to price interest rate options since positive interest rates are assumed in its formula. In this paper we propose a heuristic method that, without explicit assumptions about the forward rate generating process, extends the cumulative standard normal distribution domain to negative interest rates and allows Black’s model to work in the conventional way. Furthermore, we provide the derivations of the so called five Greek letters that enable finance professionals to evaluate the sensitivity of an option to various parameters. Along with the description of the methodology, we present an extensive simulation study and a comparison with the Normal model which is widely used in the negative environment option pricing problems.
Keywords: Black’s model; Normal distribution; Negative rates; Greek letters (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10287-021-00408-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:comgts:v:19:y:2022:i:1:d:10.1007_s10287-021-00408-6
Ordering information: This journal article can be ordered from
http://www.springer. ... ch/journal/10287/PS2
DOI: 10.1007/s10287-021-00408-6
Access Statistics for this article
Computational Management Science is currently edited by Ruediger Schultz
More articles in Computational Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().