Static Hedges of Barrier Options Under Fast Mean-Reverting Stochastic Volatility

Jeonggyu Huh, Jaegi Jeon and Yong-Ki Ma ()
Additional contact information
Jeonggyu Huh: Yonsei University
Jaegi Jeon: Yonsei University
Yong-Ki Ma: Kongju National University

Computational Economics, 2020, vol. 55, issue 1, No 7, 185-210

Abstract: Abstract In this paper, we suggest a numerically stable method for static hedging of barrier options under fast mean-reverting stochastic volatility with transaction costs. We elucidate how perturbation theory converts static hedging on time–volatility grid into the problem of designing two simpler static hedges on time grid, and see why this precludes any ill-conditioned problem from springing up. Our static hedging approach is an effective means to statically replicate the barrier option, and can therefore solve the problem of transaction costs by obtaining stable weights of the portfolio. Simulation results show that our method could obtain better hedging performance compared to preceding static hedge methods.

Keywords: Stochastic volatility model; Static hedge; Transaction costs; Barrier option; Perturbation theory (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10614-019-09883-1 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:kap:compec:v:55:y:2020:i:1:d:10.1007_s10614-019-09883-1

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-019-09883-1

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().