A Valid and Efficient Trinomial Tree for General Local-Volatility Models
U Hou Lok () and
Yuh-Dauh Lyuu ()
Additional contact information
U Hou Lok: National Taipei University of Business
Yuh-Dauh Lyuu: National Taiwan University
Computational Economics, 2022, vol. 60, issue 3, No 1, 817-832
Abstract:
Abstract The local-volatility model assumes the instantaneous volatility is a deterministic function of the underlying asset price and time. The model is very popular because it attempts to fit the volatility smile while retaining the preference freedom of the Black–Scholes option pricing model. As local-volatility model does not admit of analytical formulas in general, numerical methods are required. Tree is one such method because of its simplicity and efficiency. However, few trees in the literature guarantee valid transition probabilities and underlying asset prices simultaneously. This paper presents an efficient tree, called the extended waterline tree, that is provably valid for practically all local-volatility models. Numerical results confirm the tree’s excellent performance.
Keywords: Local-volatility model; Trinomial tree; Extended waterline tree; Volatility surface (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/s10614-021-10166-x 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:60:y:2022:i:3:d:10.1007_s10614-021-10166-x
Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2
DOI: 10.1007/s10614-021-10166-x
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 ().