Berry–Esseen inequalities for the fractional Black–Karasinski model of term structure of interest rates

Bishwal Jaya P. N. ()
Additional contact information
Bishwal Jaya P. N.: Department of Mathematics and Statistics, University of North Carolina at Charlotte, 376 Fretwell Building, 9201 University City Blvd., Charlotte, NC 28223, USA

Monte Carlo Methods and Applications, 2022, vol. 28, issue 2, 111-124

Abstract: The Black–Karasinski model is a one-factor non-affine interest rate model as it describes interest rate movements driven by a single source of randomness and the drift function is a nonlinear function of the interest rate. The drift parameters represent the level and the speed of mean reversion of the interest rate. It belongs to the class of no-arbitrage models. The paper introduces some new approximate minimum contrast estimators of the mean reversion speed parameter in the model based on discretely sampled data which are efficient and studies their asymptotic distributional properties with precise rates of convergence.

Keywords: Itô stochastic differential equation; Black–Karasinski model; discrete observations; approximate minimum contrast estimators; interest rate; non-affine models; robustness; efficiency; Monte Carlo method; Kolmogorov distance; Berry–Esseen bound (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/mcma-2022-2111 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:mcmeap:v:28:y:2022:i:2:p:111-124:n:8

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/mcma/html

DOI: 10.1515/mcma-2022-2111

Access Statistics for this article

Monte Carlo Methods and Applications is currently edited by Karl K. Sabelfeld

More articles in Monte Carlo Methods and Applications from De Gruyter
Bibliographic data for series maintained by Peter Golla ().