Asymptotic Analysis of Mixing Distributions

Archil Gulisashvili
Additional contact information
Archil Gulisashvili: Ohio University

Chapter Chapter 5 in Analytically Tractable Stochastic Stock Price Models, 2012, pp 109-166 from Springer

Abstract: Abstract Chapter 5 presents joint results of E.M. Stein and the author concerning the asymptotic behavior of mixing distribution densities associated with geometric Brownian motions, Ornstein-Uhlenbeck processes, and CIR-processes. Sharp asymptotic formulas with relative error estimates are established for these densities, using various combinations of techniques and tools. The proofs employ a Tauberian theorem for the two-sided Laplace transform, the theory of hypergeometric functions, and some methods from complex analysis. Dufresne’s recurrence formula, which allows one to navigate between the Hull-White models with different values of the model parameters, is also covered in Chap. 5.

Keywords: Analytic Continuation; Asymptotic Formula; Hypergeometric Function; Large Deviation Principle; Geometric Brownian Motion (search for similar items in EconPapers)
Date: 2012
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:sprfcp:978-3-642-31214-4_5

Ordering information: This item can be ordered from
http://www.springer.com/9783642312144

DOI: 10.1007/978-3-642-31214-4_5

Access Statistics for this chapter

More chapters in Springer Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().