Copula Based Monte Carlo Integration in Financial Problems

Alessio Sancetta

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: A computational technique that transform integrals over RK, or some of its subsets, into the hypercube [0, 1]K can be exploited in order to solve integrals via Monte Carlo integration without the need to simulate from the original distribution; all that is needed is to simulate iid uniform [0, 1] pseudo random variables. In particular the technique arises from the copula representation of multivariate distributions and the use of the marginal quantile function of the data. The procedure is further simplified if the quantile function has closed form. Several financial applications are considered in order to highlight the scope of this numerical technique for financial problems

Keywords: Copula; Martingale; Monte Carlo Integral; Quantile Transform; Utility Function. (search for similar items in EconPapers)
JEL-codes: C15 G11 G12 (search for similar items in EconPapers)
Pages: 34
Date: 2005-01
New Economics Papers: this item is included in nep-cmp, nep-ecm and nep-fin
Note: EM
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://files.econ.cam.ac.uk/repec/cam/pdf/cwpe0506.pdf (application/pdf)

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:cam:camdae:0506

Access Statistics for this paper

More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
Bibliographic data for series maintained by Jake Dyer ().