Template-Type: ReDIF-Paper 1.0
Author-Name: Pietersz, R.
Author-Name-Last: Pietersz
Author-Name-First: Raoul
Author-Person: ppi79
Author-Name: Groenen, P.J.F.
Author-Name-Last: Groenen
Author-Name-First: Patrick
Author-Person: pgr229
Title: Rank reduction of correlation matrices by majorization
Abstract: In this paper a novel method is developed for the problem of finding a low-rank correlation matrix nearest to a given correlation matrix. The method is based on majorization and therefore it is globally convergent. The method is computationally efficient, is straightforward to implement, and can handle arbitrary weights on the entries of the correlation matrix. A simulation study suggests that majorization compares favourably with competing approaches in terms of the quality of the solution within a fixed computational time. The problem of rank reduction of correlation matrices occurs when pricing a derivative dependent on a large number of assets, where the asset prices are modelled as correlated log-normal processes.
Creation-Date: 2004-04-01
File-URL: https://repub.eur.nl/pub/1202/ei200411.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2004-11
Classification-JEL: G13
Keywords: correlation matrix, lognormal price processes, majorization, rank
Handle: RePEc:ems:eureir:1202