Simulating cointegrated time series

Author

Galenko, Alexander ; Popova, E. ; Morton, David ; Popova, Ivilina

Author_Institution

PENSON Financial Services, Austin, TX, USA

fYear

2009

fDate

13-16 Dec. 2009

Firstpage

483

Lastpage

493

Abstract

When one models dependence solely via correlations, portfolio allocation models can perform poorly. This motivates considering dependence measures other than correlation. Cointegration is one such measure that captures long-term dependence. In this paper we present a new method to simulate cointegrated sample paths using the vector auto-regressive-to-anything (VARTA) algorithm. Our approach relies on new properties of cointegrated time series of financial asset prices and allows for marginal distributions from the Johnson system. The method is illustrated on two data sets, one real and one artificial.

Keywords

autoregressive processes; investment; pricing; statistical distributions; time series; Johnson system; VARTA algorithm; cointegrated sample paths; cointegrated time series; dependence measures; financial asset price; long-term dependence; marginal distribution; portfolio allocation models; vector auto-regressive-to-anything; Asset management; Finance; Financial management; Frequency estimation; Industrial engineering; Operations research; Portfolios; Security; Stochastic processes; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference (WSC), Proceedings of the 2009 Winter

Conference_Location

Austin, TX

Print_ISBN

978-1-4244-5770-0

Type

conf

DOI

10.1109/WSC.2009.5429356

Filename

5429356