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True and apparent scaling: the proximity of the markov- switching multifractal model to long-range dependence

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Liu, Ruipeng, Di Matteo, T. and Lux, Thomas (2007) True and apparent scaling: the proximity of the markov- switching multifractal model to long-range dependence. Working Paper. Coventry: Warwick Business School, Financial Econometrics Research Centre. Working papers (Warwick Business School. Financial Econometrics Research Centre) (No.07-).

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Official URL: http://www2.warwick.ac.uk/fac/soc/wbs/research/wfr...

Abstract

In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov-switching multifractal model (MSM). In order to see how well the estimated models capture the temporal dependence of the data, we estimate and compare the scaling exponents H(q) (for q = 1, 2) for both empirical data and simulated data of the estimated MSM models. In most cases the multifractal model appears to generate ‘apparent’ long memory in agreement with the empirical scaling laws.

Item Type:

Working or Discussion Paper (Working Paper)

Subjects:

H Social Sciences > HG Finance
Q Science > QA Mathematics

Divisions:

Faculty of Social Sciences > Warwick Business School > Financial Econometrics Research Centre
Faculty of Social Sciences > Warwick Business School

Library of Congress Subject Headings (LCSH):

Scaling (Social sciences), Stock exchanges -- Mathematical models, Multifractals, Markov processes, Estimation theory

Series Name:

Working papers (Warwick Business School. Financial Econometrics Research Centre)

Publisher:

Warwick Business School, Financial Econometrics Research Centre

Place of Publication:

Coventry

Official Date:

2007

Dates:

Date	Event
2007	Published

Number:

No.07-

Number of Pages:

Institution:

University of Warwick

Status:

Not Peer Reviewed

Access rights to Published version:

Open Access

Funder:

Sixth Framework Programme (European Commission) (FP6), Australian Research Council (ARC)

Grant number:

516446 (SFP), DP03440044 (ARC), DP0558183 (ARC)

References:

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