Long-Run Wavelet-Based Correlation for Financial Time Series

European Journal of Operational Research - Forthcoming

Michael J. Brennan Irish Finance Working Paper Series Research Paper No. 18-7

41 Pages Posted: 14 Jun 2018 Last revised: 19 Sep 2018

See all articles by Thomas Conlon

Thomas Conlon

University College Dublin

John Cotter

University College Dublin; University of California, Los Angeles (UCLA) - Anderson School of Management

Ramazan Gencay

Simon Fraser University

Date Written: May 29, 2018

Abstract

The asset allocation decision often relies upon correlation estimates arising from short-run data. Short-run correlation estimates may, however, be distorted by frictions. In this paper, we introduce a long-run wavelet-based correlation estimator, distinguishing between long-run common behavior and short-run singular events. Using generated data, we demonstrate a reduction in bias and error of up to 84.2% and $38.9% respectively, relative to a traditional subsampled approach. Exploiting the wavelet decomposition into short- and long-run components, we develop a model to help understand the sources of any heterogeneity in correlation. The implication is that short-run correlation may be downward biased by frictions, the latter manifesting as serial- and cross-serial correlation in the raw time series. In an empirical application to G7 international equity markets, we present evidence of increasing correlations at longer-run horizons. The significance for the asset allocation decision are examined using a minimum-variance framework, highlighting distinct optimal allocation weights at short- and long-run horizons.

Keywords: Decision Analysis; Long-Run; Correlation; Wavelet; Portfolio Analysis

JEL Classification: G00, G11, G15, C10, C14, C44, C58

Suggested Citation

Conlon, Thomas and Cotter, John and Gencay, Ramazan, Long-Run Wavelet-Based Correlation for Financial Time Series (May 29, 2018). European Journal of Operational Research - Forthcoming , Michael J. Brennan Irish Finance Working Paper Series Research Paper No. 18-7, Available at SSRN: https://ssrn.com/abstract=3186703 or http://dx.doi.org/10.2139/ssrn.3186703

Thomas Conlon (Contact Author)

University College Dublin ( email )

Smurfit Graduate Business School
Blackrock
Co. Dublin, n/a
Ireland

HOME PAGE: http://www.ucd.ie/bankingfinance/staff/drthomasconlon/

John Cotter

University College Dublin ( email )

School of Business, Carysfort Avenue
Blackrock, Co. Dublin
Ireland
353 1 716 8900 (Phone)
353 1 283 5482 (Fax)

HOME PAGE: http://https://johncotter.org/

University of California, Los Angeles (UCLA) - Anderson School of Management ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

Ramazan Gencay

Simon Fraser University ( email )

Department of Economics
8888 University Drive
Burnaby, British Columbia V5A 1S6
Canada

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