Multiscale SUR Estimation of Systematic Risk-Reference-Cited by-同舟云学术

Multiscale SUR Estimation of Systematic Risk

Published:2024-05-08 Issue: Volume: Page:
ISSN:1081-1826
Container-title:Studies in Nonlinear Dynamics & Econometrics
language:en
Short-container-title:

Author:

Michis Antonis A.¹²^ORCID

Affiliation:

1. 87194 Central Bank of Cyprus , 8 Kennedy Avenue , Nicosia 1076 , Cyprus

2. Department of Business Administration, School of Business and Law , Frederick University , 7 Gianni Freiderikou Str. , Nicosia 1036 , Cyprus

Abstract

Abstract We propose a multiscale version of the seemingly unrelated regressions model, based on wavelet transform-based time series observations. Each regression equation refers to a different time scale, which enables the use of across-scale error covariances in the feasible GLS estimation procedure for efficiency gains. We demonstrate the advantages of the proposed method over OLS with two studies: an empirical study using stock market returns for the main US industrial sectors and a detailed Monte Carlo simulation study with alternative wavelet filters. We also provide explanations for the suitability of the proposed method for estimating long-term systematic risk.

Publisher

Walter de Gruyter GmbH

Link

https://www.degruyter.com/document/doi/10.1515/snde-2023-0017/pdf

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