Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions

43 Pages Posted: 25 Jun 2020 Last revised: 15 Mar 2021

See all articles by Torben G. Andersen

Torben G. Andersen

Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER); Aarhus University - CREATES

Rasmus Tangsgaard Varneskov

Copenhagen Business School - Department of Finance; Nordea Bank AB - Nordea Asset Management

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Date Written: May 30, 2020

Abstract

This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all -- or a subset -- of the variables may be fractionally integrated and the predictive relation may feature cointegration, we provide sup-Wald break tests that are constructed using the Local speCtruM (LCM) approach. The new tests cover both parameter variation and multiple structural changes with unknown break dates, and the number of breaks being known or unknown. We establish asymptotic limit theory for the tests, showing that it coincides with standard testing procedures. As a consequence, existing critical values for tied-down Bessel processes may be applied, without modification. We implement the new structural change tests to explore the stability of the fractionally cointegrating relation between implied- and realized volatility (IV and RV). Moreover, we assess the relative efficiency of IV forecasts against a challenging time-series benchmark constructed from high-frequency data. Unlike existing studies, we find evidence that the IV-RV cointegrating relation is unstable, and that carefully constructed time-series forecasts are more efficient than IV in capturing low-frequency movements in RV.

Keywords: Cointegration, Fractional Integration, Frequency Domain Inference, Local Spectrum Procedure, Parameter Instability, Structural Change, Volatility Forecasting

JEL Classification: C12, C13, C14, C32, G17

Suggested Citation

Andersen, Torben G. and Varneskov, Rasmus Tangsgaard, Testing for Parameter Instability and Structural Change in Persistent Predictive Regressions (May 30, 2020). Available at SSRN: https://ssrn.com/abstract=3626692 or http://dx.doi.org/10.2139/ssrn.3626692

Torben G. Andersen

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Aarhus University - CREATES ( email )

School of Economics and Management
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DK-8000 Aarhus C
Denmark

Rasmus Tangsgaard Varneskov (Contact Author)

Copenhagen Business School - Department of Finance ( email )

A4.17 Solbjerg Plads 3
Copenhagen, Frederiksberg 2000
Denmark

Nordea Bank AB - Nordea Asset Management ( email )

PO Box 850
Copenhagen, 0900
Denmark

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