TY - JOUR
T1 - Testing for parameter instability and structural change in persistent predictive regressions
AU - Andersen, Torben G.
AU - Varneskov, Rasmus T.
N1 - Funding Information:
We wish to thank the Guest Editor Atsushi Inoue and two anonymous referees for helpful comments and suggestions. This manuscript subsumes a previous working paper entitled “On the Informational Efficiency of Option-Implied and Time Series Forecasts of Realized Volatility”. Financial support from CREATES, Center for Research in Econometric Analysis of Time Series ( DNRF78 ), funded by the Danish National Research Foundation, is gratefully acknowledged.
Funding Information:
We wish to thank the Guest Editor Atsushi Inoue and two anonymous referees for helpful comments and suggestions. This manuscript subsumes a previous working paper entitled ?On the Informational Efficiency of Option-Implied and Time Series Forecasts of Realized Volatility?. Financial support from CREATES, Center for Research in Econometric Analysis of Time Series (DNRF78), funded by the Danish National Research Foundation, is gratefully acknowledged.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - Cointegration
KW - Fractional integration
KW - Frequency domain inference
KW - Local spectrum procedure
KW - Parameter instability
KW - Structural change
KW - Volatility forecasting
UR - http://www.scopus.com/inward/record.url?scp=85118852680&partnerID=8YFLogxK
U2 - 10.1016/j.jeconom.2021.05.011
DO - 10.1016/j.jeconom.2021.05.011
M3 - Journal article
AN - SCOPUS:85118852680
SN - 0304-4076
VL - 231
SP - 361
EP - 386
JO - Journal of Econometrics
JF - Journal of Econometrics
IS - 2
ER -