Powerful Tests for Structural Changes in Volatility
40 Pages Posted: 27 Nov 2012
Date Written: August 14, 2012
Abstract
Detecting structural changes in volatility is important for understanding volatility dynamics and stylized facts observed for financial returns such as volatility persistence. We propose modified CUSUM and LM tests that are built on a robust estimator of the long run variance of squared series. We establish conditions under which the new tests have standard null distributions and diverge faster than standard tests under the alternative. The theory allows smooth and abrupt structural changes that can be small. The smoothing parameter is automatically selected such that the proposed test has good finite-sample size and meanwhile achieves decent power gain.
Keywords: CUSUM test, LM test, nonparametric volatility estimation, nonstationary volatility, volatility break
JEL Classification: C12, C22
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
The Spline-Garch Model for Low Frequency Volatility and its Global Macroeconomic Causes
-
The Spline-Garch Model for Low Frequency Volatility and its Global Macroeconomic Causes
-
The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes
By Robert F. Engle and J. Gonzalo Rangel
-
On the Economic Sources of Stock Market Volatility
By Robert F. Engle, Eric Ghysels, ...
-
On the Economic Sources of Stock Market Volatility
By Robert F. Engle, Eric Ghysels, ...
-
A Component Model for Dynamic Correlations
By Ric Colacito, Robert F. Engle, ...
-
Macroeconomic Volatility and Stock Market Volatility, Worldwide
By Francis X. Diebold and Kamil Yilmaz
-
Macroeconomic Volatility and Stock Market Volatility, World-Wide
By Francis X. Diebold and Kamil Yilmaz
-
Why Invest in Emerging Markets? The Role of Conditional Return Asymmetry
By Eric Ghysels, Alberto Plazzi, ...