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Estimation of the variance function in structural break autoregressive models with nonstationary and explosive segments (2022)
Journal Article

In this paper we consider estimating the innovation variance function when the conditional mean model is characterized by a structural break autoregressive model, which exhibits multiple unit root, explosive and stationary collapse segments, allowing... Read More about Estimation of the variance function in structural break autoregressive models with nonstationary and explosive segments.

CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility (2021)
Journal Article

We generalise the Homm and Breitung (2012) CUSUM-based procedure for the real-time detection of explosive autoregressive episodes in financial price data to allow for time-varying volatility. Such behaviour can heavily inflate the false positive rate... Read More about CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility.

Sign-based Unit Root Tests for Explosive Financial Bubbles in the Presence of Deterministically Time-Varying Volatility (2019)
Journal Article

This paper considers the problem of testing for an explosive bubble in …nancial data in the presence of time-varying volatility. We propose a sign-based variant of the Phillips, Shi and Yu (2015) test. Unlike the original test, the sign-based test do... Read More about Sign-based Unit Root Tests for Explosive Financial Bubbles in the Presence of Deterministically Time-Varying Volatility.

Testing the order of fractional integration of a time series in the possible presence of a trend break at an unknown point (2018)
Journal Article

We develop a test, based on the Lagrange multiplier [LM] testing principle, for the value of the long memory parameter of a univariate time series that is composed of a fractionally integrated shock around a potentially broken deterministic trend. Ou... Read More about Testing the order of fractional integration of a time series in the possible presence of a trend break at an unknown point.