Testing for a unit root against ESTAR stationarity

Harvey, David I.; Leybourne, Stephen J.; Whitehouse, Emily J.

doi:10.1515/snde-2016-0076

Real-time monitoring procedures for early detection of bubbles (2025)
Journal Article
Whitehouse, E., Harvey, D., & Leybourne, S. (2025). Real-time monitoring procedures for early detection of bubbles. International Journal of Forecasting, https://doi.org/10.1016/j.ijforecast.2024.12.005

Asset price bubbles and crashes can have severe consequences for the stability of financial and economic systems. Policymakers require timely identification of such bubbles in order to respond to their emergence. In this paper we propose new economet... Read More about Real-time monitoring procedures for early detection of bubbles.

Testing for Equal Average Forecast Accuracy in Possibly Unstable Environments (2024)
Journal Article
Harvey, D. I., Leybourne, S. J., & Zu, Y. (2024). Testing for Equal Average Forecast Accuracy in Possibly Unstable Environments. Journal of Business and Economic Statistics, https://doi.org/10.1080/07350015.2024.2418835

We consider the issue of testing the null of equal average forecast accuracy in a model where the forecast error loss differential series has a potentially non-constant mean function over time. We show that when time variation is present in the loss... Read More about Testing for Equal Average Forecast Accuracy in Possibly Unstable Environments.

A new heteroskedasticity-robust test for explosive bubbles (2024)
Journal Article
Harvey, D. I., Leybourne, S. J., Taylor, A. M., & Zu, Y. (2024). A new heteroskedasticity-robust test for explosive bubbles. Journal of Time Series Analysis, https://doi.org/10.1111/jtsa.12784

We propose a new class of modified regression-based tests for detecting asset price bubbles designed to be robust to the presence of general forms of both conditional and unconditional heteroskedasticity in the price series. This modification, based... Read More about A new heteroskedasticity-robust test for explosive bubbles.

Tests for equal forecast accuracy under heteroskedasticity (2024)
Journal Article
Harvey, D. I., Harvey, D. I., Leybourne, S. J., Leybourne, S. J., & Zu, Y. (2024). Tests for equal forecast accuracy under heteroskedasticity. Journal of Applied Econometrics, 39(5), 850-869. https://doi.org/10.1002/jae.3050

Heteroskedasticity is a common feature in empirical time series analysis, and in this paper, we consider the effects of heteroskedasticity on statistical tests for equal forecast accuracy. In such a context, we propose two new Diebold–Mariano-type te... Read More about Tests for equal forecast accuracy under heteroskedasticity.

Improved tests for stock return predictability (2023)
Journal Article
Harvey, D. I., Leybourne, S. J., & Taylor, A. M. R. (2023). Improved tests for stock return predictability. Econometric Reviews, 42(9-10), 834-861. https://doi.org/10.1080/07474938.2023.2222634

Predictive regression methods are widely used to examine the predictability of (excess) stock returns by lagged financial variables characterized by unknown degrees of persistence and endogeneity. We develop a new hybrid test for predictability in th... Read More about Improved tests for stock return predictability.

Bonferroni Type Tests for Return Predictability and the Initial Condition (2023)
Journal Article
Astill, S., Harvey, D. I., Leybourne, S. J., & Taylor, A. M. (2024). Bonferroni Type Tests for Return Predictability and the Initial Condition. Journal of Business and Economic Statistics, 42(2), 499-515. https://doi.org/10.1080/07350015.2023.2201313

We develop tests for predictability that are robust to both the magnitude of the initial condition and the degree of persistence of the predictor. While the popular Bonferroni Q test of Campbell and Yogo displays excellent power properties for strong... Read More about Bonferroni Type Tests for Return Predictability and the Initial Condition.

Real-Time Monitoring of Bubbles and Crashes (2023)
Journal Article
Whitehouse, E. J., Harvey, D. I., & Leybourne, S. J. (2023). Real-Time Monitoring of Bubbles and Crashes. Oxford Bulletin of Economics and Statistics, 85(3), 482-513. https://doi.org/10.1111/obes.12540

Given the financial and economic damage that can be caused by the collapse of an asset price bubble, it is of critical importance to rapidly detect the onset of a crash once a bubble has been identified. We develop a real-time monitoring procedure fo... Read More about Real-Time Monitoring of Bubbles and Crashes.

Estimation of the variance function in structural break autoregressive models with nonstationary and explosive segments (2022)
Journal Article
Harvey, D. I., Leybourne, S. J., & Zu, Y. (2023). Estimation of the variance function in structural break autoregressive models with nonstationary and explosive segments. Journal of Time Series Analysis, 44(2), 181-205. https://doi.org/10.1111/jtsa.12660

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.

Testing for Co-explosive Behaviour in Financial Time Series (2022)
Journal Article
Evripidou, A. C., Harvey, D. I., Leybourne, S. J., & Sollis, R. (2022). Testing for Co-explosive Behaviour in Financial Time Series. Oxford Bulletin of Economics and Statistics, 84(3), 624-650. https://doi.org/10.1111/obes.12487

This article proposes a test to determine if two price series that each contain an explosive autoregressive regime consistent with the presence of a bubble are related in the sense that a linear combination of them is integrated of order zero. We ref... Read More about Testing for Co-explosive Behaviour in Financial Time Series.

CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility (2021)
Journal Article
Astill, S., Harvey, D. I., Leybourne, S. J., Taylor, A. R., & Zu, Y. (2023). CUSUM-Based Monitoring for Explosive Episodes in Financial Data in the Presence of Time-Varying Volatility. Journal of Financial Econometrics, 21(1), 187-227. https://doi.org/10.1093/jjfinec/nbab009

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.

Simple Tests for Stock Return Predictability with Good Size and Power Properties (2021)
Journal Article
Harvey, D. I., Leybourne, S. J., & Taylor, A. M. R. (2021). Simple Tests for Stock Return Predictability with Good Size and Power Properties. Journal of Econometrics, 224(1), 198-214. https://doi.org/10.1016/j.jeconom.2021.01.004

We develop easy-to-implement tests for return predictability which, relative to extant tests in the literature, display attractive finite sample size control and power across a wide range of persistence and endogeneity levels for the predictor. Our a... Read More about Simple Tests for Stock Return Predictability with Good Size and Power Properties.

Real‐Time Detection of Regimes of Predictability in the U.S. Equity Premium (2020)
Journal Article
Harvey, D. I., Leybourne, S. J., Sollis, R., & Taylor, A. R. (2021). Real‐Time Detection of Regimes of Predictability in the U.S. Equity Premium. Journal of Applied Econometrics, 36(1), 45-70. https://doi.org/10.1002/jae.2794

We propose new real-time monitoring procedures for the emergence of end-of-sample predictive regimes using sequential implementations of standard (heteroskedasticity-robust) regression t-statistics for predictability applied over relatively short tim... Read More about Real‐Time Detection of Regimes of Predictability in the U.S. Equity Premium.

Date-stamping multiple bubble regimes (2020)
Journal Article
Harvey, D. I., Leybourne, S. J., & Whitehouse, E. J. (2020). Date-stamping multiple bubble regimes. Journal of Empirical Finance, 58, 226-246. https://doi.org/10.1016/j.jempfin.2020.06.004

Identifying the start and end dates of explosive bubble regimes has become a prominent issue in the econometric literature. Recent research has demonstrated the advantage of a model-based minimum sum of squared residuals estimator, combined with Baye... Read More about Date-stamping multiple bubble regimes.

Sign-based Unit Root Tests for Explosive Financial Bubbles in the Presence of Deterministically Time-Varying Volatility (2019)
Journal Article
Harvey, D. I., Leybourne, S. J., & Zu, Y. (2020). Sign-based Unit Root Tests for Explosive Financial Bubbles in the Presence of Deterministically Time-Varying Volatility. Econometric Theory, 36(1), 122-169. https://doi.org/10.1017/S0266466619000057

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 explosive bubbles with time-varying volatility (2018)
Journal Article
Harvey, D. I., Leybourne, S. J., & Zu, Y. (2019). Testing explosive bubbles with time-varying volatility. Econometric Reviews, 38(10), 1131-1151. https://doi.org/10.1080/07474938.2018.1536099

This paper considers the problem of testing for an explosive bubble in financial data in the presence of time-varying volatility. We propose a weighted least squares-based variant of the Phillips, Wu and Yu (2011) test for explosive autoregressive be... Read More about Testing explosive bubbles with 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
Iacone, F., Leybourne, S. J., & Taylor, A. R. (2018). Testing the order of fractional integration of a time series in the possible presence of a trend break at an unknown point. Econometric Theory, 35(6), 1201 - 1233. https://doi.org/10.1017/s0266466618000361

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.

Real-time monitoring for explosive financial bubbles (2018)
Journal Article
Astill, S., Harvey, D. I., Leybourne, S. J., Sollis, R., & Taylor, A. R. (2018). Real-time monitoring for explosive financial bubbles. Journal of Time Series Analysis, 39(6), 863-891. https://doi.org/10.1111/jtsa.12409

We propose new methods for the real-time detection of explosive bubbles in financial time series. Most extant methods are constructed for a fixed sample of data and, as such, are only appropriate when applied as one-shot tests. Sequential application... Read More about Real-time monitoring for explosive financial bubbles.

A Bootstrap Stationarity Test for Predictive Regression Invalidity (2018)
Journal Article
Georgiev, I., Harvey, D. I., Leybourne, S. J., & Taylor, A. R. (2018). A Bootstrap Stationarity Test for Predictive Regression Invalidity. Journal of Business and Economic Statistics, 37(3), 528-541. https://doi.org/10.1080/07350015.2017.1385467

In order for predictive regression tests to deliver asymptotically valid inference, account has to be taken of the degree of persistence of the predictors under test. There is also a maintained assumption that any predictability in the variable of in... Read More about A Bootstrap Stationarity Test for Predictive Regression Invalidity.

Testing for parameter instability in predictive regression models (2018)
Journal Article
Gorgiev, I., Harvey, D. I., Leybourne, S. J., & Taylor, A. R. (2018). Testing for parameter instability in predictive regression models. Journal of Econometrics, 204(1), https://doi.org/10.1016/j.jeconom.2018.01.005

We consider tests for structural change, based on the SupF and Cramer-von-Mises type statistics of Andrews (1993) and Nyblom (1989), respectively, in the slope and/or intercept parameters of a predictive regression model where the predictors display... Read More about Testing for parameter instability in predictive regression models.

Testing for a unit root against ESTAR stationarity (2017)
Journal Article
Harvey, D. I., Leybourne, S. J., & Whitehouse, E. J. (2018). Testing for a unit root against ESTAR stationarity. Studies in Nonlinear Dynamics and Econometrics, 22(1), https://doi.org/10.1515/snde-2016-0076

In this paper we examine the local power of unit root tests against globally stationary exponential smooth transition autoregressive [ESTAR] alternatives under two sources of uncertainty: the degree of nonlinearity in the ESTAR model, and the presenc... Read More about Testing for a unit root against ESTAR stationarity.

All Outputs (36)