Outputs (37)

Unit Root Tests for Explosive Financial Bubbles in the Presence of Deterministic Level Shifts (2025)
Journal Article
Harvey, D. I., Leybourne, S. J., Tatlow, B. S., & Zu, Y. (2025). Unit Root Tests for Explosive Financial Bubbles in the Presence of Deterministic Level Shifts. Oxford Bulletin of Economics and Statistics, https://doi.org/10.1111/obes.12668

This paper considers the issue of testing for an explosive bubble in financial time series in the presence of deterministic level shifts. We demonstrate that the sign-based variants of the Phillips, Shi, and Yu (2015) test, proposed by Harvey, Leybou... Read More about Unit Root Tests for Explosive Financial Bubbles in the Presence of Deterministic Level Shifts.

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.

Bonferroni-Type Tests for Return Predictability With Possibly Trending Predictors (2024)
Journal Article
Astill, S., Harvey, D. I., Leybourne, S. J., & Robert Taylor, A. M. (2025). Bonferroni-Type Tests for Return Predictability With Possibly Trending Predictors. Journal of Applied Econometrics, 40(1), 37-56. https://doi.org/10.1002/jae.3094

The Bonferroni Q test of Campbell and Yogo (2006) is widely used in empirical studies investigating predictability in asset returns by strongly persistent and endogenous predictors. Its formulation, however, only allows for a constant mean in the pre... Read More about Bonferroni-Type Tests for Return Predictability With Possibly Trending Predictors.

Systemic risk in banking, fire sales, and macroeconomic disasters (2024)
Journal Article
Bougheas, S., Harvey, D. I., Kirman, A., & Nelson, D. (2024). Systemic risk in banking, fire sales, and macroeconomic disasters. Journal of Economic Dynamics and Control, 168, Article 104975. https://doi.org/10.1016/j.jedc.2024.104975

We develop a dynamic computational network model of the banking system where fire sales provide the amplification mechanism of financial shocks. Each period a finite number of banks offers a large, but finite, number of loans to households. Banks wit... Read More about Systemic risk in banking, fire sales, and macroeconomic disasters.

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.