Outputs (34)

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. (2024). Bonferroni-Type Tests for Return Predictability with Possibly Trending Predictors. Journal of Applied Econometrics, 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.

Testing for Equal Average Forecast Accuracy in Possibly Unstable Environments (2024)
Journal Article
Harvey, D. I., Leybourne, S. J., & Zu, Y. (in press). Testing for Equal Average Forecast Accuracy in Possibly Unstable Environments. Journal of Business and Economic Statistics,

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.

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.