YANG ZU's Outputs (13)

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.

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.

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.

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.

Adaptive Testing for Cointegration With Nonstationary Volatility (2021)
Journal Article
Boswijk, H. P., & Zu, Y. (2022). Adaptive Testing for Cointegration With Nonstationary Volatility. Journal of Business and Economic Statistics, 40(2), 744-755. https://doi.org/10.1080/07350015.2020.1867558

This article develops a class of adaptive cointegration tests for multivariate time series with nonstationary volatility. Persistent changes in the innovation variance matrix of a vector autoregressive model lead to size distortions in conventional c... Read More about Adaptive Testing for Cointegration With Nonstationary Volatility.

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.

Adaptive wild bootstrap tests for a unit root with non-stationary volatility (2018)
Journal Article
Boswijk, P., & Zu, Y. (2018). Adaptive wild bootstrap tests for a unit root with non-stationary volatility. Econometrics Journal, 21(2), 87-113. https://doi.org/10.1111/ectj.12100

© 2017 The Authors. The Econometrics Journal published by John Wiley & Sons Ltd on behalf of Royal Economic Society. Recent research has emphasized that permanent changes in the innovation variance (caused by structural shifts or an integrated vola... Read More about Adaptive wild bootstrap tests for a unit root with non-stationary volatility.

Consistent nonparametric specification tests for stochastic volatility models based on the return distribution (2017)
Journal Article
Zu, Y., & Boswijk, P. (2017). Consistent nonparametric specification tests for stochastic volatility models based on the return distribution. Journal of Empirical Finance, 41, 53-75. https://doi.org/10.1016/j.jempfin.2016.12.005

© 2016 Elsevier Ltd This paper develops nonparametric specification tests for stochastic volatility models by comparing the nonparametically estimated return density and distribution functions with their parametric counterparts. Asymptotic null distr... Read More about Consistent nonparametric specification tests for stochastic volatility models based on the return distribution.

A note on the asymptotic normality of the kernel deconvolution density estimator with logarithmic chi-square noise (2015)
Journal Article
Zu, Y. (2015). A note on the asymptotic normality of the kernel deconvolution density estimator with logarithmic chi-square noise. Econometrics, 3(3), 561-576. https://doi.org/10.3390/econometrics3030561

© 2015 by the author; licensee MDPI, Basel, Switzerland. This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observatio... Read More about A note on the asymptotic normality of the kernel deconvolution density estimator with logarithmic chi-square noise.

Nonparametric specification tests for stochastic volatility models based on volatility density (2015)
Journal Article
Zu, Y. (2015). Nonparametric specification tests for stochastic volatility models based on volatility density. Journal of Econometrics, 187(1), 323-344. https://doi.org/10.1016/j.jeconom.2015.02.045

© 2015 Elsevier B.V. This paper develops a specification test for stochastic volatility models by comparing the nonparametric kernel deconvolution density estimator of an integrated volatility density with its parametric counterpart. L2 distance is u... Read More about Nonparametric specification tests for stochastic volatility models based on volatility density.

Estimating spot volatility with high-frequency financial data (2014)
Journal Article
Zu, Y., & Boswijk, P. (2014). Estimating spot volatility with high-frequency financial data. Journal of Econometrics, 181(2), https://doi.org/10.1016/j.jeconom.2014.04.001

We construct a spot volatility estimator for high-frequency financial data which contain market microstructure noise. We prove consistency and derive the asymptotic distribution of the estimator. A data-driven method is proposed to select the
scale... Read More about Estimating spot volatility with high-frequency financial data.