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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.