The Essex Centre for Macro and Financial Econometrics warmly invites you to join guest speaker Professor David Harvey from the University of Nottingham as he discusses his work on heteroskedasticity.
13:30 - 14:30
Professor David Harvey, University of Nottingham
Lectures, talks and seminars
Essex Centre for Macro and Financial Econometrics (ECMFE) Research Seminar Series
Essex Business School
Dr Yuqian Zhao firstname.lastname@example.org
The Essex Centre for Macro and Financial Econometrics (ECMFE) brings together academic and industry expertise from inside and outside the University of Essex to research and help solve important issues in financial markets.
Heteroskedasticity is a common feature in empirical time series analysis, and this presentation will consider the effects of unconditional heteroskedasticity in statistical tests for equal forecast accuracy.
In such a context, it is proposed that two new Diebold-Mariano-type tests for equal forecast accuracy which have two key properties.
First, like the original Diebold-Mariano test, the new tests have size that is robust to heteroskedasticity.
Second, the new tests have the potential to achieve power improvements relative to the original Diebold-Mariano test for a quite general class of loss differential series.
The size validity and potential power superiority of the new tests are studied theoretically and in Monte Carlo simulations. The new tests are applied to competing forecasts for the GBP/USD exchange rate, and also survey-based forecasts for US output.
This seminar is free to attend with no need to register in advance.
We warmly encourage you to share with friends, colleagues and classmates.
David Harvey is a Professor of Econometrics at the University of Nottingham and a fellow of the Granger Centre for Time Series Econometrics.
His current research interests are in the area of time series econometrics, in particular tests for bubbles, forecast evaluation and predictive regressions.
His work has been published on many top econometrics/economics journals, including;
as well as many more.