* This page is for a past course. Please note the details for our 2013 Econometrics Summer School, Oxford can be found here.
2012 Econometrics Summer School, Oxford, UK
- Date: 7-14 July, 2012
- Location: Manor Road Building, University of Oxford, UK
Course Overview
Timberlake Consultants are pleased to invite you to the 2012 Econometrics Summer School taking place at University of Oxford, UK. The Summer School comprises of three 2.5-day courses delivered by leading econometricians including Dr. Jurgen A. Doornik. The sessions will run consecutively and participants can choose to attend one or more courses. This is a great opportunity for students, academics and professionals to expand their econometrics skills and keep up-to-date with major recent developments in applied econometric modelling.
Delivered By: Dr. Jurgen A. Doornik and Dr. Jennifer Castle
The course will cover the theory and practice of econometric modeling in a non-stationary and evolving world, when the model and mechanism differ. The following topics will be described in the course: how to embed theory models in selection; impulse-indicator saturation for handling multiple breaks during selection; simultaneous systems and VAR modeling; and tests for, and modeling of, non-linearity, super exogeneity and invariance.
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Delivered By: Dr. Jennifer Castle and Prof. Grayham Mizon
The course will cover the theory and practice of economic forecasting facing a non-stationary and evolving world, when the model differs from the data generation process. A generalized taxonomy of forecast errors is developed, allowing for structural change in the forecast period, the model to be mis-specified over the sample period, and selected from sample evidence, the parameters of the model to be estimated (possibly inconsistently) from the data, which might be measured with error, the forecasts to commence from incorrect initial conditions, and innovation errors to cumulate over the forecast horizon. The taxonomy reveals the central role of unanticipated location shifts, and helps explain the outcomes of forecasting competitions. Other potential sources of forecast failure seem less relevant. Regime-shift non-stationarity can be removed by co-breaking (the cancellation of breaks across linear combinations of variables)
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Delivered By: Dr. Sebastien Laurent
The course will cover the theory and practice of volatility modelling and forecasting. Traditional regression tools have shown their limitation in the modelling of financial time-series. Assuming that only the conditional mean could be changing with covariates while the variance remains constant over time often revealed to be an unrealistic assumption in practice. The following topics will be described in the course: the ARCH model and some of its most important extensions, multivariate GARCH models, value-at-risk forecasting, ranking volatility models in terms of their forecasting power, introduction of continuous-time stochastic volatility models and non-parametric estimators of the volatility, how to disentangle jumps and the smooth part of volatility, how to forecast volatility in presence of jumps, how to identify jumps.
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Register for the Oxford, 2012 Econometrics Summer school online
Logistics and Travel
Timberlake Consultants can provide local logistical assistance and advice on travel. Please contact us to discuss your requirements further.
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Last modified: 2013-04-09 12:26:38
