Contents

Course description
Course Programme
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Terms and Conditions
About PcGive
About PcGets

Timberlake Consultants Ltd, the publisher and distributor of OxMetrics, invite you to attend a three-day or five-day course in Central London, covering the use of econometrics with PcGive Professional 10, the well known econometrics software package developed by Prof. David F. Hendry and Jurgen A. Doornik.

The Course - Several major advances in time series, forecasting and software engineering have occurred in the past few years. These advances provide a major breakthrough in the modelling of time series using easy-to-use object-oriented Windows based software. The course aims to provide delegates with background on econometric modelling methods and demonstrate, using financial data, how to interpret and report the results.

Who should attend - The course, given in English, is aimed at forecasters and researchers in

• Economic Research/ Model Building
  
• Financial Modelling/ Arbitrage Trading
  
• Quantitative Investment Management
  
• Sales and Inventory Forecasting
  
• Traffic Modellers
  
• Energy Load Forecasting
  
• and more
  

Advantages - The course will

• Review all major econometric modelling methods
  
• Provide a practical and systematic approach to the modelling of business and financial time series data
  
• Provide hands-on experience in building econometric models - each delegate is provided with a computer throughout the course
  
• Provide an opportunity for you to meet with a panel of experienced modellers to discuss industry-specific applications related to forecasting and time series analysis
  

The Principal Lecturer - The principal lecturer is:

Dr Giovanni Urga, Reader in Financial Econometrics at the Department of Investment, Risk Management and Insurance, City University Business School. Giovanni is also visiting Professor in Econometrics at Bergamo University (Italy) and at the New Economic School in Moscow.

He was formerly at the London Business School and previously at Queen Mary and Westfield College. He has published papers on econometric methodology, the econometrics of panel data, financial econometrics, the economics and econometrics of investment, modelling structural breaks, modelling common stochastic trends, emerging markets, transition economies stocks markets.
http://www.business.city.ac.uk/irmi/giovanni_urga.html

Cost - The cost of the course are:

DAY 1 - Review of the linear regression model

Economic and Econometric models. Least square estimators (LS/OLS): classical assumptions and properties. Restricted least squared estimators. Test of hypotheses. Departures from the classical assumptions and generalised least squares. Alternative functional forms. Use of dummy variables. Specification errors. Method of instrumental variables.

Introduction to PcGive: data entry and management.
Empirical Illustration: the consumption function revisited.

DAY 2 - Dynamic modelling 1

AR, MA, ARMA, and ARIMA modelling. Vector Autoregression (VAR) models. Alternative econometric methodologies. Dynamic specifications and tests for validating the models: mispecification tests. Non-nested models, encompassing and model selection. Exogeneity and causality in econometrics. Forecasting.

Empirical Illustration: the money demand and inflation.

DAY 3 - Dynamic modelling 2.

Introduction to models of non-stationary time series. Spurious correlation. Difference stationary and stochastic trends. Trend stationary and deterministic trends. Unit roots. Dickey-Fuller, Phillips and Perron tests. (Error) Equilibrium-correction models.

Empirical Illustration: consumption function, disposable income, inflation, money demand, interest rates and stock market prices.

DAY 4 - Multivariate time series models.

General-to-specific dynamic specification. Cointegration in single equations: Engle-Granger (OLS). Cointegration systems: Johansen (Maximum Likelihood).

Empirical Illustration: consumption function, money demand and stock market prices.

DAY 5 - Univariate and Multivariate financial times series models

Introduction to autoregressive conditional heteroscedasticity. Measuring volatility over time. ARCH, GARCH, ARCH-M, E-GARCH models. Lagrange multipier test for ARCH.

Empirical Illustration: the foreign exchange rates and stock prices volatility.