Time Series Forecasting & Econometrics Modelling

This course deals with econometric modelling, estimation, and testing of relationships and models for time series data
with main focus on methods for handling non-stationary time series.

Course Duration: 2 days (full-time)

Daytime Classes | Evening Classes | Virtual & Online Classes  

You will learn to…

Gain an understanding of basic econometric theory, terminology, estimation and test principles for time series models and data

Create and estimate dynamic single-equation and multi-equation models for stationary as well as non-stationary time series data

Interpret models as well as how they can be used for examining forecasting errors

Estimate and interpret the difference between long-run and short-run effects

About this course

This course deals with econometric modelling, estimation, and testing of relationships and models for time series data with main focus on methods for handling non-stationary time series. A necessary technical background will be established throughout the course that includes introduction to stationarity and non-stationarity concepts, ARMA- and VAR-modelling, deterministic and stochastic trends, integrated and cointegrated variables, unit roots, and identification. The course also covers the importance of VAR-models for econometric modelling. The course emphasises applications concerning modelling, estimation, policy analysis and forecasting.

4 Benefits of booking this course with us

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Course Dates and Location

  • This course can be attended physically at our London Training Centre or virtually and live via our Virtual Class Platform
  • Please contact us for more details of dates.

Testimonials

“The facilitator met and exceeded my expectations, hand -on exercises on industry use case senarios was done in groups to mimick team-work experience in work enviroment.”
Anonymous, Course Feedback Form

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Course Content

  1. The Nature and Scope of Econometric Modelling
  2. Review of Probability
  3. Review of Statistics
  4. Regression with a Single Regressor
  5. Multiple Regression: Estimation and Hypothesis Testing
  6. Non-Linear Regression Functions
  7. Functional Forms of Regression Models
  8. Model Selection: Criteria and Tests
  9. Regression with Panel Data
  10. Trend Seasonality and Cyclic Components
  11. Exponential Smoothing
  12. Interventions
  13. Pure and Causal ARIMA Modelling
  14. Autoregressive
  15. Moving Average
  16. Integration
  17. Multivariate ARIMA
  18. Regression with Binary Dependent Variable
  19. Instrumental Variables Regression
  20. Experiments And Quasi-Experiments
  21. Multicollinearity: What Happens if Explanatory Variables are Correlated
  22. Heteroscedasticity: What Happens if the Error Variance is Nonconstant
  23. Autocorrelation: What Happens if Error Terms are Correlated
  24. Introduction to Time Series Regression and Forecasting
  25. Estimation of Dynamic Causal Effects
  26. Additional Topics in Time Series Regression
  27. Time Series versus Econometric Modelling
  28. Some Practical Examples
  29. Econometric Analysis in Multi-Channel Marketing
  • This course is intended for Financial Analyst, or Data Analyst/Scientist working in Financial Services sector, with interest in forecasting and econometrics modelling.
  • You will need to have some basic knowledge of statistics to take this course.

£1,500 per person, ex VAT

Special Discount for Pairview alumni and current delegates.