Time Series Modelling and Forecasting using Stata - (ONLINE)

Time Series Modelling and Forecasting using Stata - (ONLINE)

Posted on

Start Date

End Date

Application Deadline

Type

Professional training

Reference Number

D-EF39-OL

Certifications & Titles

Certificate of participation

Study Options

Part Time

Fees

Regular fees: 355 - 675 EUR

Comment:

Fees and Registration:

  • Students: € 355.00
  • PhD Students: € 455.00
  • University: € 505.00
  • Commercial: € 675.00

Kindly note that:

  • To be eligible for student fees, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status.
  • Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number.
  • The number of participants is limited to 8. Places, will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled.
  • Course fees cover: course materials (handouts, Stata do files and datasets to be used during the course), a temporary licence of Stata valid for 30 days from the beginning of the course.

Individuals interested in attending the training course should contact TStat Training to ask for a registration form. The completed application should then be returned to TStat by the 14th of January 2022.

Funding Options

Students have access to discounted courses fees

Time Series data is today available for a wide range of several phenomena in Business, Finance, Economics, Public Health, the Political and Social Sciences. The aim of our Times Series Modelling and Forecasting Course  is therefore to provide researchers and professionals with the standard tool kit required for the analysis of time series data in Stata. As such the programm has been developed to offers an overview of the most commonly used methods for analysing, modelling and forecasting the dynamic behaviour of time series data, offering practical examples of empirical modelling using real-world data. Module 1 provides an introduction to Stata’s basic commands before moving to the analysis of time series features and to univariate time series models. Module 2 covers multivariate time series models for stationary and non-stationary series.

Program:

SESSION I: WORKING WITH TIME SERIES IN STATA

  • A quick introduction to Stata for time series data:
  • Graphical analysis of time series:
  • Testing for autocorrelation and testing for unit root
  • Univariate time series models: theoretical elements and practical applications of modelling real-world macroeconomic series with the arima command
  • Modelling volatility: univariate ARCH/GARCH models. Theoretical elements and practical applications of modelling real-world financial time series with the arch command
  • Forecasting AR(I) MA-ARCH models

SESSION II: MULTIVARIATE TIME SERIES MODELS

  • Stationary Vector Autoregression (VAR) modelling: theoretical elements and practical applications of modelling real-world macroeconomic time series with the var command
  • Checking correct specification of VAR models: diagnostic tests and plots
  • Granger causality and impulse response function analysis
  • Non-stationary time series: an introduction to cointegration
  • Vector error-correction models: theoretical elements and practical applications of modelling real-world macroeconomic time series with the vecm command

For more specific program details click here!

Prerequisites:

Participants should have a knowledge of the inferential statistics and introductory econometric methods illustrated in Wooldridge, J. M (2019). Participants are NOT however, required to have any previous knowledge of Stata, since Module 1 provides an introduction to Stata’s basic time series commands.

Target Audience:

Researchers and professionals working in financial institutions, policy institutions, research departments of utilities, governments, corporations, Ph.D and Master students in biostatistics, economics, finance, engineering, psychology, social and political sciences needing to implement time series data analysis methods.

Course Duration:

This training course will be offered ONLINE on a part-time (two modules) basis  on the 20th-21st of January 2022 from 10:00 am to 1:30 pm Central European Time (CET).

Course Objectives:

At the end of the course, participants are expected to be able to autonomously implement the theories and methodologies discussed during the course, by personalizing the DO file program templates specifically developed during the course in order to enhance the effectiveness of their research.

Course Structure:

In common with TStat’s training philosophy, each individual session is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied (hands-on) segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Throughout the course, theoretical sessions are reinforced by case study examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques. The intuition behind the choice and implementation of a specific technique is of the utmost importance. In this manner, the course leader is able to bridge the “often difficult” gap between abstract theoretical methodologies, and the practical issues one encounters when dealing with real data. 

Course Reading:

Introduction to Time Series Using Stata. Stata Press Publication, S. Becketti (2020).
Financial Econometrics Using Stata. Stata Press Publication, S. Boffelli and G. Urga (2016).

More Information

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Attendance

Online

Posted on

Start Date

End Date

Application Deadline

Type

Professional training

Reference Number

D-EF39-OL

Certifications & Titles

Certificate of participation

Study Options

Part Time

Fees

Regular fees: 355 - 675 EUR

Comment:

Fees and Registration:

  • Students: € 355.00
  • PhD Students: € 455.00
  • University: € 505.00
  • Commercial: € 675.00

Kindly note that:

  • To be eligible for student fees, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status.
  • Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number.
  • The number of participants is limited to 8. Places, will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled.
  • Course fees cover: course materials (handouts, Stata do files and datasets to be used during the course), a temporary licence of Stata valid for 30 days from the beginning of the course.

Individuals interested in attending the training course should contact TStat Training to ask for a registration form. The completed application should then be returned to TStat by the 14th of January 2022.

Funding Options

Students have access to discounted courses fees