Stata Workshop in Time Series

Overview

Time series data is nowadays collected for several phenomena in social and empirical sciences. This school focuses on the fundamental concepts required for the analysis, modelling and forecasting of time series data. The course provides an introduction to the theoretical foundation of time series models and a practical guide to the use of time series analysis techniques implemented in Stata 15.

The course is based on the textbook Financial Econometrics Using Stata by S.Boffelli and G.Urga (2016), Stata Press

Summary

Time series data is nowadays collected for several phenomena in social and empirical sciences. This school focuses on the fundamental concepts required for the analysis, modelling and forecasting of time series data. The course provides an introduction to the theoretical foundation of time series models and a practical guide to the use of time series analysis techniques implemented in Stata15.

The course is based on the textbook S.Boffelli and G. Urga (2016), Financial Econometrics Using Stata. Stata Press Publication.

 

Day 1 - Univariate Time Series Models

Session 1 & 2: 

  • Stochastic processes and time series. Stationarity, autocorrelation, normality.
  • Univariate time series models: Moving Average (MA), Autoregressive (AR), Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving Average (ARIMA) models. The Box&Jenkins approach.
  • Forecasting with ARMA models.
  • Empirical application: Analysis of the features of time series. The Box&Jenkins approach in practice.

Session 3 & 4: 

  • Unit root nonstationarity and main unit root tests: Augmented Dickey Fuller (ADF) and Phillips-Perron tests.
  • Equilibrium (error) correction model.
  • Spurious regression versus cointegration
  • The Engle&Granger two-step procedure for modelling cointegrating relationships
  • Empirical application: Estimating dynamic models and error correction models for nonstationary economic data.

Day 2 - Multivariate Time Series Models

Session 5 & 6: 

  • Stationary Vector Autoregression (VAR) modelling.
  • Structural vector autoregression (SVAR).
  • Granger causality.
  • Impulse response function analysis.
  • Empirical Application 2: Modelling the relationship between economic and financial stationary variables.

Session 7 & 8:

  • Non stationary and cointegrated VARs
  • The Johansen’s approach to multivariate cointegration.
  • Empirical application 2: Modelling long-run relationships in economics and finance.

Day 3 - Financial Time Series Models

Session 9 & 10: 

  • Volatility: features and measures.
  • Univariate models of conditional volatility: ARCH, GARCH, GARCH-in-mean, and IGARCH models.
  • Asymmetric GARCH models (SAARCH, EGARCH, GJRGARCH, TGARCH, APARCH). Leverage effect and news impact curve.
  • Empirical Application: Modelling asset returns volatility via alternative univariate GARCH models.

Session 11 & 12: 

  • Multivariate models of conditional volatility (MGARCH): Diagonal VECH model, Constant Conditional Correlation (CCC), Dynamic Conditional Correlation model (DCC)
  • Model diagnostic
  • Forecasting with univariate and multivariate GARCH models
  • Empirical Application: Modelling conditional correlations between asset returns with alternative multivariate GARCH models.

Learning Ratio

40% Theory, 30% Demonstration and 30% Practical 

Daily Timetable

Day 1 (Wednesday, 6 February 2019)

Time Session / Description

08:45-09:15 Arrival & Registration

09:30-11:00 Session 1

11:00-11:15 Tea/coffee break

11:15-12:45 Session 2

12:45-13:45 Lunch

13:45-15:15 Session 3

15:15-15:30 Tea/coffee break

15:30-17:00 Session 4


 

Day 2 (Thursday, 7 February 2019)

Time Session / Description

08:45-09:15 Arrival & Registration

09:30-11:00 Session 5

11:00-11:15 Tea/coffee break

11:15-12:45 Session 6

12:45-13:45 Lunch

13:45-15:15 Session 7

15:15-15:30 Tea/coffee break

15:30-17:00Session 8


 

Day 3 (Friday, 8 February 2019)

Time Session / Description

08:45-09:15 Arrival & Registration

09:30-11:00 Session 9

11:00-11:15 Tea/coffee break

11:15-12:45 Session 10

12:45-13:45 Lunch

13:45-15:15 Session 11

15:15-15:30 Tea/coffee break

15:30-17:00 Session 12

 

 

More Information / Apply Now

Start Date

End Date

Type

Summer schools

Fees

Regular fees: 310 - 1225 GBP

Comment:

Terms and Conditions

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course.
  • Payment of course fees required prior to the course start date.
  • Registration closes 1-calendar days prior to the start of the course.

    • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.
Cass%20Business%20School%2C%20London%2C%20United%20Kingdom

Cass Business School

London , United Kingdom

Start Date:

End Date:

Location

United Kingdom

London

Type

Summer schools

Cass%20Business%20School%2C%20London%2C%20United%20Kingdom