Training Calendar

Stata Workshop in Time Series

Cass Business School, Bunhill Row, London EC1Y 8TZ 3 days Stata Intermediate, Introductory
Econometrics, Statistics, 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.

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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.

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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.

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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.

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Learning Ratio

40% Theory, 30% Demonstration and 30% Practical 

Daily Timetable

Day 1 (Wednesday, 6 February 2019)

TimeSession / 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)

TimeSession / 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
15:30-17:00 Session 8


Day 3 (Friday, 8 February 2019)

TimeSession / 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

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A basic knowledge of statistics and regression analysis is required. Familiarity with Stata id advisable.

Financial Econometrics Using Stata - Stata Press Publication - S.Boffelli and G.Urga (2016)

Introduction to Time Series Using Stata - Stata Press Publication - S. Becketti (2013)

 

Several academic papers will be suggested during the course to complement 

 

 

 

  •  CommercialAcademicStudent
    1 Day pass (06/02/2019 - 08/02/2019)
    2 Day pass (06/02/2019 - 08/02/2019)
    3 Day pass (06/02/2019 - 08/02/2019)

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Cass Business School is located approximately five to ten minutes walk from the nearest underground and railway stations (Moorgate, Old Street, Barbican and Liverpool Street).

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