Time Series Data Analysis and Modelling using Stata Course

Overview

INTRODUCTION

The course will show how economic and financial time series can be modeled and analyzed. The aim is to provide understanding and insight into the methods used, as well as explaining the technical details. Statistical modeling will be demonstrated using the Stata Software and participants will be given the opportunity to use Stata in class. Statistical modeling will be demonstrated using the Stata Software. This course will equip you with skills needed in statistical analysis. Make meaningful statistical choices and help in time series forecasting.

DURATION

5 Days

What you will learn

TOPICS TO BE COVERED

• Introduction
• Stationary time series
• Unobserved components and signal extraction.
• Time Series Models
• ARIMA models
• Structural time series models
• Explanatory variables and intervention analysis
• State space models and the Kalman filter.
• Signal extraction.
• Missing observations and other data irregularities
• Spectral analysis
• Spectra of ARMA processes; stochastic cycles; linear filters; estimation of spectrum
• Trends and cycles
• Analysis of the effects of moving average and differencing operations
• Hodrick-Prescott and band-pass filters. Seasonality
• Multivariate time series models
• Common trends and co-integration; control groups
• Nonlinear models. Financial econometrics; distributions of returns, stochastic volatility and GARCH
• Dynamic conditional score models
• Multivariate volatility models.

What you require

Previous course on Data Management, Graphics and Statistical analysis using Stata or to be familiar with Stata software.