Applied Time Series Analysis and Economic Forecasting

Catalog description

This course provides students with the analytical tools necessary to analyze time series data in order to examine past trends and to forecast future ones. Students will learn practical time series forecasting techniques with particular emphasis on the ARIMA method and conditional volatility (ARCH) models and they will perform a variety of data analyses on the computer using R/Rstudio. These methods are extensively employed in economic, financial and business forecasts and can be used for various purposes such as stock market analysis, economic forecasting, risk assessment, budgetary analysis, Census analysis, yield projection, and sales forecasting. To gain a deeper understanding of how the methods work, their theoretical underpinnings will be discussed to some extent, however, the course is mainly concerned with the applications of these techniques in forecasting economic time series.