Introduction to Time Series and Forecasting

This book builds on previous econometric theory and focuses on the most common or important models for econometric time-series and econometric forecasting.The focus of the book is on the two models at the core of econometric time-series/forecasting: ARMA and ARIMA.It covers different versions of AR and MA models in other words.Pre-requisites for this book are:1. mathematical economics covering integrals, differentiation...as well as matrix algebra2. statistics on first-year undergraduate levelYou should also know some 1st-year econometrics before you start with this book, through books such as Hill's Principles of Econometrics, Gujarati's Basic Econometrics, or Johnston's Econometric Methods and similar.It is true what a previous reviewer complained about - that this is not an introductory book on econometrics: you need to have studied econometrics before, the more mathematical the better, i.e Gujarati or Johnston's books.This is an introductory book on time-series, not econometrics.A very nice things is that the book uses many real-life examples, alot of graphs, and has detailed explanations of the mathematics. The examples are not just from the field of economics but other social sciences as well.My only complaint about the book is it's choice of software.The book uses a special program called ITSM, which comes with the book (2002 edition +), and they teach you how to use it.I think it would have been much better to have done the material with more "professional" software that is more frequently used in real-life applications - like Stata, Gauss, SAS, R or even EViews.