Course title

Time Series Analysis

Code

 MST 230

Professor

Marija Trpkova-Nestorovska, PhD

Course objectives (competences): Time series analysis is one of the basic tools available for economists in order to use them for examination and decision making during solving economic problems. This subject tends to make students capable for empirical analysis in the fields of business and economics while using time series. The students gain theoretical knowledge in time series models, while the lectures are performed in laboratory, actively using statistical software Minitab and Eviews. The analyzed problems are real time series from the business and economy of Republic of Macedonia.

 http://vremenskiserii.weebly.com/  

• To elaborate the methods for building ARIMA models.
• To use the time series models as tools for statistical inference and forecasting.
• To introduce methods for contegrated time series. 

Key words: Time series, decomposition, stochastic process, ARIMA models

1. Introduction
2. Decomposition of time series
3. Exponential smoothing
4. Times series and stochastic processes
5. Autoregressive integrated moving average models

Main  literature:

• Risteski, S., Tevdoski, D., and Trpkova, M. (2012). “Introduction in time series analysis“. University “Ss. Cyril and Methodious” in Skopje, Faculty of Economics – Skopje.
• Secondary literature:
• Hamilton, J (1994). Time Series Analysis. Princeton University Press.
• Yaffee, Robert, and Monnie McGee (2000). Introduction to Time Series Analysis and Forecasting. Academic Press.
• Pena, D., G.C. Tiao and R.S. Tsay (2001). A Course in Time Series Analysis, Wiley.