Μεταπτυχιακές Εργασίες

Μόνιμο URI για αυτήν τη συλλογήhttps://pyxida.aueb.gr/handle/123456789/61

Περιήγηση

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Α Β Γ Δ Ε Ζ Η Θ Ι Κ Λ Μ Ν Ξ Ο Π Ρ Σ Τ Υ Φ Χ Ψ Ω

Τώρα δείχνει 1 - 1 από 1

Forecasting inflation rate: methods of univariate time series forecasting
(05/06/2019) Karameris, Konstantinos; Kyriazidou, Ekaterini; Tzavalis, Elias; Dimelis, Sophia
This dissertation attempts to forecast Greece's inflation rate, using functional univariate time series techniques. The goal is to cover a plethora of the most used methods of forecasting time series involving both Econometric and Machine Learning models. Some of the applied methods are the following: Simple Exponential Smoothing (SES), Holt's linear trend, Holt-Winter's Seasonal model and Box-Jenkins ARIMA (Autoregressive Integrated Moving Averages) methodology along with its extension the SARIMA (Seasonal Arima) methodology. Forecasting the inflation rate is of high importance given that the inflation is a key indicator of a country's economic activity. These forecasts can be used for the purpose of fiscal and monetary policy making, or in the private sector as the financial and labor market are greatly affected by changes in the inflation rate.