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Forecasting inflation in Montenegro using univariate time series models

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Lipovina-Božović M., Cerovic J., Vujosević S.
Business and Economic Horizons
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2015
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vol. 11
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issue 1
51-63
EN
The analysis of price trends and their prognosis is one of the key tasks of the economic authorities in each country. Due to the nature of the Montenegrin economy as small and open economy with euro as currency, forecasting inflation is very specific which is more difficult due to low quality of the data. This paper analyzes the utility and applicability of univariate time series models for forecasting price index in Montenegro. Data analysis of key macroeconomic movements in previous decades indicates the presence of many possible determinants that could influence forecasting result. This paper concludes that the forecasting models (ARIMA) based only on its own previous values cannot adequately cover the key factors that determine the price level in the future, probably because of the existence of numerous external factors that influence the price movement in Montenegro.
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Application of adaptive methods in demographic variables forecasting

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Sojka E.
Econometrics. Ekonometria. Advances in Applied Data Analytics
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2015
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issue 3 (49)
55-65
EN
The research paper is focused on the assessment of the usefulness of adaptive methods in forecasting demographic variables. The goal of the paper is to conduct the retro and prospective analysis of selected demographic values in the sphere of changes in time, and also to indicate an efficient method for the forecasting of the studied values in subsequent periods. The time series for Poland for the period between 2000 and 2013 are the basis for the development of the forecast. Mean squared errors of ex post forecasts are used as forecast quality measures. The results of the study show that among the applied methods of forecasting, the method of creeping trend with harmonic weights is the most suitable as it gives the smallest forecast errors.
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GARCH CLASS MODELS PERFORMANCE IN CONTEXT OF HIGH MARKET VOLATILITY

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Małecka M.
Acta Universitatis Lodziensis. Folia Oeconomica
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2014
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vol. 3
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issue 302
EN
In the presented paper GARCH class models were considered for describing and forecasting market volatility in context of the economic crisis. The sample composition was designed to emphasize models performance in two groups of markets: well-developed and transition. As a preview to our results, we presented the procedure of model selection form the GARCH family. We distinguished three subperiods in the time series in a way that the dependencies between forecast outcomes and a scale of market volatility were emphasized. The comparison of the forecast errors revealed a serious problem of volatility prediction in times of high market instability. The crisis impact was particularly apparent in transition markets. Our findings showed that GARCH models allowed risk control, with risk understood as a relation of forecast error to the level of predicted volatility.
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