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Autor
Osińska Magdalena (Nicolaus Copernicus University in Toruń, Poland)
Tytuł
Forecasting Stochastic Unit Root Models
Źródło
FindEcon Monograph Series : advances in financial market analysis, 2007, nr 3, s. 27-43, rys., tab., bibliogr. s. 42-43
Tytuł własny numeru
Financial markets : principles of modeling forecasting and decision-making
Słowa kluczowe
Modele stochastyczne, Ceny akcji, Symulacja Monte Carlo
Stochastic models, Shares prices, Monte Carlo simulation
Abstrakt
The aim of the research was to find out the mechanism underlying the stock prices behaviour and extrapolate it out of the sample. The stochastic unit root model was assumed. The empirical results of the tests confirmed that hypothesis in significant majority of analysed time series. Then the models were estimated and used for prediction. Two methods of forecasting were used. These were: MC-based forecasting and sequential extrapolation of fitted values. The comparison of the results has shown that the main characteristics of the models are statistically significant. Comparing the forecasting results three main findings can be stated:
• sequential extrapolation seems to be a satisfactory method of forecasting STUR processes;
• forecasting weekly data we can observe the fact: the longer forecast horizon the smaller prediction error;
• in the sample - better results were obtained for MC method.
As concerns the effectiveness of central tendency measures like median or mean, not homogeneous results are obtained, so it cannot be decided which one is to be preferred. Despite of the deterministic or stochastic method of forecasting, stochastic unit root model seems to be a quite reasonable representation of the conditional mean of the stock prices and its behaviour in forecasting can be considered as satisfactory. (fragment of text)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
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Bibliografia
Pokaż
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  6. Górka J., Osińska M. (2006), "STUR Tests and Their Sensitivity for Non-Linear Transformations and GARCH. A Monte Carlo Analysis", Paper accepted for presentation at Mathematical Methods in Economics 2006, Faculty of Economics, University of West Bohemia in Pilsen, Czech Republic, September.
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  9. Kwiatkowski J. (2005), "Bayesian Analysis of Stochastic Unit Root Models", Paper presented at International Conference FindEcon, Łódź University, Łódź.
  10. Kwiatkowski J., Osińska M. (2005), "Forecasting STUR Processes. A Comparison to Threshold and GARCH Models", Acta Universitatis Lodzienzis.
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  15. Osińska M. (2003), Stochastic Unit Root Processes Properties and Application, in: Weife W., Welfe A. (eds.), Macromodels'2003, Łódź: Łódź University Press.
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  18. Tsay R. S. (2002), Analysis of Financial time Series, New York: Wiley.
Cytowane przez
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Język
eng
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