Vol 2, No 4 (2014)
Financial-Economic Time Series Modeling and Prediction Techniques – Review
Natasa Koceska, Saso Koceski
Abstract
Financial-economic time series distinguishes from other time series because they contain a portion of uncertainity. Because of this, statistical theory and methods play important role in their analysis. Moreover, external influence of various parameters on the values in time series makes them non-linear, which on the other hand suggests employment of more complex techniques for ther modeling. To cope with this challenging problem many researchers and scientists have developed various models and techniques for analysis of financial-economic time series and forecasting of the future trends, both linear and non-. This paper aims at reviewing current state-of-the-art techiques for financial-economic time series analysis and forecasting.
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Keywords
Prediction; Time Series; Data Mining; Stock Market Prediction; Forecasting Techniques
Publication information
Volume 2, Issue 4
Year of Publication: 2014
ISSN: 1857 - 8721
Publisher: EDNOTERA
How to cite
Koceska, N., Koceski, S.(2014). Financial-Economic Time Series Modeling and Prediction Techniques – Review. Journal of Applied Economics and Business, Vol 2, No. 4, 28-33.