Abstract
Compared to the predictive models for forecasting crude oil price, the descriptive models are also important for discovering the relations among factors that have influence on crude oil price. In this paper, linguistic summarization of time series, a descriptive technique, is used to summarize the Europe Brent Spot Price (EBSP) data (dollars per barrel) from May 1987 to July 2013 on daily and monthly base. This study is the first attempt in the literature for linguistic summarization of the EBSP time series with the aim to establish a decision support tool that can be used for generating linguistic propositions helping the estimation of future behaviors and fluctuations of oil price time series for oil-importer countries such as Turkey. Economic interpretations of generated linguistic propositions about the main features of EBSP trends (duration, dynamics of change, and variability) and a procurement strategy, indicating that Turkey could cut back on oil importation about 573.88 million between 1996 and 2012, are suggested from the perspective of Turkey.
| Original language | English |
|---|---|
| Pages (from-to) | 946-970 |
| Number of pages | 25 |
| Journal | International Journal of Intelligent Systems |
| Volume | 29 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - Oct 2014 |
| Externally published | Yes |
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