Linguistic Summarization of Europe Brent Spot Price Time Series Along with the Interpretations from the Perspective of Turkey

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.

Outlier detection using linguistically quantified statements

“…In the literature, there are works by Kacprzyk and others, which focus on linguistic summaries of time series and their application for the analysis of the quotations of an investment fund. Hatipoglu et al . applied linguistic summaries to economic interpretations of generated linguistic propositions about the main features of trends (duration, dynamics of change, and variability).…”