Symbolic analysis of indicator time series by quantitative sequence alignment

Takuya Yamano, Kodai Sato, Taisei Kaizoji (), Jan-Michael Rost and Lukás Pichl

Computational Statistics & Data Analysis, 2008, vol. 53, issue 2, 486-495

Abstract: Symbolic analysis of economic indicators and derived time series offers an advantage of transferring quantitative values into qualitative notions by indexing intervals of numerical data with symbols. While differences in the numerical indicators are routinely measured by subtraction, differences in the symbolic indicators can be compared via more procedural quantitative-scoring schemes, the complexity of which depends on the alphabet size. In effect, the similarity of symbolic data sequence becomes a subtle measure. Upon motivating principles of symbolic analysis, our analysis illustrates how the optimized numerical scoring for alignment schemes may reveal functional and causal relations among the indicator data. The approach of symbolic analysis is particularly suitable for data processing in economics, in which partitioning of resources, competence, information access, or knowledge representation is common by the methodological design.

Date: 2008
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