Multidimensional Forecasting and Pattern Matching

Research output: Chapter in Book/Report/Conference proceedingChapter


We apply a pattern matching algorithm to multidimensional forecasting. The algorithm searches for occurrences of patterns in multidimensional time series and computes their predictive accuracy. A genetic algorithm breeds then patterns that maximize this accuracy evolving ever better predictors. In an application to financial data, we show that the most successful patterns in training samples can retain a statistically and economically significant predictive power out-of-sample.
Original languageEnglish
Title of host publicationProceedings ITISE 2014
Subtitle of host publicationInternational work-conference on Time Series
Number of pages9
ISBN (Electronic)978-84-15814-97-9, Ignacio Rojas Ruiz, Gonzalo Ruiz Garcia
Publication statusPublished - Jun 2014


  • multidimensional forecasting
  • genetic algorithms
  • pattern matching

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