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Authors: Alexei Bocharov and Bo Thiesson

Affiliation: Microsoft Research, United States

ISBN: 978-989-8425-99-7

Keyword(s): Regime-switching time series, Spectral clustering, Regression tree, Oblique split, Financial markets.

Related Ontology Subjects/Areas/Topics: Applications ; Economics, Business and Forecasting Applications ; Model Selection ; Pattern Recognition ; Regression ; Spectral Methods ; Theory and Methods

Abstract: We introduce a non-parametric approach for the segmentation in regime-switching time-series models. The approach is based on spectral clustering of target-regressor tuples and derives a switching regression tree, where regime switches are modeled by oblique splits. Our segmentation method is very parsimonious in the number of splits evaluated during the construction process of the tree–for a candidate node, the method only proposes one oblique split on regressors and a few targeted splits on time. The regime-switching model can therefore be learned efficiently from data. We use the class of ART time series models to serve as illustration, but because of the non-parametric nature of our segmentation approach, it readily generalizes to a wide range of time-series models that go beyond the Gaussian error assumption in ART models. Experimental results on S&P 1500 financial trading data demonstrates dramatically improved predictive accuracy for the exemplifying ART models.

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Paper citation in several formats:
Bocharov, A. and Thiesson, B. (2012). NON-PARAMETRIC SEGMENTATION OF REGIME-SWITCHING TIME SERIES WITH OBLIQUE SWITCHING TREES.In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8425-99-7, pages 116-125. DOI: 10.5220/0003758601160125

@conference{icpram12,
author={Alexei Bocharov. and Bo Thiesson.},
title={NON-PARAMETRIC SEGMENTATION OF REGIME-SWITCHING TIME SERIES WITH OBLIQUE SWITCHING TREES},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2012},
pages={116-125},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003758601160125},
isbn={978-989-8425-99-7},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - NON-PARAMETRIC SEGMENTATION OF REGIME-SWITCHING TIME SERIES WITH OBLIQUE SWITCHING TREES
SN - 978-989-8425-99-7
AU - Bocharov, A.
AU - Thiesson, B.
PY - 2012
SP - 116
EP - 125
DO - 10.5220/0003758601160125

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