Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection

Author

M. Verleysen
E. de Bodt
Amaury Lendasse, Missouri University of Science and TechnologyFollow

Abstract

A Crucial Problem in Non-Linear Time Series Forecasting is to Determine its Auto-Regressive Order, in Particular When the Prediction Method is Non Linear. We Show in This Paper that This Problem is Related to the Fractal Dimension of the Time Series, and Suggest using the Curvilinear Component Analysis (Cca) to Project the Data in a Non-Linear Way on a Space of Adequately Chosen Dimension, Before the Prediction itself. the Performances of This Method Are Illustrated on the Sbf 250 Index.

Recommended Citation

M. Verleysen et al., "Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1607, pp. 596 - 605, Springer, Jan 1999.

The definitive version is available at https://doi.org/10.1007/BFb0100527

Department(s)

Engineering Management and Systems Engineering

International Standard Book Number (ISBN)

978-354066068-2

International Standard Serial Number (ISSN)

1611-3349; 0302-9743

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jan 1999