acta physica slovaca |
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Acta Physica Slovaca 67, No.1, 1 – 83 (2016) (83 pages)
STUDY OF PREDICTION MODELS FOR TIME SERIES Erik Bartoša Richard Pincák b,c aInstitute of Physics, Slovak Academy of Sciences Dúbravská cesta 9, SK-845 11 Bratislava, Slovakia b Institute of Experimental Physics, Slovak Academy of Sciences Watsonova 47, SK-043 53 Košice, Slovakia c Bogoliubov Laboratory of Theoretical Physics, Joint Institute for Nuclear Research, 141980 Dubna, Moscow Region, Russia Full text: ::pdf :: (Received 4 August 2017, accepted 9 October 2017) Abstract: We present the concept which approaches the string theory to the field of time series forecast and data analysis through a transformation of currency rate data to the topology of physical strings and branes. We introduce new type of prediction models for financial time series based on string invariants. The performance of the first versions of prediction models is compared to support vector machines and artificial neural networks on an artificial and financial time series. We propose a string angular momentum as an another tool to analyze the stability of currency rates except the historical volatility. Next we investigate the fundamental properties of the space of time series data. We provide the proof that the space of time series data is a Kolmogorov space with T0-separation axiom using the loop space of time series data. PACS: 11.25.-w, 11.25.Wx, 05.45.Tp, 89.65.Gh Keywords: String Theory, Time-Series Analysis, Econophysics, Financial Market |
ISSN 1336-040X (online) ISSN 0323-0465 (printed) For authors: ActaStyle.cls |
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