Financial Time Series Modelling Using Fractal Interpolation Functions

Author:

Manousopoulos Polychronis1ORCID,Drakopoulos Vasileios2ORCID,Polyzos Efstathios3ORCID

Affiliation:

1. Bank of Greece, 21 Eleftherios Venizelos Avenue, 10250 Athens, Greece

2. Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131 Lamia, Greece

3. College of Business, Zayed University, Abu Dhabi P.O. Box 144534, United Arab Emirates

Abstract

Time series of financial data are both frequent and important in everyday practice. Numerous applications are based, for example, on time series of asset prices or market indices. In this article, the application of fractal interpolation functions in modelling financial time series is examined. Our motivation stems from the fact that financial time series often present fluctuations or abrupt changes which the fractal interpolants can inherently model. The results indicate that the use of fractal interpolation in financial applications is promising.

Publisher

MDPI AG

Reference39 articles.

1. Tsay, R.S. (2010). Analysis of Financial Time Series, John Wiley & Sons. [3rd ed.].

2. Taylor, S.J. (2008). Modelling Financial Time Series, World Scientific Publishing Co.. [2nd ed.].

3. Fractal functions and interpolation;Barnsley;Constr. Approx.,1986

4. Barnsley, M.F. (2012). Fractals Everywhere, Dover Publications. [3rd ed.].

5. Curve fitting by fractal interpolation;Manousopoulos;Trans. Comput. Sci.,2008

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