Publication detail

Wavelet Analysis for Stock Market Forcasting

JANKOVÁ, Z.

Original Title

Wavelet Analysis for Stock Market Forcasting

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper deals with wavelet analysis and its application on the stock market. The time series of financial and economic data are usually non-linear and non-stationary. It has been shown that using decomposition models improves the prediction accuracy of these time series. These techniques include wavelet analysis, which decomposes data not only in the time domain but also in the frequency domain, and can predict non-periodic or non-stationary time series more accurately than Fourier transform. Given the decomposition of the time series using wavelet analysis, and last but not least attention is drawn to the advantages and disadvantages resulting from the use of the method in the financial markets.

Keywords

forecasting method; stock market; wavelet analysis; wavelet decomposition; wavelet transform

Authors

JANKOVÁ, Z.

Released

28. 6. 2019

Publisher

Magnanimitas

Location

Hradec Králové, Czech Republic

ISBN

978-80-87952-30-6

Book

Interdisciplinární mezinárodní vědecká konference doktorandů a odborných asistentů QUAERE 2019

Edition number

9

Pages from

149

Pages to

153

Pages count

1229

BibTex

@inproceedings{BUT157717,
  author="Zuzana {Janková}",
  title="Wavelet Analysis for Stock Market Forcasting",
  booktitle="Interdisciplinární mezinárodní vědecká konference doktorandů a odborných asistentů QUAERE 2019",
  year="2019",
  number="9",
  pages="149--153",
  publisher="Magnanimitas",
  address="Hradec Králové, Czech Republic",
  isbn="978-80-87952-30-6"
}