Detecting the Fluctuations in Large Samples Using Wavelet Transform

Autor:	Ghassan Obeidat, S. Al Wadi
Rok vydání:	2018
Předmět:	Discrete wavelet transform Multidisciplinary Wavelet business.industry Computer science 020209 energy 0202 electrical engineering electronic engineering information engineering Wavelet transform Stock market Pattern recognition 02 engineering and technology Artificial intelligence business
Zdroj:	Modern Applied Science. 12:245
ISSN:	1913-1852 1913-1844
DOI:	10.5539/mas.v12n12p245
Popis:	structure break is a famous features in stock market data that gain consideration from many kind of researchers. Generally, it occurs because of unexpected variations in the strategy of the government. Recently, wavelet method (WT) is more popular in the stock market data analysis since it has significant benefits than the other traditional methods. In this research paper, the discrete wavelet transform (DWT) based on Daubechies model will be used to capture the structure break in Amman stocks market /Jordan (ASE) using dataset from 2010 until 2018.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8c752c42917c9513d3e7c6b197ce89ed https://doi.org/10.5539/mas.v12n12p245 Zobrazit plný text záznamu