Wavelet based multi-scale analysis of financial time series has attracted much attention,
lately, from both the academia and practitioners from all around the world. The unceasing …

This study presents an integrated system where wavelet transforms and recurrent neural
network (RNN) based on artificial bee colony (abc) algorithm (called ABC-RNN) are …

This paper examines the short term and long term dependencies between stock market
returns for the Gulf Cooperation Council (GCC) Countries (Bahrain, Kuwait, Oman, Qatar …

A financial market is an example of an adaptive complex network consisting of many
interacting units. This network reflects market's behavior. In this paper, we use Random …

Due to the characteristics of financial time series, such as being non-linear, non-stationary
and noisy, with uncertain and hidden relationships, it is difficult to capture its non-stationary …

The main aim of the present paper is to explore how the interactions between crude oil (CO)
price changes and stock returns of five developed countries namely USA, Canada …

We use a new method of studying the Hurst exponent with time and scale dependency. This
new approach allows us to recover the major events affecting worldwide markets (such as …

This paper investigates the contagion effect among stock markets (Asia, European and
America) under time varying frequencies by use of a CEEMDAN wavelet (complete …

The proprietary nature of Hedge Fund investing means that it is common practise for
managers to release minimal information about their returns. The construction of a fund of …

In the last decade, many factors, such as socio-political and econo-environmental ones,
have led to a perturbation in the timeline of the worldwide development, and especially in …