Extreme returns in stock returns need to be captured for a successful risk management function to estimate unexpected loss in portfolio. Traditional value-at-risk models based on parametric models are not able to capture the extremes in emerging markets where high volatility and nonlinear...

Purpose – The purpose of this paper is to use filtered extreme-value theory (EVT) model to forecast one of the main emerging market stock returns and compare the predictive performance of this model with other conditional volatility models. Design/methodology/approach – This paper employs...

In this paper, we investigate the relationship between industrial production and sectoral credit defaults (non-performing loans ratio) cycle by wavelet network analysis in Turkey over the period January 2001-November 2007. We use feedforward neural network based wavelet decomposition to analyze...

This paper examines the impacts of changes in interest rates on stock returns by using wavelet analysis with Granger causality test. Financial time series in non-coherent markets should be analyzed by advanced methods capturing complexity of the markets and non-linearities in stock returns. As a...

In this study, variance changing to the scale and multi-scale Capital Asset Pricing Model (CAPM) is tested by Wavelets as a new analysis method in finance and economics. It introduces a new approach to the variance changing to the scale as a general risk indicator, and to multi-scale CAPM...

Tests results for causality between energy consumption and economic growth do not have a consensus in the financial economics literature. Empirical evidence varies on the economies examined and methodology employed. This paper proposes a wavelet analysis as a semi- parametric model for detecting...