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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12813

Title: Time-frequency coherence and forecast analysis of selected stock returns in Ghana using haar wavelet
Authors: Eghan, Rhydal Esi
Amoako-Yirenkyi, Peter
Omari-Sasu, Akoto Yaw
Frimpong, Nana Kena
Keywords: Co-movement
stock returns
wavelet coherence
Issue Date: 14-Feb-2019
Publisher: Journal of Advances in Mathematics and Computer Science
Abstract: Aims/ objectives: The study seeks to analyze the correlation of some selected stock returns with respect to both time and frequency domain, and also to forecast returns using Wavelet Coherence and Wavelet-ARIMA model as alternative to Pearson correlation and ARIMA model respectively. Study Design: Financial Mathematics. Place and Duration of Study: August 2016 to July 2017 , Department of Mathematics, Kwame Nkrumah University of Science and Technology. Methodology: We transform data using the Haar Wavelet as the basis function. Results: Results revealed interesting dynamics of correlations altering in time and across frequencies continually between paired returns. Furthermore, Wavelet-Arima method was found to be more appropriate for forecast with minimal error measure of forecast values. Conclusion: Given the heterogeneous trading behavior in stock markets, investors operate at di erent frequencies for their trade and investment preferences. Thus, apart from the time domain, there is a frequency domain, which represents various investment horizons.
Description: An article published by Journal of Advances in Mathematics and Computer Science and also available at DOI: 10.9734/JAMCS/2019/46323
URI: http://hdl.handle.net/123456789/12813
Appears in Collections:College of Science

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