Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/5026
Title: Fractal Connectivity Networks of Select Stock Returns Exhibiting Long Range Dependence
Authors: Assaf, Ata 
Affiliations: Faculty of Business and Management 
Co-authors: Avishek Bandhari
Rajendra N. Paramanik
Keywords: Long memory
Fractal connectivity
Wavelets
Hurst
Complex networks
Issue Date: 2021
Conference: Virtual Conference on International Macroeconomics and Finance. ( 27th of March, 2021 - Kerala, India)
Abstract: 
Despite several attempts in applied econometrics and time series literature to identify the common channels contributing to fractal structures and long memory in multivariate financial time series, we propose a wavelet-based fractal connectivity analysis, which is the first application in economics and financial studies, enabling one to successfully segregate markets into fractally similar or diverse groups and find that developed markets have similar fractal structures. Similarly, stock returns of emerging markets exhibiting long-memory tend to follow similar fractal structures. Furthermore, network analyses of fractal connectivity support our findings on market efficiency which has theoretical roots in both fractal and adaptive market hypothesis.
URI: https://scholarhub.balamand.edu.lb/handle/uob/5026
Type: Conference Presentation
Appears in Collections:Department of Business Administration

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