Long memory in select stock returns using an alternative wavelet log-scale alignment approach

2020/04/18 by Bhandari, Avishek, Kamaiah, Bandi
#65T60 #81Q35 #Chaotic Dynamics (nlin.CD) #Dynamical Systems (math.DS) #FOS: Economics and business #FOS: Electrical engineering #FOS: Mathematics #FOS: Physical sciences #I.5 #Signal Processing (eess.SP) #Statistical Finance (q-fin.ST) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2004.08550

Abstract

This study investigates the efficiency of some select stock markets. Using an improved wavelet estimator of long range dependence, we show evidence of long memory in the stock returns of some emerging Asian economies. However, developed markets of Europe and the United States did not exhibit long memory thereby confirming the efficiency of developed stock markets. On the other hand, emerging Asian markets are found to be less efficient as long memory is more pronounced in these markets.

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