Long Memory and Correlation Structures of Select Stock Returns Using Novel Wavelet and Fractal Connectivity Networks

This study investigates the long range dependence and correlation structures of some select stock markets. Using novel wavelet methods of long range dependence, we show presence of long memory in the stock returns of some emerging economies and the lack of it in developed markets of Europe and the United States. Moreover, we conduct a wavelet based fractal connectivity analysis, which is the first application in economics and financial studies, to segregate markets into fractally similar 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.