 Since underlying data sets are affected by non-stationarities  , we also applied MF-DFA and MF-DXA in order to examine the multifractality nature of data and to analyze the relationship and mutual interaction between pairs of series, respectively. The overall results are quite interesting, since we found only 170 pair of stock markets cointegrated, and according to the Granger causality and mutual information we realized that the strongest relations lies between emerging markets, and between emerging and frontier markets.
<coherence>  Since underlying data sets are affected by non-stationarities  , we also applied MF-DFA and MF-DXA in order to examine the multifractality nature of data and to analyze the relationship and mutual interaction between pairs of series, respectively. The overall results are quite interesting, since we found only 170 pair of stock markets cointegrated, and according to the Granger causality and mutual information we realized that the strongest relations lies between emerging markets, and between emerging and frontier markets.
 Since underlying data sets are affected by non-stationarities , we also apply AMF-DFA and AMF-DXA. We find only 170 pair of stock markets cointegrated, and according to the Granger causality and mutual information we realized that the strongest relations lies between emerging markets, and between emerging and frontier markets.