G7 Stock Markets: Who is The First to Defeat The DCCA Correlation?

Following the methodology of Ferreira and Dionísio (2016), the objective of this paper is to analyze the behavior stock markets in the G7 countries and find which of those countries is the first to reach levels of long-range correlations that are not significant. We carry out this analysis using detrended cross-correlation analysis and its correlation coefficient, to check for the existence of long-range dependence in time series. The existence of long-range dependence could be understood as a possibility of EMH violation. This analysis remains interesting because studies are not conclusive about the existence or not of long memory in stock return rates.

Why does the Euro fail? The DCCA approach

The present crisis in the Euro is one of the most serious crises reported in history. The fact that different countries that adopted the Euro have different conditions to support asymmetric shocks in their economies could explain some of the consequences currently affecting the Eurozone. In this paper we apply detrended cross-correlation analysis and its cross correlation coefficient to evaluate the degree of financial integration of the first set of countries to adopt the common currency. Since time series used in these studies are known to be non-stationary, DCCA is suited to study it. It is the first time this methodology has been applied to study financial integration. We conclude that the degree of financial integration is unequal in several countries using the common currency. The fact that countries like Greece, Ireland or Portugal are the ones facing most problems in verification of the parity used in this paper could help to explain the present instability in the Eurozone.

How long is the memory of the US stock market?

The Efficient Market Hypothesis (EMH), one of the most important hypothesis in financial economics, argues that return rates have no memory (correlation) which implies that agents cannot make abnormal profits in financial markets, due to the possibility of arbitrage operations. With return rates for the US stock market, we corroborate the fact that with a linear approach, return rates do not show evidence of correlation. However, linear approaches might not be complete or global, since return rates could suffer from nonlinearities. Using detrended cross-correlation analysis and its correlation coefficient, a methodology which analyzes long-range behavior between series, we show that the long-range correlation of return rates only ends in the 149th lag, which corresponds to about seven months. Does this result undermine the EMH?