Global Correlations Part 1

I downloaded MSCI regional monthly returns for North America, Europe, BRIC countries, Asia, and Latin America from January 2001 to October 2017.   Figure 1 displays statistics for the five regions over 202 months.

Figure 1

	N_AMERICA	EUROPE	BRIC	ASIA	EM_LATIN_AMERICA
Mean	0.439	0.355	0.827	0.417	0.825
Median	1.089	0.529	1.250	0.976	1.341
Maximum	11.624	13.053	17.279	12.955	16.919
Minimum	-24.268	-23.882	-39.573	-22.623	-42.882
Std. Dev.	3.873	5.452	6.649	4.410	6.920
Skewness	-1.796	-0.796	-1.295	-0.888	-1.461
Kurtosis	11.180	4.897	9.013	6.265	9.893
Jarque-Bera	671.6936	51.62247	360.7243	116.2527	471.798
Probability	0	0	0	0	0
Observations	202	202	202	202	202

 

Source: MSCI & GLP Risk Management, Inc.

 

One interesting point is that the Jarque-Bera statistic indicates that none of the returns may be considered normally distributed.    This can be seen in figure 2, a distribution chart, of Asia compared to a normal distribution.

The blue line is a distribution of the data using a kernel density.  The red line is a normal distribution based on the mean and standard deviation of the data.  The historical data shows a much higher kurtosis than the normal (more mass in the center of the distribution).

Figure 2

Correlations

Correlations over the entire period are shown in figure 3.

Figure 3

	N_AMERICA	EUROPE	BRIC	ASIA	LATIN_AMERICA
N_AMERICA	1.000	0.677	0.772	0.793	0.765
EUROPE	0.677	1.000	0.625	0.590	0.603
BRIC	0.772	0.625	1.000	0.859	0.933
ASIA	0.793	0.590	0.859	1.000	0.786
LATIN_AMERICA	0.765	0.603	0.933	0.786	1.000

 

Correlations in 2008 were higher and are shown in figure 4.

Figure 4

		N_AMERICA	EUROPE	BRIC	AC_ASIA	LATIN_AMERICA
	N_AMERICA	1.000	0.826	0.922	0.938	0.926
	EUROPE	0.826	1.000	0.896	0.891	0.884
	BRIC	0.922	0.896	1.000	0.982	0.966
	AC_ASIA	0.938	0.891	0.982	1.000	0.945
	LATIN_AMERICA	0.926	0.884	0.966	0.945	1.000

 

It can be difficult to identify higher or lower correlations in a table.  I averaged the correlations for several periods and these can be seen in figure 5.

Figure 5

For many years the investment community believed that correlations were constant.  The chart and tables above confirm that in times of financial stress (2008) correlations across the board increase.  Just when an investor needs diversification, it disappears. The final figure in this short piece shows that on a rolling 36 month basis correlations do indeed change.

Figure 6

From December 2003, to October 2017, the rolling 36 month correlation between North America and Europe varied between 0.22 and .85.  The average correlation for the entire seventeen year period (almost) was 0.64.  In 20015, the correlation was at its lowest point well below two standard deviations from the mean.  It was approximately 3.75 standard deviations below the mean!

There are several conclusions from this short analysis:

• Correlations are not constant. They can and do change often in a significant manner.  This has important implications for portfolio optimization.
• While it is useful to know past correlations, they contain little or no information useful to forecast future correlations. Just like investors know that past returns contain no information about future returns, past correlations contain no information about future correlations.
• And remember investors care about future correlations.