Correlation Between Calvert Emerging and Siit Emerging
Can any of the company-specific risk be diversified away by investing in both Calvert Emerging and Siit Emerging at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Calvert Emerging and Siit Emerging into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Calvert Emerging Markets and Siit Emerging Markets, you can compare the effects of market volatilities on Calvert Emerging and Siit Emerging and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Calvert Emerging with a short position of Siit Emerging. Check out your portfolio center. Please also check ongoing floating volatility patterns of Calvert Emerging and Siit Emerging.
Diversification Opportunities for Calvert Emerging and Siit Emerging
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between Calvert and Siit is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding Calvert Emerging Markets and Siit Emerging Markets in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Siit Emerging Markets and Calvert Emerging is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Calvert Emerging Markets are associated (or correlated) with Siit Emerging. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Siit Emerging Markets has no effect on the direction of Calvert Emerging i.e., Calvert Emerging and Siit Emerging go up and down completely randomly.
Pair Corralation between Calvert Emerging and Siit Emerging
Assuming the 90 days horizon Calvert Emerging is expected to generate 3.23 times less return on investment than Siit Emerging. In addition to that, Calvert Emerging is 3.19 times more volatile than Siit Emerging Markets. It trades about 0.04 of its total potential returns per unit of risk. Siit Emerging Markets is currently generating about 0.42 per unit of volatility. If you would invest 854.00 in Siit Emerging Markets on May 12, 2025 and sell it today you would earn a total of 53.00 from holding Siit Emerging Markets or generate 6.21% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Calvert Emerging Markets vs. Siit Emerging Markets
Performance |
Timeline |
Calvert Emerging Markets |
Siit Emerging Markets |
Calvert Emerging and Siit Emerging Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Calvert Emerging and Siit Emerging
The main advantage of trading using opposite Calvert Emerging and Siit Emerging positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Calvert Emerging position performs unexpectedly, Siit Emerging can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Siit Emerging will offset losses from the drop in Siit Emerging's long position.Calvert Emerging vs. Perkins Small Cap | Calvert Emerging vs. Ultrasmall Cap Profund Ultrasmall Cap | Calvert Emerging vs. Mutual Of America | Calvert Emerging vs. Northern Small Cap |
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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