Correlation Between Emerging Markets and Us Small
Can any of the company-specific risk be diversified away by investing in both Emerging Markets and Us Small 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 Emerging Markets and Us Small into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Emerging Markets Targeted and Us Small Cap, you can compare the effects of market volatilities on Emerging Markets and Us Small 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 Emerging Markets with a short position of Us Small. Check out your portfolio center. Please also check ongoing floating volatility patterns of Emerging Markets and Us Small.
Diversification Opportunities for Emerging Markets and Us Small
0.95 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Emerging and DFSVX is 0.95. Overlapping area represents the amount of risk that can be diversified away by holding Emerging Markets Targeted and Us Small Cap in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Us Small Cap and Emerging Markets 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 Emerging Markets Targeted are associated (or correlated) with Us Small. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Us Small Cap has no effect on the direction of Emerging Markets i.e., Emerging Markets and Us Small go up and down completely randomly.
Pair Corralation between Emerging Markets and Us Small
Assuming the 90 days horizon Emerging Markets Targeted is expected to generate 0.55 times more return on investment than Us Small. However, Emerging Markets Targeted is 1.81 times less risky than Us Small. It trades about 0.41 of its potential returns per unit of risk. Us Small Cap is currently generating about 0.22 per unit of risk. If you would invest 1,100 in Emerging Markets Targeted on April 25, 2025 and sell it today you would earn a total of 201.00 from holding Emerging Markets Targeted or generate 18.27% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Emerging Markets Targeted vs. Us Small Cap
Performance |
Timeline |
Emerging Markets Targeted |
Us Small Cap |
Emerging Markets and Us Small Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Emerging Markets and Us Small
The main advantage of trading using opposite Emerging Markets and Us Small positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Emerging Markets position performs unexpectedly, Us Small 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 Us Small will offset losses from the drop in Us Small's long position.Emerging Markets vs. T Rowe Price | Emerging Markets vs. Ab E Opportunities | Emerging Markets vs. Centerstone Investors Fund | Emerging Markets vs. Buffalo Growth Fund |
Us Small vs. Us Micro Cap | Us Small vs. Dfa International Small | Us Small vs. Us Large Cap | Us Small vs. International Small Pany |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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