Correlation Between Blrc Sgy and Federated Emerging
Can any of the company-specific risk be diversified away by investing in both Blrc Sgy and Federated 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 Blrc Sgy and Federated Emerging into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Blrc Sgy Mnp and Federated Emerging Market, you can compare the effects of market volatilities on Blrc Sgy and Federated 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 Blrc Sgy with a short position of Federated Emerging. Check out your portfolio center. Please also check ongoing floating volatility patterns of Blrc Sgy and Federated Emerging.
Diversification Opportunities for Blrc Sgy and Federated Emerging
0.86 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Blrc and Federated is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding Blrc Sgy Mnp and Federated Emerging Market in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated Emerging Market and Blrc Sgy 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 Blrc Sgy Mnp are associated (or correlated) with Federated Emerging. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated Emerging Market has no effect on the direction of Blrc Sgy i.e., Blrc Sgy and Federated Emerging go up and down completely randomly.
Pair Corralation between Blrc Sgy and Federated Emerging
Assuming the 90 days horizon Blrc Sgy is expected to generate 3.33 times less return on investment than Federated Emerging. But when comparing it to its historical volatility, Blrc Sgy Mnp is 1.36 times less risky than Federated Emerging. It trades about 0.04 of its potential returns per unit of risk. Federated Emerging Market is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 662.00 in Federated Emerging Market on October 22, 2024 and sell it today you would earn a total of 117.00 from holding Federated Emerging Market or generate 17.67% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Blrc Sgy Mnp vs. Federated Emerging Market
Performance |
Timeline |
Blrc Sgy Mnp |
Federated Emerging Market |
Blrc Sgy and Federated Emerging Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Blrc Sgy and Federated Emerging
The main advantage of trading using opposite Blrc Sgy and Federated Emerging positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Blrc Sgy position performs unexpectedly, Federated 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 Federated Emerging will offset losses from the drop in Federated Emerging's long position.Blrc Sgy vs. Icon Information Technology | Blrc Sgy vs. Pgim Jennison Technology | Blrc Sgy vs. Technology Ultrasector Profund | Blrc Sgy vs. Vanguard Information Technology |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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