Correlation Between East Africa and Office Properties
Can any of the company-specific risk be diversified away by investing in both East Africa and Office Properties 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 East Africa and Office Properties into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between East Africa Metals and Office Properties Income, you can compare the effects of market volatilities on East Africa and Office Properties 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 East Africa with a short position of Office Properties. Check out your portfolio center. Please also check ongoing floating volatility patterns of East Africa and Office Properties.
Diversification Opportunities for East Africa and Office Properties
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between East and Office is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding East Africa Metals and Office Properties Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Office Properties Income and East Africa 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 East Africa Metals are associated (or correlated) with Office Properties. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Office Properties Income has no effect on the direction of East Africa i.e., East Africa and Office Properties go up and down completely randomly.
Pair Corralation between East Africa and Office Properties
Assuming the 90 days horizon East Africa Metals is expected to generate 29.26 times more return on investment than Office Properties. However, East Africa is 29.26 times more volatile than Office Properties Income. It trades about 0.09 of its potential returns per unit of risk. Office Properties Income is currently generating about -0.01 per unit of risk. If you would invest 9.15 in East Africa Metals on October 11, 2024 and sell it today you would earn a total of 1.85 from holding East Africa Metals or generate 20.22% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 99.6% |
Values | Daily Returns |
East Africa Metals vs. Office Properties Income
Performance |
Timeline |
East Africa Metals |
Office Properties Income |
East Africa and Office Properties Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with East Africa and Office Properties
The main advantage of trading using opposite East Africa and Office Properties positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if East Africa position performs unexpectedly, Office Properties 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 Office Properties will offset losses from the drop in Office Properties' long position.East Africa vs. Pasinex Resources Limited | East Africa vs. Commander Resources | East Africa vs. Forsys Metals Corp | East Africa vs. American CuMo Mining |
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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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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