Correlation Between Central Europe and Aberdeen Income
Can any of the company-specific risk be diversified away by investing in both Central Europe and Aberdeen Income 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 Central Europe and Aberdeen Income into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Central Europe Russia and Aberdeen Income Credit, you can compare the effects of market volatilities on Central Europe and Aberdeen Income 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 Central Europe with a short position of Aberdeen Income. Check out your portfolio center. Please also check ongoing floating volatility patterns of Central Europe and Aberdeen Income.
Diversification Opportunities for Central Europe and Aberdeen Income
-0.14 | Correlation Coefficient |
Good diversification
The 3 months correlation between Central and Aberdeen is -0.14. Overlapping area represents the amount of risk that can be diversified away by holding Central Europe Russia and Aberdeen Income Credit in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aberdeen Income Credit and Central Europe 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 Central Europe Russia are associated (or correlated) with Aberdeen Income. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aberdeen Income Credit has no effect on the direction of Central Europe i.e., Central Europe and Aberdeen Income go up and down completely randomly.
Pair Corralation between Central Europe and Aberdeen Income
Considering the 90-day investment horizon Central Europe Russia is expected to generate 3.56 times more return on investment than Aberdeen Income. However, Central Europe is 3.56 times more volatile than Aberdeen Income Credit. It trades about 0.18 of its potential returns per unit of risk. Aberdeen Income Credit is currently generating about 0.43 per unit of risk. If you would invest 1,113 in Central Europe Russia on October 20, 2024 and sell it today you would earn a total of 94.00 from holding Central Europe Russia or generate 8.45% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Central Europe Russia vs. Aberdeen Income Credit
Performance |
| Timeline |
| Central Europe Russia |
| Aberdeen Income Credit |
Central Europe and Aberdeen Income Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Central Europe and Aberdeen Income
The main advantage of trading using opposite Central Europe and Aberdeen Income positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Central Europe position performs unexpectedly, Aberdeen Income 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 Aberdeen Income will offset losses from the drop in Aberdeen Income's long position.| Central Europe vs. Mexico Closed | Central Europe vs. NXG NextGen Infrastructure | Central Europe vs. Taiwan Closed | Central Europe vs. Japan Smaller Capitalization |
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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