Correlation Between Solid State and Aeorema Communications
Can any of the company-specific risk be diversified away by investing in both Solid State and Aeorema Communications 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 Solid State and Aeorema Communications into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Solid State Plc and Aeorema Communications Plc, you can compare the effects of market volatilities on Solid State and Aeorema Communications 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 Solid State with a short position of Aeorema Communications. Check out your portfolio center. Please also check ongoing floating volatility patterns of Solid State and Aeorema Communications.
Diversification Opportunities for Solid State and Aeorema Communications
-0.6 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Solid and Aeorema is -0.6. Overlapping area represents the amount of risk that can be diversified away by holding Solid State Plc and Aeorema Communications Plc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aeorema Communications and Solid State 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 Solid State Plc are associated (or correlated) with Aeorema Communications. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aeorema Communications has no effect on the direction of Solid State i.e., Solid State and Aeorema Communications go up and down completely randomly.
Pair Corralation between Solid State and Aeorema Communications
Assuming the 90 days trading horizon Solid State Plc is expected to generate 1.42 times more return on investment than Aeorema Communications. However, Solid State is 1.42 times more volatile than Aeorema Communications Plc. It trades about 0.46 of its potential returns per unit of risk. Aeorema Communications Plc is currently generating about -0.51 per unit of risk. If you would invest 12,750 in Solid State Plc on October 22, 2024 and sell it today you would earn a total of 3,250 from holding Solid State Plc or generate 25.49% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Solid State Plc vs. Aeorema Communications Plc
Performance |
Timeline |
Solid State Plc |
Aeorema Communications |
Solid State and Aeorema Communications Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Solid State and Aeorema Communications
The main advantage of trading using opposite Solid State and Aeorema Communications positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Solid State position performs unexpectedly, Aeorema Communications 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 Aeorema Communications will offset losses from the drop in Aeorema Communications' long position.Solid State vs. Westlake Chemical Corp | Solid State vs. Inspiration Healthcare Group | Solid State vs. Trainline Plc | Solid State vs. PureTech Health plc |
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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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