Correlation Between Singapore Airlines and Metro AG
Can any of the company-specific risk be diversified away by investing in both Singapore Airlines and Metro AG 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 Singapore Airlines and Metro AG into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Singapore Airlines Limited and Metro AG, you can compare the effects of market volatilities on Singapore Airlines and Metro AG 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 Singapore Airlines with a short position of Metro AG. Check out your portfolio center. Please also check ongoing floating volatility patterns of Singapore Airlines and Metro AG.
Diversification Opportunities for Singapore Airlines and Metro AG
0.17 | Correlation Coefficient |
Average diversification
The 3 months correlation between Singapore and Metro is 0.17. Overlapping area represents the amount of risk that can be diversified away by holding Singapore Airlines Limited and Metro AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Metro AG and Singapore Airlines 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 Singapore Airlines Limited are associated (or correlated) with Metro AG. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Metro AG has no effect on the direction of Singapore Airlines i.e., Singapore Airlines and Metro AG go up and down completely randomly.
Pair Corralation between Singapore Airlines and Metro AG
Assuming the 90 days trading horizon Singapore Airlines Limited is expected to generate 0.26 times more return on investment than Metro AG. However, Singapore Airlines Limited is 3.91 times less risky than Metro AG. It trades about 0.08 of its potential returns per unit of risk. Metro AG is currently generating about -0.21 per unit of risk. If you would invest 441.00 in Singapore Airlines Limited on September 24, 2024 and sell it today you would earn a total of 4.00 from holding Singapore Airlines Limited or generate 0.91% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Singapore Airlines Limited vs. Metro AG
Performance |
| Timeline |
| Singapore Airlines |
| Metro AG |
Singapore Airlines and Metro AG Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Singapore Airlines and Metro AG
The main advantage of trading using opposite Singapore Airlines and Metro AG positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Singapore Airlines position performs unexpectedly, Metro AG 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 Metro AG will offset losses from the drop in Metro AG's long position.| Singapore Airlines vs. EAT WELL INVESTMENT | Singapore Airlines vs. Strategic Investments AS | Singapore Airlines vs. ECHO INVESTMENT ZY | Singapore Airlines vs. United Airlines Holdings |
| Metro AG vs. Singapore Airlines Limited | Metro AG vs. Texas Roadhouse | Metro AG vs. SINGAPORE AIRLINES | Metro AG vs. EVS Broadcast Equipment |
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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