Correlation Between Siemens Energy and GE Aerospace
Can any of the company-specific risk be diversified away by investing in both Siemens Energy and GE Aerospace 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 Siemens Energy and GE Aerospace into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Siemens Energy AG and GE Aerospace, you can compare the effects of market volatilities on Siemens Energy and GE Aerospace 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 Siemens Energy with a short position of GE Aerospace. Check out your portfolio center. Please also check ongoing floating volatility patterns of Siemens Energy and GE Aerospace.
Diversification Opportunities for Siemens Energy and GE Aerospace
0.36 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Siemens and GE Aerospace is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding Siemens Energy AG and GE Aerospace in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GE Aerospace and Siemens Energy 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 Siemens Energy AG are associated (or correlated) with GE Aerospace. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GE Aerospace has no effect on the direction of Siemens Energy i.e., Siemens Energy and GE Aerospace go up and down completely randomly.
Pair Corralation between Siemens Energy and GE Aerospace
Assuming the 90 days horizon Siemens Energy AG is expected to generate 1.51 times more return on investment than GE Aerospace. However, Siemens Energy is 1.51 times more volatile than GE Aerospace. It trades about 0.56 of its potential returns per unit of risk. GE Aerospace is currently generating about 0.19 per unit of risk. If you would invest 4,083 in Siemens Energy AG on September 1, 2024 and sell it today you would earn a total of 1,317 from holding Siemens Energy AG or generate 32.26% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 95.45% |
| Values | Daily Returns |
Siemens Energy AG vs. GE Aerospace
Performance |
| Timeline |
| Siemens Energy AG |
| GE Aerospace |
Siemens Energy and GE Aerospace Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Siemens Energy and GE Aerospace
The main advantage of trading using opposite Siemens Energy and GE Aerospace positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Siemens Energy position performs unexpectedly, GE Aerospace 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 GE Aerospace will offset losses from the drop in GE Aerospace's long position.| Siemens Energy vs. SPX Corp | Siemens Energy vs. Nuscale Power Corp | Siemens Energy vs. Vestas Wind Systems | Siemens Energy vs. Nordex SE |
| GE Aerospace vs. Illinois Tool Works | GE Aerospace vs. Dover | GE Aerospace vs. Cummins | GE Aerospace vs. Eaton PLC |
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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