Correlation Between Steel Dynamics and Deutsche Telekom
Can any of the company-specific risk be diversified away by investing in both Steel Dynamics and Deutsche Telekom 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 Steel Dynamics and Deutsche Telekom into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Steel Dynamics and Deutsche Telekom AG, you can compare the effects of market volatilities on Steel Dynamics and Deutsche Telekom 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 Steel Dynamics with a short position of Deutsche Telekom. Check out your portfolio center. Please also check ongoing floating volatility patterns of Steel Dynamics and Deutsche Telekom.
Diversification Opportunities for Steel Dynamics and Deutsche Telekom
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Steel and Deutsche is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding Steel Dynamics and Deutsche Telekom AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Deutsche Telekom and Steel Dynamics 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 Steel Dynamics are associated (or correlated) with Deutsche Telekom. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Deutsche Telekom has no effect on the direction of Steel Dynamics i.e., Steel Dynamics and Deutsche Telekom go up and down completely randomly.
Pair Corralation between Steel Dynamics and Deutsche Telekom
Assuming the 90 days horizon Steel Dynamics is expected to generate 2.03 times less return on investment than Deutsche Telekom. In addition to that, Steel Dynamics is 1.46 times more volatile than Deutsche Telekom AG. It trades about 0.06 of its total potential returns per unit of risk. Deutsche Telekom AG is currently generating about 0.18 per unit of volatility. If you would invest 2,889 in Deutsche Telekom AG on December 30, 2024 and sell it today you would earn a total of 524.00 from holding Deutsche Telekom AG or generate 18.14% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Steel Dynamics vs. Deutsche Telekom AG
Performance |
Timeline |
Steel Dynamics |
Deutsche Telekom |
Steel Dynamics and Deutsche Telekom Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Steel Dynamics and Deutsche Telekom
The main advantage of trading using opposite Steel Dynamics and Deutsche Telekom positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Steel Dynamics position performs unexpectedly, Deutsche Telekom 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 Deutsche Telekom will offset losses from the drop in Deutsche Telekom's long position.Steel Dynamics vs. ADRIATIC METALS LS 013355 | Steel Dynamics vs. Tower Semiconductor | Steel Dynamics vs. Lattice Semiconductor | Steel Dynamics vs. CHINA TONTINE WINES |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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