Correlation Between Digi International and Atmos Energy
Can any of the company-specific risk be diversified away by investing in both Digi International and Atmos Energy 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 Digi International and Atmos Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Digi International and Atmos Energy, you can compare the effects of market volatilities on Digi International and Atmos Energy 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 Digi International with a short position of Atmos Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Digi International and Atmos Energy.
Diversification Opportunities for Digi International and Atmos Energy
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Digi and Atmos is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Digi International and Atmos Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Atmos Energy and Digi International 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 Digi International are associated (or correlated) with Atmos Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Atmos Energy has no effect on the direction of Digi International i.e., Digi International and Atmos Energy go up and down completely randomly.
Pair Corralation between Digi International and Atmos Energy
Given the investment horizon of 90 days Digi International is expected to generate 3.08 times less return on investment than Atmos Energy. In addition to that, Digi International is 2.47 times more volatile than Atmos Energy. It trades about 0.01 of its total potential returns per unit of risk. Atmos Energy is currently generating about 0.05 per unit of volatility. If you would invest 10,919 in Atmos Energy on September 18, 2024 and sell it today you would earn a total of 3,103 from holding Atmos Energy or generate 28.42% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Digi International vs. Atmos Energy
Performance |
Timeline |
Digi International |
Atmos Energy |
Digi International and Atmos Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Digi International and Atmos Energy
The main advantage of trading using opposite Digi International and Atmos Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Digi International position performs unexpectedly, Atmos Energy 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 Atmos Energy will offset losses from the drop in Atmos Energy's long position.Digi International vs. Extreme Networks | Digi International vs. Ciena Corp | Digi International vs. Harmonic | Digi International vs. Comtech Telecommunications Corp |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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