Correlation Between Atmos Energy and NiSource
Can any of the company-specific risk be diversified away by investing in both Atmos Energy and NiSource 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 Atmos Energy and NiSource into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Atmos Energy and NiSource, you can compare the effects of market volatilities on Atmos Energy and NiSource 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 Atmos Energy with a short position of NiSource. Check out your portfolio center. Please also check ongoing floating volatility patterns of Atmos Energy and NiSource.
Diversification Opportunities for Atmos Energy and NiSource
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Atmos and NiSource is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding Atmos Energy and NiSource in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on NiSource and Atmos 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 Atmos Energy are associated (or correlated) with NiSource. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of NiSource has no effect on the direction of Atmos Energy i.e., Atmos Energy and NiSource go up and down completely randomly.
Pair Corralation between Atmos Energy and NiSource
Considering the 90-day investment horizon Atmos Energy is expected to under-perform the NiSource. In addition to that, Atmos Energy is 1.06 times more volatile than NiSource. It trades about -0.04 of its total potential returns per unit of risk. NiSource is currently generating about 0.1 per unit of volatility. If you would invest 2,748 in NiSource on January 29, 2024 and sell it today you would earn a total of 46.00 from holding NiSource or generate 1.67% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Atmos Energy vs. NiSource
Performance |
Timeline |
Atmos Energy |
NiSource |
Atmos Energy and NiSource Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Atmos Energy and NiSource
The main advantage of trading using opposite Atmos Energy and NiSource positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Atmos Energy position performs unexpectedly, NiSource 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 NiSource will offset losses from the drop in NiSource's long position.The idea behind Atmos Energy and NiSource pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.NiSource vs. NorthWestern | NiSource vs. Avista | NiSource vs. Otter Tail | NiSource vs. Companhia Paranaense de |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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