Correlation Between Atmos Energy and Catalyst Pharmaceuticals
Can any of the company-specific risk be diversified away by investing in both Atmos Energy and Catalyst Pharmaceuticals 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 Catalyst Pharmaceuticals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Atmos Energy and Catalyst Pharmaceuticals, you can compare the effects of market volatilities on Atmos Energy and Catalyst Pharmaceuticals 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 Catalyst Pharmaceuticals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Atmos Energy and Catalyst Pharmaceuticals.
Diversification Opportunities for Atmos Energy and Catalyst Pharmaceuticals
0.57 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Atmos and Catalyst is 0.57. Overlapping area represents the amount of risk that can be diversified away by holding Atmos Energy and Catalyst Pharmaceuticals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Catalyst Pharmaceuticals 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 Catalyst Pharmaceuticals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Catalyst Pharmaceuticals has no effect on the direction of Atmos Energy i.e., Atmos Energy and Catalyst Pharmaceuticals go up and down completely randomly.
Pair Corralation between Atmos Energy and Catalyst Pharmaceuticals
Considering the 90-day investment horizon Atmos Energy is expected to generate 0.42 times more return on investment than Catalyst Pharmaceuticals. However, Atmos Energy is 2.41 times less risky than Catalyst Pharmaceuticals. It trades about -0.17 of its potential returns per unit of risk. Catalyst Pharmaceuticals is currently generating about -0.12 per unit of risk. If you would invest 14,597 in Atmos Energy on September 13, 2024 and sell it today you would lose (530.00) from holding Atmos Energy or give up 3.63% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Atmos Energy vs. Catalyst Pharmaceuticals
Performance |
Timeline |
Atmos Energy |
Catalyst Pharmaceuticals |
Atmos Energy and Catalyst Pharmaceuticals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Atmos Energy and Catalyst Pharmaceuticals
The main advantage of trading using opposite Atmos Energy and Catalyst Pharmaceuticals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Atmos Energy position performs unexpectedly, Catalyst Pharmaceuticals 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 Catalyst Pharmaceuticals will offset losses from the drop in Catalyst Pharmaceuticals' long position.Atmos Energy vs. One Gas | Atmos Energy vs. NiSource | Atmos Energy vs. Aquagold International | Atmos Energy vs. Thrivent High Yield |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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