Correlation Between Federal National and Orca Energy
Can any of the company-specific risk be diversified away by investing in both Federal National and Orca 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 Federal National and Orca Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Federal National Mortgage and Orca Energy Group, you can compare the effects of market volatilities on Federal National and Orca 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 Federal National with a short position of Orca Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Federal National and Orca Energy.
Diversification Opportunities for Federal National and Orca Energy
-0.77 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Federal and Orca is -0.77. Overlapping area represents the amount of risk that can be diversified away by holding Federal National Mortgage and Orca Energy Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Orca Energy Group and Federal National 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 Federal National Mortgage are associated (or correlated) with Orca Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Orca Energy Group has no effect on the direction of Federal National i.e., Federal National and Orca Energy go up and down completely randomly.
Pair Corralation between Federal National and Orca Energy
Assuming the 90 days horizon Federal National Mortgage is expected to generate 7.67 times more return on investment than Orca Energy. However, Federal National is 7.67 times more volatile than Orca Energy Group. It trades about 0.23 of its potential returns per unit of risk. Orca Energy Group is currently generating about 0.01 per unit of risk. If you would invest 1,599,500 in Federal National Mortgage on September 1, 2024 and sell it today you would earn a total of 1,700,500 from holding Federal National Mortgage or generate 106.31% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Federal National Mortgage vs. Orca Energy Group
Performance |
| Timeline |
| Federal National Mortgage |
| Orca Energy Group |
Federal National and Orca Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Federal National and Orca Energy
The main advantage of trading using opposite Federal National and Orca Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Federal National position performs unexpectedly, Orca 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 Orca Energy will offset losses from the drop in Orca Energy's long position.| Federal National vs. Federal Home Loan | Federal National vs. Federal Home Loan | Federal National vs. Federal Home Loan | Federal National vs. Federal Home Loan |
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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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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