Correlation Between UnitedHealth Group and Fobi AI
Can any of the company-specific risk be diversified away by investing in both UnitedHealth Group and Fobi AI 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 UnitedHealth Group and Fobi AI into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between UnitedHealth Group CDR and Fobi AI, you can compare the effects of market volatilities on UnitedHealth Group and Fobi AI 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 UnitedHealth Group with a short position of Fobi AI. Check out your portfolio center. Please also check ongoing floating volatility patterns of UnitedHealth Group and Fobi AI.
Diversification Opportunities for UnitedHealth Group and Fobi AI
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between UnitedHealth and Fobi is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding UnitedHealth Group CDR and Fobi AI in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fobi AI and UnitedHealth Group 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 UnitedHealth Group CDR are associated (or correlated) with Fobi AI. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fobi AI has no effect on the direction of UnitedHealth Group i.e., UnitedHealth Group and Fobi AI go up and down completely randomly.
Pair Corralation between UnitedHealth Group and Fobi AI
Assuming the 90 days trading horizon UnitedHealth Group CDR is expected to generate 0.27 times more return on investment than Fobi AI. However, UnitedHealth Group CDR is 3.76 times less risky than Fobi AI. It trades about 0.0 of its potential returns per unit of risk. Fobi AI is currently generating about -0.05 per unit of risk. If you would invest 2,536 in UnitedHealth Group CDR on September 14, 2024 and sell it today you would lose (76.00) from holding UnitedHealth Group CDR or give up 3.0% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
UnitedHealth Group CDR vs. Fobi AI
Performance |
| Timeline |
| UnitedHealth Group CDR |
| Fobi AI |
UnitedHealth Group and Fobi AI Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with UnitedHealth Group and Fobi AI
The main advantage of trading using opposite UnitedHealth Group and Fobi AI positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if UnitedHealth Group position performs unexpectedly, Fobi AI 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 Fobi AI will offset losses from the drop in Fobi AI's long position.| UnitedHealth Group vs. MTY Food Group | UnitedHealth Group vs. Altair Resources | UnitedHealth Group vs. VIP Entertainment Technologies | UnitedHealth Group vs. NeXGold Mining Corp |
| Fobi AI vs. Walmart Inc CDR | Fobi AI vs. Amazon CDR | Fobi AI vs. Berkshire Hathaway CDR | Fobi AI vs. UnitedHealth Group CDR |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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