Correlation Between United Utilities and Regions Financial
Can any of the company-specific risk be diversified away by investing in both United Utilities and Regions Financial 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 United Utilities and Regions Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between United Utilities Group and Regions Financial, you can compare the effects of market volatilities on United Utilities and Regions Financial 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 United Utilities with a short position of Regions Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of United Utilities and Regions Financial.
Diversification Opportunities for United Utilities and Regions Financial
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between United and Regions is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding United Utilities Group and Regions Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Regions Financial and United Utilities 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 United Utilities Group are associated (or correlated) with Regions Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Regions Financial has no effect on the direction of United Utilities i.e., United Utilities and Regions Financial go up and down completely randomly.
Pair Corralation between United Utilities and Regions Financial
Assuming the 90 days trading horizon United Utilities Group is expected to generate 0.74 times more return on investment than Regions Financial. However, United Utilities Group is 1.35 times less risky than Regions Financial. It trades about -0.31 of its potential returns per unit of risk. Regions Financial is currently generating about -0.36 per unit of risk. If you would invest 1,362 in United Utilities Group on September 26, 2024 and sell it today you would lose (102.00) from holding United Utilities Group or give up 7.49% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
United Utilities Group vs. Regions Financial
Performance |
Timeline |
United Utilities |
Regions Financial |
United Utilities and Regions Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with United Utilities and Regions Financial
The main advantage of trading using opposite United Utilities and Regions Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if United Utilities position performs unexpectedly, Regions Financial 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 Regions Financial will offset losses from the drop in Regions Financial's long position.United Utilities vs. American Water Works | United Utilities vs. Aqua America | United Utilities vs. Companhia de Saneamento | United Utilities vs. Guangdong Investment Limited |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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