Correlation Between Federal Agricultural and USU Software
Can any of the company-specific risk be diversified away by investing in both Federal Agricultural and USU Software 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 Agricultural and USU Software into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Federal Agricultural Mortgage and USU Software AG, you can compare the effects of market volatilities on Federal Agricultural and USU Software 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 Agricultural with a short position of USU Software. Check out your portfolio center. Please also check ongoing floating volatility patterns of Federal Agricultural and USU Software.
Diversification Opportunities for Federal Agricultural and USU Software
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Federal and USU is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Federal Agricultural Mortgage and USU Software AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on USU Software AG and Federal Agricultural 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 Agricultural Mortgage are associated (or correlated) with USU Software. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of USU Software AG has no effect on the direction of Federal Agricultural i.e., Federal Agricultural and USU Software go up and down completely randomly.
Pair Corralation between Federal Agricultural and USU Software
Assuming the 90 days horizon Federal Agricultural Mortgage is expected to under-perform the USU Software. In addition to that, Federal Agricultural is 1.51 times more volatile than USU Software AG. It trades about -0.07 of its total potential returns per unit of risk. USU Software AG is currently generating about -0.09 per unit of volatility. If you would invest 2,250 in USU Software AG on October 11, 2024 and sell it today you would lose (90.00) from holding USU Software AG or give up 4.0% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Federal Agricultural Mortgage vs. USU Software AG
Performance |
Timeline |
Federal Agricultural |
USU Software AG |
Federal Agricultural and USU Software Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Federal Agricultural and USU Software
The main advantage of trading using opposite Federal Agricultural and USU Software positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Federal Agricultural position performs unexpectedly, USU Software 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 USU Software will offset losses from the drop in USU Software's long position.Federal Agricultural vs. Aedas Homes SA | Federal Agricultural vs. American Homes 4 | Federal Agricultural vs. Addus HomeCare | Federal Agricultural vs. Haverty Furniture Companies |
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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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