Correlation Between SYSCO and Federal National
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By analyzing existing cross correlation between SYSCO P 445 and Federal National Mortgage, you can compare the effects of market volatilities on SYSCO and Federal National 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 SYSCO with a short position of Federal National. Check out your portfolio center. Please also check ongoing floating volatility patterns of SYSCO and Federal National.
Diversification Opportunities for SYSCO and Federal National
-0.47 | Correlation Coefficient |
Very good diversification
The 3 months correlation between SYSCO and Federal is -0.47. Overlapping area represents the amount of risk that can be diversified away by holding SYSCO P 445 and Federal National Mortgage in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federal National Mortgage and SYSCO 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 SYSCO P 445 are associated (or correlated) with Federal National. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federal National Mortgage has no effect on the direction of SYSCO i.e., SYSCO and Federal National go up and down completely randomly.
Pair Corralation between SYSCO and Federal National
Assuming the 90 days trading horizon SYSCO is expected to generate 6.72 times less return on investment than Federal National. But when comparing it to its historical volatility, SYSCO P 445 is 4.85 times less risky than Federal National. It trades about 0.22 of its potential returns per unit of risk. Federal National Mortgage is currently generating about 0.31 of returns per unit of risk over similar time horizon. If you would invest 730.00 in Federal National Mortgage on August 25, 2024 and sell it today you would earn a total of 830.00 from holding Federal National Mortgage or generate 113.7% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 54.55% |
| Values | Daily Returns |
SYSCO P 445 vs. Federal National Mortgage
Performance |
| Timeline |
| SYSCO P 445 |
| Federal National Mortgage |
SYSCO and Federal National Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SYSCO and Federal National
The main advantage of trading using opposite SYSCO and Federal National positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SYSCO position performs unexpectedly, Federal National 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 Federal National will offset losses from the drop in Federal National's long position.The idea behind SYSCO P 445 and Federal National Mortgage pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Federal National vs. Federal Home Loan | Federal National vs. Federal Home Loan | Federal National vs. Federal Home Loan | Federal National vs. Federal Home Loan |
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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