Correlation Between Federal Agricultural and SLM Corp
Can any of the company-specific risk be diversified away by investing in both Federal Agricultural and SLM Corp 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 SLM Corp 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 SLM Corp Pb, you can compare the effects of market volatilities on Federal Agricultural and SLM Corp 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 SLM Corp. Check out your portfolio center. Please also check ongoing floating volatility patterns of Federal Agricultural and SLM Corp.
Diversification Opportunities for Federal Agricultural and SLM Corp
-0.15 | Correlation Coefficient |
Good diversification
The 3 months correlation between Federal and SLM is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding Federal Agricultural Mortgage and SLM Corp Pb in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SLM Corp Pb 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 SLM Corp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SLM Corp Pb has no effect on the direction of Federal Agricultural i.e., Federal Agricultural and SLM Corp go up and down completely randomly.
Pair Corralation between Federal Agricultural and SLM Corp
Considering the 90-day investment horizon Federal Agricultural Mortgage is expected to generate 3.8 times more return on investment than SLM Corp. However, Federal Agricultural is 3.8 times more volatile than SLM Corp Pb. It trades about 0.07 of its potential returns per unit of risk. SLM Corp Pb is currently generating about 0.01 per unit of risk. If you would invest 19,600 in Federal Agricultural Mortgage on August 30, 2024 and sell it today you would earn a total of 1,531 from holding Federal Agricultural Mortgage or generate 7.81% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Federal Agricultural Mortgage vs. SLM Corp Pb
Performance |
Timeline |
Federal Agricultural |
SLM Corp Pb |
Federal Agricultural and SLM Corp Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Federal Agricultural and SLM Corp
The main advantage of trading using opposite Federal Agricultural and SLM Corp positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Federal Agricultural position performs unexpectedly, SLM Corp 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 SLM Corp will offset losses from the drop in SLM Corp's long position.Federal Agricultural vs. Velocity Financial Llc | Federal Agricultural vs. Security National Financial | Federal Agricultural vs. Encore Capital Group | Federal Agricultural vs. PennyMac Finl Svcs |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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