Correlation Between Cumberland Pharmaceuticals and SSIC Old
Can any of the company-specific risk be diversified away by investing in both Cumberland Pharmaceuticals and SSIC Old 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 Cumberland Pharmaceuticals and SSIC Old into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cumberland Pharmaceuticals and SSIC Old, you can compare the effects of market volatilities on Cumberland Pharmaceuticals and SSIC Old 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 Cumberland Pharmaceuticals with a short position of SSIC Old. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cumberland Pharmaceuticals and SSIC Old.
Diversification Opportunities for Cumberland Pharmaceuticals and SSIC Old
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Cumberland and SSIC is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Cumberland Pharmaceuticals and SSIC Old in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SSIC Old and Cumberland Pharmaceuticals 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 Cumberland Pharmaceuticals are associated (or correlated) with SSIC Old. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SSIC Old has no effect on the direction of Cumberland Pharmaceuticals i.e., Cumberland Pharmaceuticals and SSIC Old go up and down completely randomly.
Pair Corralation between Cumberland Pharmaceuticals and SSIC Old
If you would invest 242.00 in Cumberland Pharmaceuticals on December 30, 2024 and sell it today you would earn a total of 199.00 from holding Cumberland Pharmaceuticals or generate 82.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Flat |
Strength | Insignificant |
Accuracy | 0.0% |
Values | Daily Returns |
Cumberland Pharmaceuticals vs. SSIC Old
Performance |
Timeline |
Cumberland Pharmaceuticals |
SSIC Old |
Risk-Adjusted Performance
Very Weak
Weak | Strong |
Cumberland Pharmaceuticals and SSIC Old Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cumberland Pharmaceuticals and SSIC Old
The main advantage of trading using opposite Cumberland Pharmaceuticals and SSIC Old positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cumberland Pharmaceuticals position performs unexpectedly, SSIC Old 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 SSIC Old will offset losses from the drop in SSIC Old's long position.The idea behind Cumberland Pharmaceuticals and SSIC Old 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.
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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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