Correlation Between JCTCF Old and National Storm
Can any of the company-specific risk be diversified away by investing in both JCTCF Old and National Storm 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 JCTCF Old and National Storm into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between JCTCF Old and National Storm Recovery, you can compare the effects of market volatilities on JCTCF Old and National Storm 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 JCTCF Old with a short position of National Storm. Check out your portfolio center. Please also check ongoing floating volatility patterns of JCTCF Old and National Storm.
Diversification Opportunities for JCTCF Old and National Storm
-0.16 | Correlation Coefficient |
Good diversification
The 3 months correlation between JCTCF and National is -0.16. Overlapping area represents the amount of risk that can be diversified away by holding JCTCF Old and National Storm Recovery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on National Storm Recovery and JCTCF Old 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 JCTCF Old are associated (or correlated) with National Storm. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of National Storm Recovery has no effect on the direction of JCTCF Old i.e., JCTCF Old and National Storm go up and down completely randomly.
Pair Corralation between JCTCF Old and National Storm
Assuming the 90 days horizon JCTCF Old is expected to under-perform the National Storm. But the stock apears to be less risky and, when comparing its historical volatility, JCTCF Old is 6.95 times less risky than National Storm. The stock trades about 0.0 of its potential returns per unit of risk. The National Storm Recovery is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 36.00 in National Storm Recovery on October 22, 2024 and sell it today you would lose (26.00) from holding National Storm Recovery or give up 72.22% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 69.6% |
| Values | Daily Returns |
JCTCF Old vs. National Storm Recovery
Performance |
| Timeline |
| JCTCF Old |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| National Storm Recovery |
JCTCF Old and National Storm Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with JCTCF Old and National Storm
The main advantage of trading using opposite JCTCF Old and National Storm positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JCTCF Old position performs unexpectedly, National Storm 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 National Storm will offset losses from the drop in National Storm's long position.| JCTCF Old vs. National Storm Recovery | JCTCF Old vs. Kewaunee Scientific | JCTCF Old vs. Nortech Systems Incorporated | JCTCF Old vs. Gencor Industries |
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 Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.
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