Correlation Between Stag Industrial and CSSC Offshore
Can any of the company-specific risk be diversified away by investing in both Stag Industrial and CSSC Offshore 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 Stag Industrial and CSSC Offshore into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Stag Industrial and CSSC Offshore Marine, you can compare the effects of market volatilities on Stag Industrial and CSSC Offshore 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 Stag Industrial with a short position of CSSC Offshore. Check out your portfolio center. Please also check ongoing floating volatility patterns of Stag Industrial and CSSC Offshore.
Diversification Opportunities for Stag Industrial and CSSC Offshore
0.29 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Stag and CSSC is 0.29. Overlapping area represents the amount of risk that can be diversified away by holding Stag Industrial and CSSC Offshore Marine in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CSSC Offshore Marine and Stag Industrial 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 Stag Industrial are associated (or correlated) with CSSC Offshore. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CSSC Offshore Marine has no effect on the direction of Stag Industrial i.e., Stag Industrial and CSSC Offshore go up and down completely randomly.
Pair Corralation between Stag Industrial and CSSC Offshore
Assuming the 90 days trading horizon Stag Industrial is expected to generate 0.84 times more return on investment than CSSC Offshore. However, Stag Industrial is 1.18 times less risky than CSSC Offshore. It trades about 0.11 of its potential returns per unit of risk. CSSC Offshore Marine is currently generating about -0.3 per unit of risk. If you would invest 3,259 in Stag Industrial on October 20, 2024 and sell it today you would earn a total of 85.00 from holding Stag Industrial or generate 2.61% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 94.44% |
| Values | Daily Returns |
Stag Industrial vs. CSSC Offshore Marine
Performance |
| Timeline |
| Stag Industrial |
| CSSC Offshore Marine |
Stag Industrial and CSSC Offshore Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Stag Industrial and CSSC Offshore
The main advantage of trading using opposite Stag Industrial and CSSC Offshore positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Stag Industrial position performs unexpectedly, CSSC Offshore 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 CSSC Offshore will offset losses from the drop in CSSC Offshore's long position.| Stag Industrial vs. Apple Inc | Stag Industrial vs. Apple Inc | Stag Industrial vs. Apple Inc | Stag Industrial vs. Apple Inc |
| CSSC Offshore vs. Stag Industrial | CSSC Offshore vs. Ubisoft Entertainment SA | CSSC Offshore vs. GREENX METALS LTD | CSSC Offshore vs. ARDAGH METAL PACDL 0001 |
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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