Correlation Between CSSC Offshore and Mitsubishi Materials
Can any of the company-specific risk be diversified away by investing in both CSSC Offshore and Mitsubishi Materials 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 CSSC Offshore and Mitsubishi Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CSSC Offshore Marine and Mitsubishi Materials, you can compare the effects of market volatilities on CSSC Offshore and Mitsubishi Materials 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 CSSC Offshore with a short position of Mitsubishi Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of CSSC Offshore and Mitsubishi Materials.
Diversification Opportunities for CSSC Offshore and Mitsubishi Materials
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between CSSC and Mitsubishi is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding CSSC Offshore Marine and Mitsubishi Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mitsubishi Materials and CSSC Offshore 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 CSSC Offshore Marine are associated (or correlated) with Mitsubishi Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mitsubishi Materials has no effect on the direction of CSSC Offshore i.e., CSSC Offshore and Mitsubishi Materials go up and down completely randomly.
Pair Corralation between CSSC Offshore and Mitsubishi Materials
Assuming the 90 days trading horizon CSSC Offshore Marine is expected to under-perform the Mitsubishi Materials. In addition to that, CSSC Offshore is 2.44 times more volatile than Mitsubishi Materials. It trades about -0.09 of its total potential returns per unit of risk. Mitsubishi Materials is currently generating about 0.01 per unit of volatility. If you would invest 1,500 in Mitsubishi Materials on September 13, 2024 and sell it today you would earn a total of 0.00 from holding Mitsubishi Materials or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
CSSC Offshore Marine vs. Mitsubishi Materials
Performance |
Timeline |
CSSC Offshore Marine |
Mitsubishi Materials |
CSSC Offshore and Mitsubishi Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CSSC Offshore and Mitsubishi Materials
The main advantage of trading using opposite CSSC Offshore and Mitsubishi Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CSSC Offshore position performs unexpectedly, Mitsubishi Materials 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 Mitsubishi Materials will offset losses from the drop in Mitsubishi Materials' long position.CSSC Offshore vs. Apple Inc | CSSC Offshore vs. Apple Inc | CSSC Offshore vs. Apple Inc | CSSC Offshore vs. Apple Inc |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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