Correlation Between Martin Marietta and Vulcan Materials
Can any of the company-specific risk be diversified away by investing in both Martin Marietta and Vulcan 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 Martin Marietta and Vulcan Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Martin Marietta Materials, and Vulcan Materials, you can compare the effects of market volatilities on Martin Marietta and Vulcan 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 Martin Marietta with a short position of Vulcan Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of Martin Marietta and Vulcan Materials.
Diversification Opportunities for Martin Marietta and Vulcan Materials
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Martin and Vulcan is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Martin Marietta Materials, and Vulcan Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Vulcan Materials and Martin Marietta 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 Martin Marietta Materials, are associated (or correlated) with Vulcan Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Vulcan Materials has no effect on the direction of Martin Marietta i.e., Martin Marietta and Vulcan Materials go up and down completely randomly.
Pair Corralation between Martin Marietta and Vulcan Materials
Assuming the 90 days trading horizon Martin Marietta Materials, is expected to generate 0.06 times more return on investment than Vulcan Materials. However, Martin Marietta Materials, is 15.66 times less risky than Vulcan Materials. It trades about -0.11 of its potential returns per unit of risk. Vulcan Materials is currently generating about -0.17 per unit of risk. If you would invest 56,187 in Martin Marietta Materials, on December 25, 2024 and sell it today you would lose (499.00) from holding Martin Marietta Materials, or give up 0.89% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Martin Marietta Materials, vs. Vulcan Materials
Performance |
Timeline |
Martin Marietta Mate |
Vulcan Materials |
Martin Marietta and Vulcan Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Martin Marietta and Vulcan Materials
The main advantage of trading using opposite Martin Marietta and Vulcan Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Martin Marietta position performs unexpectedly, Vulcan 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 Vulcan Materials will offset losses from the drop in Vulcan Materials' long position.Martin Marietta vs. Micron Technology | Martin Marietta vs. Paycom Software | Martin Marietta vs. L3Harris Technologies, | Martin Marietta vs. Seagate Technology Holdings |
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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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