Correlation Between Martin Marietta and Northland Power
Can any of the company-specific risk be diversified away by investing in both Martin Marietta and Northland Power 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 Northland Power 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 Northland Power, you can compare the effects of market volatilities on Martin Marietta and Northland Power 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 Northland Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Martin Marietta and Northland Power.
Diversification Opportunities for Martin Marietta and Northland Power
-0.61 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Martin and Northland is -0.61. Overlapping area represents the amount of risk that can be diversified away by holding Martin Marietta Materials and Northland Power in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Northland Power 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 Northland Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Northland Power has no effect on the direction of Martin Marietta i.e., Martin Marietta and Northland Power go up and down completely randomly.
Pair Corralation between Martin Marietta and Northland Power
Assuming the 90 days trading horizon Martin Marietta Materials is expected to generate 0.55 times more return on investment than Northland Power. However, Martin Marietta Materials is 1.82 times less risky than Northland Power. It trades about 0.08 of its potential returns per unit of risk. Northland Power is currently generating about -0.03 per unit of risk. If you would invest 31,274 in Martin Marietta Materials on September 14, 2024 and sell it today you would earn a total of 21,986 from holding Martin Marietta Materials or generate 70.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Martin Marietta Materials vs. Northland Power
Performance |
Timeline |
Martin Marietta Materials |
Northland Power |
Martin Marietta and Northland Power Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Martin Marietta and Northland Power
The main advantage of trading using opposite Martin Marietta and Northland Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Martin Marietta position performs unexpectedly, Northland Power 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 Northland Power will offset losses from the drop in Northland Power's long position.Martin Marietta vs. Apple Inc | Martin Marietta vs. Apple Inc | Martin Marietta vs. Apple Inc | Martin Marietta 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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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