Correlation Between Waste Management and General Motors
Can any of the company-specific risk be diversified away by investing in both Waste Management and General Motors 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 Waste Management and General Motors into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Waste Management and General Motors, you can compare the effects of market volatilities on Waste Management and General Motors 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 Waste Management with a short position of General Motors. Check out your portfolio center. Please also check ongoing floating volatility patterns of Waste Management and General Motors.
Diversification Opportunities for Waste Management and General Motors
-0.23 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Waste and General is -0.23. Overlapping area represents the amount of risk that can be diversified away by holding Waste Management and General Motors in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on General Motors and Waste Management 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 Waste Management are associated (or correlated) with General Motors. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of General Motors has no effect on the direction of Waste Management i.e., Waste Management and General Motors go up and down completely randomly.
Pair Corralation between Waste Management and General Motors
Assuming the 90 days trading horizon Waste Management is expected to generate 0.41 times more return on investment than General Motors. However, Waste Management is 2.43 times less risky than General Motors. It trades about 0.0 of its potential returns per unit of risk. General Motors is currently generating about -0.07 per unit of risk. If you would invest 68,095 in Waste Management on December 2, 2024 and sell it today you would lose (203.00) from holding Waste Management or give up 0.3% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Waste Management vs. General Motors
Performance |
Timeline |
Waste Management |
General Motors |
Waste Management and General Motors Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Waste Management and General Motors
The main advantage of trading using opposite Waste Management and General Motors positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Waste Management position performs unexpectedly, General Motors 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 General Motors will offset losses from the drop in General Motors' long position.Waste Management vs. Jefferies Financial Group | Waste Management vs. The Hartford Financial | Waste Management vs. Lloyds Banking Group | Waste Management vs. Citizens Financial Group, |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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