Correlation Between Thermo Fisher and Home Depot
Can any of the company-specific risk be diversified away by investing in both Thermo Fisher and Home Depot 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 Thermo Fisher and Home Depot into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Thermo Fisher Scientific and The Home Depot, you can compare the effects of market volatilities on Thermo Fisher and Home Depot 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 Thermo Fisher with a short position of Home Depot. Check out your portfolio center. Please also check ongoing floating volatility patterns of Thermo Fisher and Home Depot.
Diversification Opportunities for Thermo Fisher and Home Depot
-0.23 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Thermo and Home is -0.23. Overlapping area represents the amount of risk that can be diversified away by holding Thermo Fisher Scientific and The Home Depot in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Home Depot and Thermo Fisher 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 Thermo Fisher Scientific are associated (or correlated) with Home Depot. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Home Depot has no effect on the direction of Thermo Fisher i.e., Thermo Fisher and Home Depot go up and down completely randomly.
Pair Corralation between Thermo Fisher and Home Depot
Assuming the 90 days trading horizon Thermo Fisher is expected to generate 3.37 times less return on investment than Home Depot. In addition to that, Thermo Fisher is 1.37 times more volatile than The Home Depot. It trades about 0.01 of its total potential returns per unit of risk. The Home Depot is currently generating about 0.03 per unit of volatility. If you would invest 8,298 in The Home Depot on October 9, 2024 and sell it today you would earn a total of 179.00 from holding The Home Depot or generate 2.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Thermo Fisher Scientific vs. The Home Depot
Performance |
Timeline |
Thermo Fisher Scientific |
Home Depot |
Thermo Fisher and Home Depot Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Thermo Fisher and Home Depot
The main advantage of trading using opposite Thermo Fisher and Home Depot positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Thermo Fisher position performs unexpectedly, Home Depot 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 Home Depot will offset losses from the drop in Home Depot's long position.Thermo Fisher vs. Waste Management | Thermo Fisher vs. Take Two Interactive Software | Thermo Fisher vs. Check Point Software | Thermo Fisher vs. Hormel Foods |
Home Depot vs. CM Hospitalar SA | Home Depot vs. UnitedHealth Group Incorporated | Home Depot vs. Vulcan Materials | Home Depot vs. Metalrgica Riosulense SA |
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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