Correlation Between EMCOR and Gamma Communications
Can any of the company-specific risk be diversified away by investing in both EMCOR and Gamma Communications 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 EMCOR and Gamma Communications into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EMCOR Group and Gamma Communications plc, you can compare the effects of market volatilities on EMCOR and Gamma Communications 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 EMCOR with a short position of Gamma Communications. Check out your portfolio center. Please also check ongoing floating volatility patterns of EMCOR and Gamma Communications.
Diversification Opportunities for EMCOR and Gamma Communications
-0.48 | Correlation Coefficient |
Very good diversification
The 3 months correlation between EMCOR and Gamma is -0.48. Overlapping area represents the amount of risk that can be diversified away by holding EMCOR Group and Gamma Communications plc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gamma Communications plc and EMCOR 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 EMCOR Group are associated (or correlated) with Gamma Communications. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gamma Communications plc has no effect on the direction of EMCOR i.e., EMCOR and Gamma Communications go up and down completely randomly.
Pair Corralation between EMCOR and Gamma Communications
Assuming the 90 days horizon EMCOR Group is expected to generate 1.37 times more return on investment than Gamma Communications. However, EMCOR is 1.37 times more volatile than Gamma Communications plc. It trades about 0.09 of its potential returns per unit of risk. Gamma Communications plc is currently generating about 0.05 per unit of risk. If you would invest 33,415 in EMCOR Group on September 30, 2024 and sell it today you would earn a total of 11,025 from holding EMCOR Group or generate 32.99% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
EMCOR Group vs. Gamma Communications plc
Performance |
Timeline |
EMCOR Group |
Gamma Communications plc |
EMCOR and Gamma Communications Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with EMCOR and Gamma Communications
The main advantage of trading using opposite EMCOR and Gamma Communications positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EMCOR position performs unexpectedly, Gamma Communications 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 Gamma Communications will offset losses from the drop in Gamma Communications' long position.EMCOR vs. Gamma Communications plc | EMCOR vs. Verizon Communications | EMCOR vs. COMPUTERSHARE | EMCOR vs. BURLINGTON STORES |
Gamma Communications vs. T Mobile | Gamma Communications vs. ATT Inc | Gamma Communications vs. Deutsche Telekom AG | Gamma Communications vs. Deutsche Telekom AG |
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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