Correlation Between GFL ENVIRONM and CHINA EDUCATION
Can any of the company-specific risk be diversified away by investing in both GFL ENVIRONM and CHINA EDUCATION 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 GFL ENVIRONM and CHINA EDUCATION into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GFL ENVIRONM and CHINA EDUCATION GROUP, you can compare the effects of market volatilities on GFL ENVIRONM and CHINA EDUCATION 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 GFL ENVIRONM with a short position of CHINA EDUCATION. Check out your portfolio center. Please also check ongoing floating volatility patterns of GFL ENVIRONM and CHINA EDUCATION.
Diversification Opportunities for GFL ENVIRONM and CHINA EDUCATION
-0.68 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between GFL and CHINA is -0.68. Overlapping area represents the amount of risk that can be diversified away by holding GFL ENVIRONM and CHINA EDUCATION GROUP in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CHINA EDUCATION GROUP and GFL ENVIRONM 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 GFL ENVIRONM are associated (or correlated) with CHINA EDUCATION. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CHINA EDUCATION GROUP has no effect on the direction of GFL ENVIRONM i.e., GFL ENVIRONM and CHINA EDUCATION go up and down completely randomly.
Pair Corralation between GFL ENVIRONM and CHINA EDUCATION
Assuming the 90 days horizon GFL ENVIRONM is expected to generate 0.61 times more return on investment than CHINA EDUCATION. However, GFL ENVIRONM is 1.63 times less risky than CHINA EDUCATION. It trades about 0.11 of its potential returns per unit of risk. CHINA EDUCATION GROUP is currently generating about -0.02 per unit of risk. If you would invest 4,140 in GFL ENVIRONM on September 14, 2024 and sell it today you would earn a total of 160.00 from holding GFL ENVIRONM or generate 3.86% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
GFL ENVIRONM vs. CHINA EDUCATION GROUP
Performance |
| Timeline |
| GFL ENVIRONM |
| CHINA EDUCATION GROUP |
GFL ENVIRONM and CHINA EDUCATION Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GFL ENVIRONM and CHINA EDUCATION
The main advantage of trading using opposite GFL ENVIRONM and CHINA EDUCATION positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GFL ENVIRONM position performs unexpectedly, CHINA EDUCATION 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 CHINA EDUCATION will offset losses from the drop in CHINA EDUCATION's long position.| GFL ENVIRONM vs. Veolia Environnement SA | GFL ENVIRONM vs. Superior Plus Corp | GFL ENVIRONM vs. SIVERS SEMICONDUCTORS AB | GFL ENVIRONM vs. NorAm Drilling AS |
| CHINA EDUCATION vs. Apple Inc | CHINA EDUCATION vs. Apple Inc | CHINA EDUCATION vs. Apple Inc | CHINA EDUCATION vs. Apple Inc |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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