Correlation Between GREENX METALS and ETFS Coffee
Can any of the company-specific risk be diversified away by investing in both GREENX METALS and ETFS Coffee 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 GREENX METALS and ETFS Coffee into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GREENX METALS LTD and ETFS Coffee ETC, you can compare the effects of market volatilities on GREENX METALS and ETFS Coffee 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 GREENX METALS with a short position of ETFS Coffee. Check out your portfolio center. Please also check ongoing floating volatility patterns of GREENX METALS and ETFS Coffee.
Diversification Opportunities for GREENX METALS and ETFS Coffee
-0.21 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GREENX and ETFS is -0.21. Overlapping area represents the amount of risk that can be diversified away by holding GREENX METALS LTD and ETFS Coffee ETC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ETFS Coffee ETC and GREENX METALS 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 GREENX METALS LTD are associated (or correlated) with ETFS Coffee. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ETFS Coffee ETC has no effect on the direction of GREENX METALS i.e., GREENX METALS and ETFS Coffee go up and down completely randomly.
Pair Corralation between GREENX METALS and ETFS Coffee
Assuming the 90 days trading horizon GREENX METALS LTD is expected to under-perform the ETFS Coffee. In addition to that, GREENX METALS is 1.62 times more volatile than ETFS Coffee ETC. It trades about -0.15 of its total potential returns per unit of risk. ETFS Coffee ETC is currently generating about 0.49 per unit of volatility. If you would invest 3,861 in ETFS Coffee ETC on August 28, 2024 and sell it today you would earn a total of 1,068 from holding ETFS Coffee ETC or generate 27.66% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.24% |
| Values | Daily Returns |
GREENX METALS LTD vs. ETFS Coffee ETC
Performance |
| Timeline |
| GREENX METALS LTD |
| ETFS Coffee ETC |
GREENX METALS and ETFS Coffee Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GREENX METALS and ETFS Coffee
The main advantage of trading using opposite GREENX METALS and ETFS Coffee positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GREENX METALS position performs unexpectedly, ETFS Coffee 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 ETFS Coffee will offset losses from the drop in ETFS Coffee's long position.| GREENX METALS vs. PERENNIAL ENERGY HD 01 | GREENX METALS vs. Superior Plus Corp | GREENX METALS vs. NMI Holdings | GREENX METALS vs. Origin Agritech |
| ETFS Coffee vs. Apple Inc | ETFS Coffee vs. Apple Inc | ETFS Coffee vs. Apple Inc | ETFS Coffee 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 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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