Correlation Between Future Metals and Adriatic Metals
Can any of the company-specific risk be diversified away by investing in both Future Metals and Adriatic Metals 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 Future Metals and Adriatic Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Future Metals NL and Adriatic Metals, you can compare the effects of market volatilities on Future Metals and Adriatic Metals 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 Future Metals with a short position of Adriatic Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Future Metals and Adriatic Metals.
Diversification Opportunities for Future Metals and Adriatic Metals
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Future and Adriatic is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Future Metals NL and Adriatic Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Adriatic Metals and Future 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 Future Metals NL are associated (or correlated) with Adriatic Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Adriatic Metals has no effect on the direction of Future Metals i.e., Future Metals and Adriatic Metals go up and down completely randomly.
Pair Corralation between Future Metals and Adriatic Metals
Assuming the 90 days trading horizon Future Metals NL is expected to under-perform the Adriatic Metals. In addition to that, Future Metals is 1.12 times more volatile than Adriatic Metals. It trades about -0.05 of its total potential returns per unit of risk. Adriatic Metals is currently generating about 0.01 per unit of volatility. If you would invest 21,200 in Adriatic Metals on August 30, 2024 and sell it today you would lose (400.00) from holding Adriatic Metals or give up 1.89% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Future Metals NL vs. Adriatic Metals
Performance |
| Timeline |
| Future Metals NL |
| Adriatic Metals |
Future Metals and Adriatic Metals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Future Metals and Adriatic Metals
The main advantage of trading using opposite Future Metals and Adriatic Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Future Metals position performs unexpectedly, Adriatic Metals 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 Adriatic Metals will offset losses from the drop in Adriatic Metals' long position.| Future Metals vs. Givaudan SA | Future Metals vs. Antofagasta PLC | Future Metals vs. Centamin PLC | Future Metals vs. Atalaya Mining |
| Adriatic Metals vs. Givaudan SA | Adriatic Metals vs. Antofagasta PLC | Adriatic Metals vs. Centamin PLC | Adriatic Metals vs. Atalaya Mining |
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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