Correlation Between Infinico Metals and Rackla Metals
Can any of the company-specific risk be diversified away by investing in both Infinico Metals and Rackla 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 Infinico Metals and Rackla Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Infinico Metals Corp and Rackla Metals, you can compare the effects of market volatilities on Infinico Metals and Rackla 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 Infinico Metals with a short position of Rackla Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Infinico Metals and Rackla Metals.
Diversification Opportunities for Infinico Metals and Rackla Metals
-0.62 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Infinico and Rackla is -0.62. Overlapping area represents the amount of risk that can be diversified away by holding Infinico Metals Corp and Rackla Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Rackla Metals and Infinico 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 Infinico Metals Corp are associated (or correlated) with Rackla Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Rackla Metals has no effect on the direction of Infinico Metals i.e., Infinico Metals and Rackla Metals go up and down completely randomly.
Pair Corralation between Infinico Metals and Rackla Metals
Assuming the 90 days trading horizon Infinico Metals Corp is expected to under-perform the Rackla Metals. In addition to that, Infinico Metals is 1.18 times more volatile than Rackla Metals. It trades about -0.17 of its total potential returns per unit of risk. Rackla Metals is currently generating about 0.09 per unit of volatility. If you would invest 10.00 in Rackla Metals on August 28, 2024 and sell it today you would earn a total of 1.00 from holding Rackla Metals or generate 10.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 95.24% |
| Values | Daily Returns |
Infinico Metals Corp vs. Rackla Metals
Performance |
| Timeline |
| Infinico Metals Corp |
| Rackla Metals |
Infinico Metals and Rackla Metals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Infinico Metals and Rackla Metals
The main advantage of trading using opposite Infinico Metals and Rackla Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Infinico Metals position performs unexpectedly, Rackla 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 Rackla Metals will offset losses from the drop in Rackla Metals' long position.| Infinico Metals vs. First Majestic Silver | Infinico Metals vs. Ivanhoe Energy | Infinico Metals vs. Orezone Gold Corp |
| Rackla Metals vs. First Majestic Silver | Rackla Metals vs. Ivanhoe Energy | Rackla Metals vs. Orezone Gold Corp |
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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