Correlation Between GoMgA Resources and Lithium Chile
Can any of the company-specific risk be diversified away by investing in both GoMgA Resources and Lithium Chile 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 GoMgA Resources and Lithium Chile into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GoMgA Resources and Lithium Chile, you can compare the effects of market volatilities on GoMgA Resources and Lithium Chile 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 GoMgA Resources with a short position of Lithium Chile. Check out your portfolio center. Please also check ongoing floating volatility patterns of GoMgA Resources and Lithium Chile.
Diversification Opportunities for GoMgA Resources and Lithium Chile
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GoMgA and Lithium is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding GoMgA Resources and Lithium Chile in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lithium Chile and GoMgA Resources 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 GoMgA Resources are associated (or correlated) with Lithium Chile. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lithium Chile has no effect on the direction of GoMgA Resources i.e., GoMgA Resources and Lithium Chile go up and down completely randomly.
Pair Corralation between GoMgA Resources and Lithium Chile
Assuming the 90 days horizon GoMgA Resources is expected to generate 1.63 times less return on investment than Lithium Chile. In addition to that, GoMgA Resources is 1.74 times more volatile than Lithium Chile. It trades about 0.01 of its total potential returns per unit of risk. Lithium Chile is currently generating about 0.03 per unit of volatility. If you would invest 43.00 in Lithium Chile on October 27, 2024 and sell it today you would earn a total of 6.00 from holding Lithium Chile or generate 13.95% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 99.68% |
Values | Daily Returns |
GoMgA Resources vs. Lithium Chile
Performance |
Timeline |
GoMgA Resources |
Lithium Chile |
GoMgA Resources and Lithium Chile Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GoMgA Resources and Lithium Chile
The main advantage of trading using opposite GoMgA Resources and Lithium Chile positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GoMgA Resources position performs unexpectedly, Lithium Chile 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 Lithium Chile will offset losses from the drop in Lithium Chile's long position.GoMgA Resources vs. Infinite Ore Corp | GoMgA Resources vs. FPX Nickel Corp | GoMgA Resources vs. Power Metals Corp | GoMgA Resources vs. International Lithium Corp |
Lithium Chile vs. GoMgA Resources | Lithium Chile vs. Infinite Ore Corp | Lithium Chile vs. FPX Nickel Corp | Lithium Chile vs. Power Metals 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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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