Correlation Between Sandfire Resources and Aruma Resources
Can any of the company-specific risk be diversified away by investing in both Sandfire Resources and Aruma Resources 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 Sandfire Resources and Aruma Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sandfire Resources NL and Aruma Resources, you can compare the effects of market volatilities on Sandfire Resources and Aruma Resources 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 Sandfire Resources with a short position of Aruma Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sandfire Resources and Aruma Resources.
Diversification Opportunities for Sandfire Resources and Aruma Resources
-0.36 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Sandfire and Aruma is -0.36. Overlapping area represents the amount of risk that can be diversified away by holding Sandfire Resources NL and Aruma Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aruma Resources and Sandfire 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 Sandfire Resources NL are associated (or correlated) with Aruma Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aruma Resources has no effect on the direction of Sandfire Resources i.e., Sandfire Resources and Aruma Resources go up and down completely randomly.
Pair Corralation between Sandfire Resources and Aruma Resources
Assuming the 90 days trading horizon Sandfire Resources NL is expected to generate 0.17 times more return on investment than Aruma Resources. However, Sandfire Resources NL is 5.87 times less risky than Aruma Resources. It trades about 0.01 of its potential returns per unit of risk. Aruma Resources is currently generating about -0.1 per unit of risk. If you would invest 1,037 in Sandfire Resources NL on September 1, 2024 and sell it today you would earn a total of 0.00 from holding Sandfire Resources NL or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.65% |
Values | Daily Returns |
Sandfire Resources NL vs. Aruma Resources
Performance |
Timeline |
Sandfire Resources |
Aruma Resources |
Sandfire Resources and Aruma Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sandfire Resources and Aruma Resources
The main advantage of trading using opposite Sandfire Resources and Aruma Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sandfire Resources position performs unexpectedly, Aruma Resources 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 Aruma Resources will offset losses from the drop in Aruma Resources' long position.Sandfire Resources vs. Readytech Holdings | Sandfire Resources vs. Thorney Technologies | Sandfire Resources vs. TTG Fintech | Sandfire Resources vs. BTC Health Limited |
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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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