Correlation Between Iluka Resources and Giyani Metals
Can any of the company-specific risk be diversified away by investing in both Iluka Resources and Giyani 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 Iluka Resources and Giyani Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Iluka Resources Ltd and Giyani Metals Corp, you can compare the effects of market volatilities on Iluka Resources and Giyani 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 Iluka Resources with a short position of Giyani Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Iluka Resources and Giyani Metals.
Diversification Opportunities for Iluka Resources and Giyani Metals
-0.31 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Iluka and Giyani is -0.31. Overlapping area represents the amount of risk that can be diversified away by holding Iluka Resources Ltd and Giyani Metals Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Giyani Metals Corp and Iluka 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 Iluka Resources Ltd are associated (or correlated) with Giyani Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Giyani Metals Corp has no effect on the direction of Iluka Resources i.e., Iluka Resources and Giyani Metals go up and down completely randomly.
Pair Corralation between Iluka Resources and Giyani Metals
Assuming the 90 days horizon Iluka Resources Ltd is expected to under-perform the Giyani Metals. But the pink sheet apears to be less risky and, when comparing its historical volatility, Iluka Resources Ltd is 3.0 times less risky than Giyani Metals. The pink sheet trades about -0.08 of its potential returns per unit of risk. The Giyani Metals Corp is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 6.00 in Giyani Metals Corp on December 29, 2024 and sell it today you would earn a total of 0.00 from holding Giyani Metals Corp or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Iluka Resources Ltd vs. Giyani Metals Corp
Performance |
Timeline |
Iluka Resources |
Giyani Metals Corp |
Iluka Resources and Giyani Metals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Iluka Resources and Giyani Metals
The main advantage of trading using opposite Iluka Resources and Giyani Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Iluka Resources position performs unexpectedly, Giyani 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 Giyani Metals will offset losses from the drop in Giyani Metals' long position.Iluka Resources vs. ERAMET SA | Iluka Resources vs. Giyani Metals Corp | Iluka Resources vs. IGO Limited | Iluka Resources vs. Grid Metals Corp |
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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 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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