Correlation Between Eros Resources and Mkango Resources
Can any of the company-specific risk be diversified away by investing in both Eros Resources and Mkango 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 Eros Resources and Mkango Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Eros Resources Corp and Mkango Resources, you can compare the effects of market volatilities on Eros Resources and Mkango 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 Eros Resources with a short position of Mkango Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Eros Resources and Mkango Resources.
Diversification Opportunities for Eros Resources and Mkango Resources
0.07 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Eros and Mkango is 0.07. Overlapping area represents the amount of risk that can be diversified away by holding Eros Resources Corp and Mkango Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mkango Resources and Eros 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 Eros Resources Corp are associated (or correlated) with Mkango Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mkango Resources has no effect on the direction of Eros Resources i.e., Eros Resources and Mkango Resources go up and down completely randomly.
Pair Corralation between Eros Resources and Mkango Resources
Assuming the 90 days horizon Eros Resources Corp is expected to generate 0.81 times more return on investment than Mkango Resources. However, Eros Resources Corp is 1.23 times less risky than Mkango Resources. It trades about 0.09 of its potential returns per unit of risk. Mkango Resources is currently generating about 0.07 per unit of risk. If you would invest 3.50 in Eros Resources Corp on October 24, 2024 and sell it today you would earn a total of 1.50 from holding Eros Resources Corp or generate 42.86% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Eros Resources Corp vs. Mkango Resources
Performance |
Timeline |
Eros Resources Corp |
Mkango Resources |
Eros Resources and Mkango Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Eros Resources and Mkango Resources
The main advantage of trading using opposite Eros Resources and Mkango Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Eros Resources position performs unexpectedly, Mkango 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 Mkango Resources will offset losses from the drop in Mkango Resources' long position.Eros Resources vs. National Bank of | Eros Resources vs. Financial 15 Split | Eros Resources vs. CVS HEALTH CDR | Eros Resources vs. Canadian Imperial Bank |
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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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