Correlation Between MetalsGrove Mining and Westpac Banking
Can any of the company-specific risk be diversified away by investing in both MetalsGrove Mining and Westpac Banking 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 MetalsGrove Mining and Westpac Banking into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MetalsGrove Mining and Westpac Banking, you can compare the effects of market volatilities on MetalsGrove Mining and Westpac Banking 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 MetalsGrove Mining with a short position of Westpac Banking. Check out your portfolio center. Please also check ongoing floating volatility patterns of MetalsGrove Mining and Westpac Banking.
Diversification Opportunities for MetalsGrove Mining and Westpac Banking
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between MetalsGrove and Westpac is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding MetalsGrove Mining and Westpac Banking in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Westpac Banking and MetalsGrove Mining 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 MetalsGrove Mining are associated (or correlated) with Westpac Banking. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Westpac Banking has no effect on the direction of MetalsGrove Mining i.e., MetalsGrove Mining and Westpac Banking go up and down completely randomly.
Pair Corralation between MetalsGrove Mining and Westpac Banking
Assuming the 90 days trading horizon MetalsGrove Mining is expected to generate 15.69 times more return on investment than Westpac Banking. However, MetalsGrove Mining is 15.69 times more volatile than Westpac Banking. It trades about 0.03 of its potential returns per unit of risk. Westpac Banking is currently generating about 0.06 per unit of risk. If you would invest 5.30 in MetalsGrove Mining on December 25, 2024 and sell it today you would earn a total of 0.20 from holding MetalsGrove Mining or generate 3.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
MetalsGrove Mining vs. Westpac Banking
Performance |
Timeline |
MetalsGrove Mining |
Westpac Banking |
MetalsGrove Mining and Westpac Banking Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MetalsGrove Mining and Westpac Banking
The main advantage of trading using opposite MetalsGrove Mining and Westpac Banking positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MetalsGrove Mining position performs unexpectedly, Westpac Banking 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 Westpac Banking will offset losses from the drop in Westpac Banking's long position.MetalsGrove Mining vs. Ramsay Health Care | MetalsGrove Mining vs. Event Hospitality and | MetalsGrove Mining vs. Energy Technologies Limited | MetalsGrove Mining vs. Zoom2u Technologies |
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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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