Correlation Between Retail Food and Mantle Minerals
Can any of the company-specific risk be diversified away by investing in both Retail Food and Mantle Minerals 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 Retail Food and Mantle Minerals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Retail Food Group and Mantle Minerals Limited, you can compare the effects of market volatilities on Retail Food and Mantle Minerals 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 Retail Food with a short position of Mantle Minerals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Retail Food and Mantle Minerals.
Diversification Opportunities for Retail Food and Mantle Minerals
-0.38 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Retail and Mantle is -0.38. Overlapping area represents the amount of risk that can be diversified away by holding Retail Food Group and Mantle Minerals Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mantle Minerals and Retail Food 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 Retail Food Group are associated (or correlated) with Mantle Minerals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mantle Minerals has no effect on the direction of Retail Food i.e., Retail Food and Mantle Minerals go up and down completely randomly.
Pair Corralation between Retail Food and Mantle Minerals
Assuming the 90 days trading horizon Retail Food is expected to generate 17.13 times less return on investment than Mantle Minerals. But when comparing it to its historical volatility, Retail Food Group is 10.65 times less risky than Mantle Minerals. It trades about 0.04 of its potential returns per unit of risk. Mantle Minerals Limited is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 0.20 in Mantle Minerals Limited on September 15, 2024 and sell it today you would lose (0.10) from holding Mantle Minerals Limited or give up 50.0% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Retail Food Group vs. Mantle Minerals Limited
Performance |
Timeline |
Retail Food Group |
Mantle Minerals |
Retail Food and Mantle Minerals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Retail Food and Mantle Minerals
The main advantage of trading using opposite Retail Food and Mantle Minerals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Retail Food position performs unexpectedly, Mantle Minerals 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 Mantle Minerals will offset losses from the drop in Mantle Minerals' long position.Retail Food vs. Oceania Healthcare | Retail Food vs. Capitol Health | Retail Food vs. Ramsay Health Care | Retail Food vs. Macquarie Technology Group |
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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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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