Correlation Between PREMIER FOODS and Impala Platinum
Can any of the company-specific risk be diversified away by investing in both PREMIER FOODS and Impala Platinum 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 PREMIER FOODS and Impala Platinum into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PREMIER FOODS and Impala Platinum Holdings, you can compare the effects of market volatilities on PREMIER FOODS and Impala Platinum 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 PREMIER FOODS with a short position of Impala Platinum. Check out your portfolio center. Please also check ongoing floating volatility patterns of PREMIER FOODS and Impala Platinum.
Diversification Opportunities for PREMIER FOODS and Impala Platinum
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between PREMIER and Impala is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding PREMIER FOODS and Impala Platinum Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Impala Platinum Holdings and PREMIER FOODS 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 PREMIER FOODS are associated (or correlated) with Impala Platinum. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Impala Platinum Holdings has no effect on the direction of PREMIER FOODS i.e., PREMIER FOODS and Impala Platinum go up and down completely randomly.
Pair Corralation between PREMIER FOODS and Impala Platinum
Assuming the 90 days trading horizon PREMIER FOODS is expected to generate 1.24 times less return on investment than Impala Platinum. But when comparing it to its historical volatility, PREMIER FOODS is 3.0 times less risky than Impala Platinum. It trades about 0.12 of its potential returns per unit of risk. Impala Platinum Holdings is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 405.00 in Impala Platinum Holdings on September 14, 2024 and sell it today you would earn a total of 151.00 from holding Impala Platinum Holdings or generate 37.28% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
PREMIER FOODS vs. Impala Platinum Holdings
Performance |
Timeline |
PREMIER FOODS |
Impala Platinum Holdings |
PREMIER FOODS and Impala Platinum Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with PREMIER FOODS and Impala Platinum
The main advantage of trading using opposite PREMIER FOODS and Impala Platinum positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PREMIER FOODS position performs unexpectedly, Impala Platinum 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 Impala Platinum will offset losses from the drop in Impala Platinum's long position.PREMIER FOODS vs. Federal Agricultural Mortgage | PREMIER FOODS vs. DAIRY FARM INTL | PREMIER FOODS vs. Sterling Construction | PREMIER FOODS vs. CITY OFFICE REIT |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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