Correlation Between Sage Potash and Petrus Resources
Can any of the company-specific risk be diversified away by investing in both Sage Potash and Petrus 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 Sage Potash and Petrus Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sage Potash Corp and Petrus Resources, you can compare the effects of market volatilities on Sage Potash and Petrus 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 Sage Potash with a short position of Petrus Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sage Potash and Petrus Resources.
Diversification Opportunities for Sage Potash and Petrus Resources
-0.41 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Sage and Petrus is -0.41. Overlapping area represents the amount of risk that can be diversified away by holding Sage Potash Corp and Petrus Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Petrus Resources and Sage Potash 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 Sage Potash Corp are associated (or correlated) with Petrus Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Petrus Resources has no effect on the direction of Sage Potash i.e., Sage Potash and Petrus Resources go up and down completely randomly.
Pair Corralation between Sage Potash and Petrus Resources
Assuming the 90 days trading horizon Sage Potash Corp is expected to generate 2.88 times more return on investment than Petrus Resources. However, Sage Potash is 2.88 times more volatile than Petrus Resources. It trades about 0.01 of its potential returns per unit of risk. Petrus Resources is currently generating about -0.01 per unit of risk. If you would invest 59.00 in Sage Potash Corp on September 3, 2024 and sell it today you would lose (39.00) from holding Sage Potash Corp or give up 66.1% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 86.46% |
| Values | Daily Returns |
Sage Potash Corp vs. Petrus Resources
Performance |
| Timeline |
| Sage Potash Corp |
| Petrus Resources |
Sage Potash and Petrus Resources Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sage Potash and Petrus Resources
The main advantage of trading using opposite Sage Potash and Petrus Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sage Potash position performs unexpectedly, Petrus 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 Petrus Resources will offset losses from the drop in Petrus Resources' long position.| Sage Potash vs. North American Construction | Sage Potash vs. Arizona Metals Corp | Sage Potash vs. Canlan Ice Sports | Sage Potash vs. TGS Esports |
| Petrus Resources vs. InPlay Oil Corp | Petrus Resources vs. Yangarra Resources | Petrus Resources vs. Pine Cliff Energy |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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