Correlation Between Mountain Province and Bonterra Energy
Can any of the company-specific risk be diversified away by investing in both Mountain Province and Bonterra Energy 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 Mountain Province and Bonterra Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mountain Province Diamonds and Bonterra Energy Corp, you can compare the effects of market volatilities on Mountain Province and Bonterra Energy 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 Mountain Province with a short position of Bonterra Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mountain Province and Bonterra Energy.
Diversification Opportunities for Mountain Province and Bonterra Energy
0.75 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mountain and Bonterra is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Mountain Province Diamonds and Bonterra Energy Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bonterra Energy Corp and Mountain Province 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 Mountain Province Diamonds are associated (or correlated) with Bonterra Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bonterra Energy Corp has no effect on the direction of Mountain Province i.e., Mountain Province and Bonterra Energy go up and down completely randomly.
Pair Corralation between Mountain Province and Bonterra Energy
Assuming the 90 days trading horizon Mountain Province Diamonds is expected to under-perform the Bonterra Energy. In addition to that, Mountain Province is 2.07 times more volatile than Bonterra Energy Corp. It trades about -0.08 of its total potential returns per unit of risk. Bonterra Energy Corp is currently generating about -0.06 per unit of volatility. If you would invest 271.00 in Bonterra Energy Corp on September 29, 2024 and sell it today you would lose (32.00) from holding Bonterra Energy Corp or give up 11.81% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.44% |
Values | Daily Returns |
Mountain Province Diamonds vs. Bonterra Energy Corp
Performance |
Timeline |
Mountain Province |
Bonterra Energy Corp |
Mountain Province and Bonterra Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mountain Province and Bonterra Energy
The main advantage of trading using opposite Mountain Province and Bonterra Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mountain Province position performs unexpectedly, Bonterra Energy 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 Bonterra Energy will offset losses from the drop in Bonterra Energy's long position.Mountain Province vs. Precipitate Gold Corp | Mountain Province vs. ROKMASTER Resources Corp | Mountain Province vs. Rugby Mining Limited |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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