Correlation Between Postmedia Network and Nicola Mining
Can any of the company-specific risk be diversified away by investing in both Postmedia Network and Nicola Mining 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 Postmedia Network and Nicola Mining into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Postmedia Network Canada and Nicola Mining, you can compare the effects of market volatilities on Postmedia Network and Nicola Mining 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 Postmedia Network with a short position of Nicola Mining. Check out your portfolio center. Please also check ongoing floating volatility patterns of Postmedia Network and Nicola Mining.
Diversification Opportunities for Postmedia Network and Nicola Mining
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Postmedia and Nicola is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Postmedia Network Canada and Nicola Mining in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nicola Mining and Postmedia Network 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 Postmedia Network Canada are associated (or correlated) with Nicola Mining. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nicola Mining has no effect on the direction of Postmedia Network i.e., Postmedia Network and Nicola Mining go up and down completely randomly.
Pair Corralation between Postmedia Network and Nicola Mining
Assuming the 90 days trading horizon Postmedia Network is expected to generate 1.17 times less return on investment than Nicola Mining. But when comparing it to its historical volatility, Postmedia Network Canada is 1.23 times less risky than Nicola Mining. It trades about 0.03 of its potential returns per unit of risk. Nicola Mining is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 32.00 in Nicola Mining on August 31, 2024 and sell it today you would lose (5.00) from holding Nicola Mining or give up 15.62% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 99.73% |
Values | Daily Returns |
Postmedia Network Canada vs. Nicola Mining
Performance |
Timeline |
Postmedia Network Canada |
Nicola Mining |
Postmedia Network and Nicola Mining Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Postmedia Network and Nicola Mining
The main advantage of trading using opposite Postmedia Network and Nicola Mining positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Postmedia Network position performs unexpectedly, Nicola Mining 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 Nicola Mining will offset losses from the drop in Nicola Mining's long position.Postmedia Network vs. Cielo Waste Solutions | Postmedia Network vs. Eros Resources Corp | Postmedia Network vs. Forstrong Global Income | Postmedia Network vs. iShares Canadian HYBrid |
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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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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