Correlation Between Cardinal Energy and Melbana Energy
Can any of the company-specific risk be diversified away by investing in both Cardinal Energy and Melbana 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 Cardinal Energy and Melbana Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cardinal Energy and Melbana Energy Limited, you can compare the effects of market volatilities on Cardinal Energy and Melbana 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 Cardinal Energy with a short position of Melbana Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cardinal Energy and Melbana Energy.
Diversification Opportunities for Cardinal Energy and Melbana Energy
-0.47 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Cardinal and Melbana is -0.47. Overlapping area represents the amount of risk that can be diversified away by holding Cardinal Energy and Melbana Energy Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Melbana Energy and Cardinal Energy 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 Cardinal Energy are associated (or correlated) with Melbana Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Melbana Energy has no effect on the direction of Cardinal Energy i.e., Cardinal Energy and Melbana Energy go up and down completely randomly.
Pair Corralation between Cardinal Energy and Melbana Energy
Assuming the 90 days horizon Cardinal Energy is expected to generate 159.17 times less return on investment than Melbana Energy. But when comparing it to its historical volatility, Cardinal Energy is 12.41 times less risky than Melbana Energy. It trades about 0.01 of its potential returns per unit of risk. Melbana Energy Limited is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest 0.20 in Melbana Energy Limited on December 30, 2024 and sell it today you would earn a total of 0.30 from holding Melbana Energy Limited or generate 150.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Cardinal Energy vs. Melbana Energy Limited
Performance |
Timeline |
Cardinal Energy |
Melbana Energy |
Cardinal Energy and Melbana Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cardinal Energy and Melbana Energy
The main advantage of trading using opposite Cardinal Energy and Melbana Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cardinal Energy position performs unexpectedly, Melbana 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 Melbana Energy will offset losses from the drop in Melbana Energy's long position.Cardinal Energy vs. Tamarack Valley Energy | Cardinal Energy vs. Pine Cliff Energy | Cardinal Energy vs. MEG Energy Corp | Cardinal Energy vs. Headwater Exploration |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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