Correlation Between Harum Energy and Bayan Resources
Can any of the company-specific risk be diversified away by investing in both Harum Energy and Bayan 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 Harum Energy and Bayan Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Harum Energy Tbk and Bayan Resources Tbk, you can compare the effects of market volatilities on Harum Energy and Bayan 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 Harum Energy with a short position of Bayan Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Harum Energy and Bayan Resources.
Diversification Opportunities for Harum Energy and Bayan Resources
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Harum and Bayan is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Harum Energy Tbk and Bayan Resources Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bayan Resources Tbk and Harum 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 Harum Energy Tbk are associated (or correlated) with Bayan Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bayan Resources Tbk has no effect on the direction of Harum Energy i.e., Harum Energy and Bayan Resources go up and down completely randomly.
Pair Corralation between Harum Energy and Bayan Resources
Assuming the 90 days trading horizon Harum Energy Tbk is expected to under-perform the Bayan Resources. In addition to that, Harum Energy is 3.03 times more volatile than Bayan Resources Tbk. It trades about -0.25 of its total potential returns per unit of risk. Bayan Resources Tbk is currently generating about -0.02 per unit of volatility. If you would invest 2,025,000 in Bayan Resources Tbk on December 30, 2024 and sell it today you would lose (22,500) from holding Bayan Resources Tbk or give up 1.11% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Harum Energy Tbk vs. Bayan Resources Tbk
Performance |
Timeline |
Harum Energy Tbk |
Bayan Resources Tbk |
Harum Energy and Bayan Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Harum Energy and Bayan Resources
The main advantage of trading using opposite Harum Energy and Bayan Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Harum Energy position performs unexpectedly, Bayan 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 Bayan Resources will offset losses from the drop in Bayan Resources' long position.Harum Energy vs. Indo Tambangraya Megah | Harum Energy vs. Indika Energy Tbk | Harum Energy vs. Adaro Energy Tbk | Harum Energy vs. Akr Corporindo Tbk |
Bayan Resources vs. Indo Tambangraya Megah | Bayan Resources vs. Indika Energy Tbk | Bayan Resources vs. Darma Henwa Tbk | Bayan Resources vs. Harum Energy Tbk |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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