Correlation Between Bank Central and Pertamina Geothermal
Can any of the company-specific risk be diversified away by investing in both Bank Central and Pertamina Geothermal 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 Bank Central and Pertamina Geothermal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Central Asia and Pertamina Geothermal Energy, you can compare the effects of market volatilities on Bank Central and Pertamina Geothermal 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 Bank Central with a short position of Pertamina Geothermal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Central and Pertamina Geothermal.
Diversification Opportunities for Bank Central and Pertamina Geothermal
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and Pertamina is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Bank Central Asia and Pertamina Geothermal Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pertamina Geothermal and Bank Central 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 Bank Central Asia are associated (or correlated) with Pertamina Geothermal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pertamina Geothermal has no effect on the direction of Bank Central i.e., Bank Central and Pertamina Geothermal go up and down completely randomly.
Pair Corralation between Bank Central and Pertamina Geothermal
Assuming the 90 days trading horizon Bank Central Asia is expected to generate 0.84 times more return on investment than Pertamina Geothermal. However, Bank Central Asia is 1.19 times less risky than Pertamina Geothermal. It trades about -0.06 of its potential returns per unit of risk. Pertamina Geothermal Energy is currently generating about -0.28 per unit of risk. If you would invest 1,019,913 in Bank Central Asia on September 1, 2024 and sell it today you would lose (19,913) from holding Bank Central Asia or give up 1.95% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Central Asia vs. Pertamina Geothermal Energy
Performance |
Timeline |
Bank Central Asia |
Pertamina Geothermal |
Bank Central and Pertamina Geothermal Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Central and Pertamina Geothermal
The main advantage of trading using opposite Bank Central and Pertamina Geothermal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Central position performs unexpectedly, Pertamina Geothermal 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 Pertamina Geothermal will offset losses from the drop in Pertamina Geothermal's long position.Bank Central vs. Bank Rakyat Indonesia | Bank Central vs. Bank Mandiri Persero | Bank Central vs. Bank Negara Indonesia | Bank Central vs. Astra International Tbk |
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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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