Correlation Between PT Bank and Active Health
Can any of the company-specific risk be diversified away by investing in both PT Bank and Active Health 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 PT Bank and Active Health into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PT Bank Rakyat and Active Health Foods, you can compare the effects of market volatilities on PT Bank and Active Health 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 PT Bank with a short position of Active Health. Check out your portfolio center. Please also check ongoing floating volatility patterns of PT Bank and Active Health.
Diversification Opportunities for PT Bank and Active Health
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between BKRKF and Active is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding PT Bank Rakyat and Active Health Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Active Health Foods and PT Bank 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 PT Bank Rakyat are associated (or correlated) with Active Health. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Active Health Foods has no effect on the direction of PT Bank i.e., PT Bank and Active Health go up and down completely randomly.
Pair Corralation between PT Bank and Active Health
Assuming the 90 days horizon PT Bank is expected to generate 22.43 times less return on investment than Active Health. But when comparing it to its historical volatility, PT Bank Rakyat is 9.37 times less risky than Active Health. It trades about 0.03 of its potential returns per unit of risk. Active Health Foods is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 0.03 in Active Health Foods on August 29, 2024 and sell it today you would lose (0.02) from holding Active Health Foods or give up 66.67% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 81.85% |
| Values | Daily Returns |
PT Bank Rakyat vs. Active Health Foods
Performance |
| Timeline |
| PT Bank Rakyat |
| Active Health Foods |
PT Bank and Active Health Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with PT Bank and Active Health
The main advantage of trading using opposite PT Bank and Active Health positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PT Bank position performs unexpectedly, Active Health 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 Active Health will offset losses from the drop in Active Health's long position.| PT Bank vs. Bank Mandiri Persero | PT Bank vs. Piraeus Bank SA | PT Bank vs. Eurobank Ergasias Services | PT Bank vs. Kasikornbank Public Co |
| Active Health vs. Embotelladora Andina SA | Active Health vs. Signet International Holdings | Active Health vs. National Beverage Corp | Active Health vs. PT Astra International |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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