Correlation Between Bank Capital and Bank Artha
Can any of the company-specific risk be diversified away by investing in both Bank Capital and Bank Artha 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 Capital and Bank Artha into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Capital Indonesia and Bank Artha Graha, you can compare the effects of market volatilities on Bank Capital and Bank Artha 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 Capital with a short position of Bank Artha. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Capital and Bank Artha.
Diversification Opportunities for Bank Capital and Bank Artha
-0.32 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Bank and Bank is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding Bank Capital Indonesia and Bank Artha Graha in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Artha Graha and Bank Capital 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 Capital Indonesia are associated (or correlated) with Bank Artha. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Artha Graha has no effect on the direction of Bank Capital i.e., Bank Capital and Bank Artha go up and down completely randomly.
Pair Corralation between Bank Capital and Bank Artha
Assuming the 90 days trading horizon Bank Capital Indonesia is expected to generate 0.05 times more return on investment than Bank Artha. However, Bank Capital Indonesia is 20.44 times less risky than Bank Artha. It trades about 0.09 of its potential returns per unit of risk. Bank Artha Graha is currently generating about -0.07 per unit of risk. If you would invest 13,000 in Bank Capital Indonesia on October 26, 2024 and sell it today you would earn a total of 100.00 from holding Bank Capital Indonesia or generate 0.77% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bank Capital Indonesia vs. Bank Artha Graha
Performance |
| Timeline |
| Bank Capital Indonesia |
| Bank Artha Graha |
Bank Capital and Bank Artha Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank Capital and Bank Artha
The main advantage of trading using opposite Bank Capital and Bank Artha positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Capital position performs unexpectedly, Bank Artha 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 Bank Artha will offset losses from the drop in Bank Artha's long position.| Bank Capital vs. Bank Mnc Internasional | Bank Capital vs. Bank Qnb Indonesia | Bank Capital vs. Bank Victoria International | Bank Capital vs. Bank Rakyat Indonesia |
| Bank Artha vs. Bank Victoria International | Bank Artha vs. Bank Bumi Arta | Bank Artha vs. Bank Mnc Internasional | Bank Artha vs. Bank Qnb Indonesia |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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