Correlation Between Bank Danamon and Bank Maybank
Can any of the company-specific risk be diversified away by investing in both Bank Danamon and Bank Maybank 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 Danamon and Bank Maybank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Danamon Indonesia and Bank Maybank Indonesia, you can compare the effects of market volatilities on Bank Danamon and Bank Maybank 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 Danamon with a short position of Bank Maybank. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Danamon and Bank Maybank.
Diversification Opportunities for Bank Danamon and Bank Maybank
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Bank and Bank is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Bank Danamon Indonesia and Bank Maybank Indonesia in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Maybank Indonesia and Bank Danamon 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 Danamon Indonesia are associated (or correlated) with Bank Maybank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Maybank Indonesia has no effect on the direction of Bank Danamon i.e., Bank Danamon and Bank Maybank go up and down completely randomly.
Pair Corralation between Bank Danamon and Bank Maybank
Assuming the 90 days trading horizon Bank Danamon Indonesia is expected to generate 0.65 times more return on investment than Bank Maybank. However, Bank Danamon Indonesia is 1.54 times less risky than Bank Maybank. It trades about -0.09 of its potential returns per unit of risk. Bank Maybank Indonesia is currently generating about -0.14 per unit of risk. If you would invest 262,000 in Bank Danamon Indonesia on September 3, 2024 and sell it today you would lose (10,000) from holding Bank Danamon Indonesia or give up 3.82% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Danamon Indonesia vs. Bank Maybank Indonesia
Performance |
Timeline |
Bank Danamon Indonesia |
Bank Maybank Indonesia |
Bank Danamon and Bank Maybank Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Danamon and Bank Maybank
The main advantage of trading using opposite Bank Danamon and Bank Maybank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Danamon position performs unexpectedly, Bank Maybank 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 Maybank will offset losses from the drop in Bank Maybank's long position.Bank Danamon vs. Paninvest Tbk | Bank Danamon vs. Mitra Pinasthika Mustika | Bank Danamon vs. Jakarta Int Hotels | Bank Danamon vs. Asuransi Harta Aman |
Bank Maybank vs. Paninvest Tbk | Bank Maybank vs. Mitra Pinasthika Mustika | Bank Maybank vs. Jakarta Int Hotels | Bank Maybank vs. Asuransi Harta Aman |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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