Correlation Between Bank Woori and Bank Windu
Can any of the company-specific risk be diversified away by investing in both Bank Woori and Bank Windu 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 Woori and Bank Windu into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Woori Saudara and Bank Windu Kentjana, you can compare the effects of market volatilities on Bank Woori and Bank Windu 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 Woori with a short position of Bank Windu. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Woori and Bank Windu.
Diversification Opportunities for Bank Woori and Bank Windu
-0.06 | Correlation Coefficient |
Good diversification
The 3 months correlation between Bank and Bank is -0.06. Overlapping area represents the amount of risk that can be diversified away by holding Bank Woori Saudara and Bank Windu Kentjana in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Windu Kentjana and Bank Woori 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 Woori Saudara are associated (or correlated) with Bank Windu. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Windu Kentjana has no effect on the direction of Bank Woori i.e., Bank Woori and Bank Windu go up and down completely randomly.
Pair Corralation between Bank Woori and Bank Windu
Assuming the 90 days trading horizon Bank Woori Saudara is expected to under-perform the Bank Windu. But the stock apears to be less risky and, when comparing its historical volatility, Bank Woori Saudara is 1.33 times less risky than Bank Windu. The stock trades about -0.04 of its potential returns per unit of risk. The Bank Windu Kentjana is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 7,200 in Bank Windu Kentjana on August 31, 2024 and sell it today you would earn a total of 800.00 from holding Bank Windu Kentjana or generate 11.11% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 99.72% |
| Values | Daily Returns |
Bank Woori Saudara vs. Bank Windu Kentjana
Performance |
| Timeline |
| Bank Woori Saudara |
| Bank Windu Kentjana |
Bank Woori and Bank Windu Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank Woori and Bank Windu
The main advantage of trading using opposite Bank Woori and Bank Windu positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Woori position performs unexpectedly, Bank Windu 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 Windu will offset losses from the drop in Bank Windu's long position.| Bank Woori vs. Bank Ocbc Nisp | Bank Woori vs. Bank Pan Indonesia | Bank Woori vs. Bank Mega Tbk | Bank Woori vs. Bank Mayapada Internasional |
| Bank Windu vs. Bank Mayapada Internasional | Bank Windu vs. Bank Artha Graha | Bank Windu vs. Bank Pembangunan Daerah | Bank Windu vs. Bank Mega 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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