Correlation Between Bank Rakyat and Mustika Ratu
Can any of the company-specific risk be diversified away by investing in both Bank Rakyat and Mustika Ratu 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 Rakyat and Mustika Ratu into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank Rakyat Indonesia and Mustika Ratu Tbk, you can compare the effects of market volatilities on Bank Rakyat and Mustika Ratu 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 Rakyat with a short position of Mustika Ratu. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank Rakyat and Mustika Ratu.
Diversification Opportunities for Bank Rakyat and Mustika Ratu
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Bank and Mustika is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding Bank Rakyat Indonesia and Mustika Ratu Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mustika Ratu Tbk and Bank Rakyat 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 Rakyat Indonesia are associated (or correlated) with Mustika Ratu. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mustika Ratu Tbk has no effect on the direction of Bank Rakyat i.e., Bank Rakyat and Mustika Ratu go up and down completely randomly.
Pair Corralation between Bank Rakyat and Mustika Ratu
Assuming the 90 days trading horizon Bank Rakyat Indonesia is expected to generate 0.91 times more return on investment than Mustika Ratu. However, Bank Rakyat Indonesia is 1.1 times less risky than Mustika Ratu. It trades about -0.21 of its potential returns per unit of risk. Mustika Ratu Tbk is currently generating about -0.24 per unit of risk. If you would invest 530,000 in Bank Rakyat Indonesia on September 15, 2024 and sell it today you would lose (110,000) from holding Bank Rakyat Indonesia or give up 20.75% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Bank Rakyat Indonesia vs. Mustika Ratu Tbk
Performance |
Timeline |
Bank Rakyat Indonesia |
Mustika Ratu Tbk |
Bank Rakyat and Mustika Ratu Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank Rakyat and Mustika Ratu
The main advantage of trading using opposite Bank Rakyat and Mustika Ratu positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank Rakyat position performs unexpectedly, Mustika Ratu 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 Mustika Ratu will offset losses from the drop in Mustika Ratu's long position.Bank Rakyat vs. Bank Central Asia | Bank Rakyat vs. Bank Mandiri Persero | Bank Rakyat vs. Bank Negara Indonesia | Bank Rakyat vs. Telkom Indonesia Tbk |
Mustika Ratu vs. Austindo Nusantara Jaya | Mustika Ratu vs. Garudafood Putra Putri | Mustika Ratu vs. Provident Agro Tbk | Mustika Ratu vs. Dharma Satya Nusantara |
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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