Correlation Between PT Anugerah and Bank Rakyat
Can any of the company-specific risk be diversified away by investing in both PT Anugerah and Bank Rakyat 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 Anugerah and Bank Rakyat into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PT Anugerah Spareparts and Bank Rakyat Indonesia, you can compare the effects of market volatilities on PT Anugerah and Bank Rakyat 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 Anugerah with a short position of Bank Rakyat. Check out your portfolio center. Please also check ongoing floating volatility patterns of PT Anugerah and Bank Rakyat.
Diversification Opportunities for PT Anugerah and Bank Rakyat
0.19 | Correlation Coefficient |
Average diversification
The 3 months correlation between AEGS and Bank is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding PT Anugerah Spareparts and Bank Rakyat Indonesia in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Rakyat Indonesia and PT Anugerah 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 Anugerah Spareparts are associated (or correlated) with Bank Rakyat. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Rakyat Indonesia has no effect on the direction of PT Anugerah i.e., PT Anugerah and Bank Rakyat go up and down completely randomly.
Pair Corralation between PT Anugerah and Bank Rakyat
Assuming the 90 days trading horizon PT Anugerah Spareparts is expected to under-perform the Bank Rakyat. In addition to that, PT Anugerah is 3.32 times more volatile than Bank Rakyat Indonesia. It trades about -0.04 of its total potential returns per unit of risk. Bank Rakyat Indonesia is currently generating about 0.01 per unit of volatility. If you would invest 406,412 in Bank Rakyat Indonesia on September 3, 2024 and sell it today you would earn a total of 11,588 from holding Bank Rakyat Indonesia or generate 2.85% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 65.49% |
| Values | Daily Returns |
PT Anugerah Spareparts vs. Bank Rakyat Indonesia
Performance |
| Timeline |
| PT Anugerah Spareparts |
| Bank Rakyat Indonesia |
PT Anugerah and Bank Rakyat Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with PT Anugerah and Bank Rakyat
The main advantage of trading using opposite PT Anugerah and Bank Rakyat positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PT Anugerah position performs unexpectedly, Bank Rakyat 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 Rakyat will offset losses from the drop in Bank Rakyat's long position.| PT Anugerah vs. PT UBC Medical | PT Anugerah vs. City Retail Developments | PT Anugerah vs. Media Nusantara Citra | PT Anugerah vs. Indosterling Technomedia Tbk |
| Bank Rakyat vs. Paninvest Tbk | Bank Rakyat vs. Mitra Pinasthika Mustika | Bank Rakyat vs. Jakarta Int Hotels | Bank Rakyat 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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