Correlation Between PT Indofood and Bima Sakti
Can any of the company-specific risk be diversified away by investing in both PT Indofood and Bima Sakti 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 Indofood and Bima Sakti into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PT Indofood Sukses and Bima Sakti Pertiwi, you can compare the effects of market volatilities on PT Indofood and Bima Sakti 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 Indofood with a short position of Bima Sakti. Check out your portfolio center. Please also check ongoing floating volatility patterns of PT Indofood and Bima Sakti.
Diversification Opportunities for PT Indofood and Bima Sakti
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between INDF and Bima is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding PT Indofood Sukses and Bima Sakti Pertiwi in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bima Sakti Pertiwi and PT Indofood 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 Indofood Sukses are associated (or correlated) with Bima Sakti. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bima Sakti Pertiwi has no effect on the direction of PT Indofood i.e., PT Indofood and Bima Sakti go up and down completely randomly.
Pair Corralation between PT Indofood and Bima Sakti
Assuming the 90 days trading horizon PT Indofood Sukses is expected to generate 0.99 times more return on investment than Bima Sakti. However, PT Indofood Sukses is 1.01 times less risky than Bima Sakti. It trades about 0.12 of its potential returns per unit of risk. Bima Sakti Pertiwi is currently generating about -0.01 per unit of risk. If you would invest 677,500 in PT Indofood Sukses on September 3, 2024 and sell it today you would earn a total of 77,500 from holding PT Indofood Sukses or generate 11.44% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
PT Indofood Sukses vs. Bima Sakti Pertiwi
Performance |
| Timeline |
| PT Indofood Sukses |
| Bima Sakti Pertiwi |
PT Indofood and Bima Sakti Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with PT Indofood and Bima Sakti
The main advantage of trading using opposite PT Indofood and Bima Sakti positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PT Indofood position performs unexpectedly, Bima Sakti 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 Bima Sakti will offset losses from the drop in Bima Sakti's long position.| PT Indofood vs. Astra International Tbk | PT Indofood vs. Unilever Indonesia Tbk | PT Indofood vs. Telkom Indonesia Tbk | PT Indofood vs. Bank Mandiri Persero |
| Bima Sakti vs. Prima Alloy Steel | Bima Sakti vs. Weha Transportasi Indonesia | Bima Sakti vs. PT Indofood Sukses | Bima Sakti vs. Trinitan Metals and |
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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