Correlation Between Multi Bintang and Kalbe Farma
Can any of the company-specific risk be diversified away by investing in both Multi Bintang and Kalbe Farma 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 Multi Bintang and Kalbe Farma into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Multi Bintang Indonesia and Kalbe Farma Tbk, you can compare the effects of market volatilities on Multi Bintang and Kalbe Farma 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 Multi Bintang with a short position of Kalbe Farma. Check out your portfolio center. Please also check ongoing floating volatility patterns of Multi Bintang and Kalbe Farma.
Diversification Opportunities for Multi Bintang and Kalbe Farma
-0.78 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Multi and Kalbe is -0.78. Overlapping area represents the amount of risk that can be diversified away by holding Multi Bintang Indonesia and Kalbe Farma Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kalbe Farma Tbk and Multi Bintang 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 Multi Bintang Indonesia are associated (or correlated) with Kalbe Farma. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kalbe Farma Tbk has no effect on the direction of Multi Bintang i.e., Multi Bintang and Kalbe Farma go up and down completely randomly.
Pair Corralation between Multi Bintang and Kalbe Farma
Assuming the 90 days trading horizon Multi Bintang Indonesia is expected to generate 0.56 times more return on investment than Kalbe Farma. However, Multi Bintang Indonesia is 1.77 times less risky than Kalbe Farma. It trades about -0.06 of its potential returns per unit of risk. Kalbe Farma Tbk is currently generating about -0.04 per unit of risk. If you would invest 768,971 in Multi Bintang Indonesia on August 31, 2024 and sell it today you would lose (146,471) from holding Multi Bintang Indonesia or give up 19.05% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Multi Bintang Indonesia vs. Kalbe Farma Tbk
Performance |
| Timeline |
| Multi Bintang Indonesia |
| Kalbe Farma Tbk |
Multi Bintang and Kalbe Farma Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Multi Bintang and Kalbe Farma
The main advantage of trading using opposite Multi Bintang and Kalbe Farma positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Multi Bintang position performs unexpectedly, Kalbe Farma 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 Kalbe Farma will offset losses from the drop in Kalbe Farma's long position.| Multi Bintang vs. Delta Djakarta Tbk | Multi Bintang vs. Merck Tbk | Multi Bintang vs. Mayora Indah Tbk | Multi Bintang vs. Ultra Jaya Milk |
| Kalbe Farma vs. PT Indofood Sukses | Kalbe Farma vs. Unilever Indonesia Tbk | Kalbe Farma vs. Semen Indonesia Persero | Kalbe Farma vs. United Tractors 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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