Correlation Between Hanjaya Mandala and Asuransi Bintang
Can any of the company-specific risk be diversified away by investing in both Hanjaya Mandala and Asuransi Bintang 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 Hanjaya Mandala and Asuransi Bintang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hanjaya Mandala Sampoerna and Asuransi Bintang Tbk, you can compare the effects of market volatilities on Hanjaya Mandala and Asuransi Bintang 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 Hanjaya Mandala with a short position of Asuransi Bintang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hanjaya Mandala and Asuransi Bintang.
Diversification Opportunities for Hanjaya Mandala and Asuransi Bintang
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hanjaya and Asuransi is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Hanjaya Mandala Sampoerna and Asuransi Bintang Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Asuransi Bintang Tbk and Hanjaya Mandala 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 Hanjaya Mandala Sampoerna are associated (or correlated) with Asuransi Bintang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Asuransi Bintang Tbk has no effect on the direction of Hanjaya Mandala i.e., Hanjaya Mandala and Asuransi Bintang go up and down completely randomly.
Pair Corralation between Hanjaya Mandala and Asuransi Bintang
Assuming the 90 days trading horizon Hanjaya Mandala Sampoerna is expected to generate 0.13 times more return on investment than Asuransi Bintang. However, Hanjaya Mandala Sampoerna is 7.42 times less risky than Asuransi Bintang. It trades about -0.23 of its potential returns per unit of risk. Asuransi Bintang Tbk is currently generating about -0.11 per unit of risk. If you would invest 69,000 in Hanjaya Mandala Sampoerna on September 1, 2024 and sell it today you would lose (4,000) from holding Hanjaya Mandala Sampoerna or give up 5.8% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 95.45% |
Values | Daily Returns |
Hanjaya Mandala Sampoerna vs. Asuransi Bintang Tbk
Performance |
Timeline |
Hanjaya Mandala Sampoerna |
Asuransi Bintang Tbk |
Hanjaya Mandala and Asuransi Bintang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hanjaya Mandala and Asuransi Bintang
The main advantage of trading using opposite Hanjaya Mandala and Asuransi Bintang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hanjaya Mandala position performs unexpectedly, Asuransi Bintang 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 Asuransi Bintang will offset losses from the drop in Asuransi Bintang's long position.Hanjaya Mandala vs. Gudang Garam Tbk | Hanjaya Mandala vs. Unilever Indonesia Tbk | Hanjaya Mandala vs. Indofood Cbp Sukses | Hanjaya Mandala vs. PT Indofood Sukses |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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