Correlation Between Mitra Pinasthika and Bintang Mitra
Can any of the company-specific risk be diversified away by investing in both Mitra Pinasthika and Bintang Mitra 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 Mitra Pinasthika and Bintang Mitra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mitra Pinasthika Mustika and Bintang Mitra Semestaraya, you can compare the effects of market volatilities on Mitra Pinasthika and Bintang Mitra 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 Mitra Pinasthika with a short position of Bintang Mitra. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitra Pinasthika and Bintang Mitra.
Diversification Opportunities for Mitra Pinasthika and Bintang Mitra
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mitra and Bintang is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Mitra Pinasthika Mustika and Bintang Mitra Semestaraya in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bintang Mitra Semestaraya and Mitra Pinasthika 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 Mitra Pinasthika Mustika are associated (or correlated) with Bintang Mitra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bintang Mitra Semestaraya has no effect on the direction of Mitra Pinasthika i.e., Mitra Pinasthika and Bintang Mitra go up and down completely randomly.
Pair Corralation between Mitra Pinasthika and Bintang Mitra
Assuming the 90 days trading horizon Mitra Pinasthika Mustika is expected to generate 0.33 times more return on investment than Bintang Mitra. However, Mitra Pinasthika Mustika is 2.99 times less risky than Bintang Mitra. It trades about -0.11 of its potential returns per unit of risk. Bintang Mitra Semestaraya is currently generating about -0.04 per unit of risk. If you would invest 103,000 in Mitra Pinasthika Mustika on September 13, 2024 and sell it today you would lose (3,500) from holding Mitra Pinasthika Mustika or give up 3.4% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Mitra Pinasthika Mustika vs. Bintang Mitra Semestaraya
Performance |
Timeline |
Mitra Pinasthika Mustika |
Bintang Mitra Semestaraya |
Mitra Pinasthika and Bintang Mitra Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitra Pinasthika and Bintang Mitra
The main advantage of trading using opposite Mitra Pinasthika and Bintang Mitra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitra Pinasthika position performs unexpectedly, Bintang Mitra 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 Bintang Mitra will offset losses from the drop in Bintang Mitra's long position.Mitra Pinasthika vs. Pembangunan Graha Lestari | Mitra Pinasthika vs. Pembangunan Jaya Ancol | Mitra Pinasthika vs. Hotel Sahid Jaya | Mitra Pinasthika vs. Mitrabara Adiperdana PT |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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