Correlation Between Chandra Asri and Mitra Keluarga
Can any of the company-specific risk be diversified away by investing in both Chandra Asri and Mitra Keluarga 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 Chandra Asri and Mitra Keluarga into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Chandra Asri Petrochemical and Mitra Keluarga Karyasehat, you can compare the effects of market volatilities on Chandra Asri and Mitra Keluarga 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 Chandra Asri with a short position of Mitra Keluarga. Check out your portfolio center. Please also check ongoing floating volatility patterns of Chandra Asri and Mitra Keluarga.
Diversification Opportunities for Chandra Asri and Mitra Keluarga
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Chandra and Mitra is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Chandra Asri Petrochemical and Mitra Keluarga Karyasehat in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mitra Keluarga Karyasehat and Chandra Asri 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 Chandra Asri Petrochemical are associated (or correlated) with Mitra Keluarga. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mitra Keluarga Karyasehat has no effect on the direction of Chandra Asri i.e., Chandra Asri and Mitra Keluarga go up and down completely randomly.
Pair Corralation between Chandra Asri and Mitra Keluarga
Assuming the 90 days trading horizon Chandra Asri Petrochemical is expected to generate 3.0 times more return on investment than Mitra Keluarga. However, Chandra Asri is 3.0 times more volatile than Mitra Keluarga Karyasehat. It trades about 0.15 of its potential returns per unit of risk. Mitra Keluarga Karyasehat is currently generating about -0.24 per unit of risk. If you would invest 682,500 in Chandra Asri Petrochemical on September 15, 2024 and sell it today you would earn a total of 97,500 from holding Chandra Asri Petrochemical or generate 14.29% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 95.45% |
Values | Daily Returns |
Chandra Asri Petrochemical vs. Mitra Keluarga Karyasehat
Performance |
Timeline |
Chandra Asri Petroch |
Mitra Keluarga Karyasehat |
Chandra Asri and Mitra Keluarga Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Chandra Asri and Mitra Keluarga
The main advantage of trading using opposite Chandra Asri and Mitra Keluarga positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Chandra Asri position performs unexpectedly, Mitra Keluarga 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 Mitra Keluarga will offset losses from the drop in Mitra Keluarga's long position.Chandra Asri vs. Barito Pacific Tbk | Chandra Asri vs. Pabrik Kertas Tjiwi | Chandra Asri vs. Charoen Pokphand Indonesia | Chandra Asri vs. Indah Kiat Pulp |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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