Correlation Between Langgeng Makmur and Elang Mahkota
Can any of the company-specific risk be diversified away by investing in both Langgeng Makmur and Elang Mahkota 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 Langgeng Makmur and Elang Mahkota into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Langgeng Makmur Industri and Elang Mahkota Teknologi, you can compare the effects of market volatilities on Langgeng Makmur and Elang Mahkota 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 Langgeng Makmur with a short position of Elang Mahkota. Check out your portfolio center. Please also check ongoing floating volatility patterns of Langgeng Makmur and Elang Mahkota.
Diversification Opportunities for Langgeng Makmur and Elang Mahkota
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Langgeng and Elang is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Langgeng Makmur Industri and Elang Mahkota Teknologi in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Elang Mahkota Teknologi and Langgeng Makmur 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 Langgeng Makmur Industri are associated (or correlated) with Elang Mahkota. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Elang Mahkota Teknologi has no effect on the direction of Langgeng Makmur i.e., Langgeng Makmur and Elang Mahkota go up and down completely randomly.
Pair Corralation between Langgeng Makmur and Elang Mahkota
Assuming the 90 days trading horizon Langgeng Makmur Industri is expected to generate 5.81 times more return on investment than Elang Mahkota. However, Langgeng Makmur is 5.81 times more volatile than Elang Mahkota Teknologi. It trades about 0.18 of its potential returns per unit of risk. Elang Mahkota Teknologi is currently generating about 0.02 per unit of risk. If you would invest 11,300 in Langgeng Makmur Industri on August 27, 2024 and sell it today you would earn a total of 6,900 from holding Langgeng Makmur Industri or generate 61.06% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Langgeng Makmur Industri vs. Elang Mahkota Teknologi
Performance |
Timeline |
Langgeng Makmur Industri |
Elang Mahkota Teknologi |
Langgeng Makmur and Elang Mahkota Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Langgeng Makmur and Elang Mahkota
The main advantage of trading using opposite Langgeng Makmur and Elang Mahkota positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Langgeng Makmur position performs unexpectedly, Elang Mahkota 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 Elang Mahkota will offset losses from the drop in Elang Mahkota's long position.Langgeng Makmur vs. Kedaung Indah Can | Langgeng Makmur vs. Kedawung Setia Industrial | Langgeng Makmur vs. Mustika Ratu Tbk | Langgeng Makmur vs. Pyridam Farma Tbk |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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