Correlation Between Medikaloka Hermina and PT MNC
Can any of the company-specific risk be diversified away by investing in both Medikaloka Hermina and PT MNC 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 Medikaloka Hermina and PT MNC into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Medikaloka Hermina PT and PT MNC Energy, you can compare the effects of market volatilities on Medikaloka Hermina and PT MNC 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 Medikaloka Hermina with a short position of PT MNC. Check out your portfolio center. Please also check ongoing floating volatility patterns of Medikaloka Hermina and PT MNC.
Diversification Opportunities for Medikaloka Hermina and PT MNC
-0.51 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Medikaloka and IATA is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding Medikaloka Hermina PT and PT MNC Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PT MNC Energy and Medikaloka Hermina 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 Medikaloka Hermina PT are associated (or correlated) with PT MNC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PT MNC Energy has no effect on the direction of Medikaloka Hermina i.e., Medikaloka Hermina and PT MNC go up and down completely randomly.
Pair Corralation between Medikaloka Hermina and PT MNC
Assuming the 90 days trading horizon Medikaloka Hermina is expected to generate 1.06 times less return on investment than PT MNC. But when comparing it to its historical volatility, Medikaloka Hermina PT is 2.57 times less risky than PT MNC. It trades about 0.08 of its potential returns per unit of risk. PT MNC Energy is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 4,100 in PT MNC Energy on September 1, 2024 and sell it today you would earn a total of 300.00 from holding PT MNC Energy or generate 7.32% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 99.21% |
| Values | Daily Returns |
Medikaloka Hermina PT vs. PT MNC Energy
Performance |
| Timeline |
| Medikaloka Hermina |
| PT MNC Energy |
Medikaloka Hermina and PT MNC Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Medikaloka Hermina and PT MNC
The main advantage of trading using opposite Medikaloka Hermina and PT MNC positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Medikaloka Hermina position performs unexpectedly, PT MNC 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 PT MNC will offset losses from the drop in PT MNC's long position.| Medikaloka Hermina vs. Matahari Department Store | Medikaloka Hermina vs. Surya Citra Media | Medikaloka Hermina vs. Lippo Karawaci Tbk |
| PT MNC vs. Mnc Investama Tbk | PT MNC vs. Exploitasi Energi Indonesia | PT MNC vs. Smartfren Telecom Tbk | PT MNC vs. Humpuss Intermoda Transportasi |
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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