Correlation Between Langgeng Makmur and Bank Pan
Can any of the company-specific risk be diversified away by investing in both Langgeng Makmur and Bank Pan 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 Bank Pan 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 Bank Pan Indonesia, you can compare the effects of market volatilities on Langgeng Makmur and Bank Pan 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 Bank Pan. Check out your portfolio center. Please also check ongoing floating volatility patterns of Langgeng Makmur and Bank Pan.
Diversification Opportunities for Langgeng Makmur and Bank Pan
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Langgeng and Bank is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Langgeng Makmur Industri and Bank Pan Indonesia in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bank Pan Indonesia 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 Bank Pan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bank Pan Indonesia has no effect on the direction of Langgeng Makmur i.e., Langgeng Makmur and Bank Pan go up and down completely randomly.
Pair Corralation between Langgeng Makmur and Bank Pan
Assuming the 90 days trading horizon Langgeng Makmur Industri is expected to generate 5.35 times more return on investment than Bank Pan. However, Langgeng Makmur is 5.35 times more volatile than Bank Pan Indonesia. It trades about 0.17 of its potential returns per unit of risk. Bank Pan Indonesia is currently generating about -0.15 per unit of risk. If you would invest 11,400 in Langgeng Makmur Industri on August 30, 2024 and sell it today you would earn a total of 4,000 from holding Langgeng Makmur Industri or generate 35.09% 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. Bank Pan Indonesia
Performance |
| Timeline |
| Langgeng Makmur Industri |
| Bank Pan Indonesia |
Langgeng Makmur and Bank Pan Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Langgeng Makmur and Bank Pan
The main advantage of trading using opposite Langgeng Makmur and Bank Pan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Langgeng Makmur position performs unexpectedly, Bank Pan 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 Bank Pan will offset losses from the drop in Bank Pan'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 |
| Bank Pan vs. Bank Danamon Indonesia | Bank Pan vs. Bank Cimb Niaga | Bank Pan vs. Panin Financial Tbk | Bank Pan vs. Bank Maybank Indonesia |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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