Correlation Between Hartadinata Abadi and Panca Mitra
Can any of the company-specific risk be diversified away by investing in both Hartadinata Abadi and Panca 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 Hartadinata Abadi and Panca Mitra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hartadinata Abadi Tbk and Panca Mitra Multiperdana, you can compare the effects of market volatilities on Hartadinata Abadi and Panca 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 Hartadinata Abadi with a short position of Panca Mitra. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hartadinata Abadi and Panca Mitra.
Diversification Opportunities for Hartadinata Abadi and Panca Mitra
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Hartadinata and Panca is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding Hartadinata Abadi Tbk and Panca Mitra Multiperdana in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Panca Mitra Multiperdana and Hartadinata Abadi 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 Hartadinata Abadi Tbk are associated (or correlated) with Panca Mitra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Panca Mitra Multiperdana has no effect on the direction of Hartadinata Abadi i.e., Hartadinata Abadi and Panca Mitra go up and down completely randomly.
Pair Corralation between Hartadinata Abadi and Panca Mitra
Assuming the 90 days trading horizon Hartadinata Abadi Tbk is expected to generate 0.49 times more return on investment than Panca Mitra. However, Hartadinata Abadi Tbk is 2.03 times less risky than Panca Mitra. It trades about -0.04 of its potential returns per unit of risk. Panca Mitra Multiperdana is currently generating about -0.17 per unit of risk. If you would invest 38,600 in Hartadinata Abadi Tbk on September 17, 2024 and sell it today you would lose (3,200) from holding Hartadinata Abadi Tbk or give up 8.29% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Hartadinata Abadi Tbk vs. Panca Mitra Multiperdana
Performance |
Timeline |
Hartadinata Abadi Tbk |
Panca Mitra Multiperdana |
Hartadinata Abadi and Panca Mitra Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hartadinata Abadi and Panca Mitra
The main advantage of trading using opposite Hartadinata Abadi and Panca Mitra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hartadinata Abadi position performs unexpectedly, Panca 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 Panca Mitra will offset losses from the drop in Panca Mitra's long position.Hartadinata Abadi vs. Pembangunan Graha Lestari | Hartadinata Abadi vs. Pembangunan Jaya Ancol | Hartadinata Abadi vs. Hotel Sahid Jaya | Hartadinata Abadi 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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