Correlation Between Harum Energy and Elang Mahkota
Can any of the company-specific risk be diversified away by investing in both Harum Energy 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 Harum Energy and Elang Mahkota into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Harum Energy Tbk and Elang Mahkota Teknologi, you can compare the effects of market volatilities on Harum Energy 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 Harum Energy with a short position of Elang Mahkota. Check out your portfolio center. Please also check ongoing floating volatility patterns of Harum Energy and Elang Mahkota.
Diversification Opportunities for Harum Energy and Elang Mahkota
-0.73 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Harum and Elang is -0.73. Overlapping area represents the amount of risk that can be diversified away by holding Harum Energy Tbk 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 Harum Energy 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 Harum Energy Tbk 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 Harum Energy i.e., Harum Energy and Elang Mahkota go up and down completely randomly.
Pair Corralation between Harum Energy and Elang Mahkota
Assuming the 90 days trading horizon Harum Energy Tbk is expected to under-perform the Elang Mahkota. But the stock apears to be less risky and, when comparing its historical volatility, Harum Energy Tbk is 1.7 times less risky than Elang Mahkota. The stock trades about -0.16 of its potential returns per unit of risk. The Elang Mahkota Teknologi is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 41,000 in Elang Mahkota Teknologi on September 3, 2024 and sell it today you would earn a total of 7,600 from holding Elang Mahkota Teknologi or generate 18.54% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Harum Energy Tbk vs. Elang Mahkota Teknologi
Performance |
Timeline |
Harum Energy Tbk |
Elang Mahkota Teknologi |
Harum Energy and Elang Mahkota Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Harum Energy and Elang Mahkota
The main advantage of trading using opposite Harum Energy and Elang Mahkota positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Harum Energy 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.Harum Energy vs. Weha Transportasi Indonesia | Harum Energy vs. Mitra Pinasthika Mustika | Harum Energy vs. Jakarta Int Hotels | Harum Energy vs. Asuransi Harta Aman |
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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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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