Correlation Between Darma Henwa and Sumber Global
Can any of the company-specific risk be diversified away by investing in both Darma Henwa and Sumber Global 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 Darma Henwa and Sumber Global into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Darma Henwa Tbk and Sumber Global Energy, you can compare the effects of market volatilities on Darma Henwa and Sumber Global 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 Darma Henwa with a short position of Sumber Global. Check out your portfolio center. Please also check ongoing floating volatility patterns of Darma Henwa and Sumber Global.
Diversification Opportunities for Darma Henwa and Sumber Global
-0.47 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Darma and Sumber is -0.47. Overlapping area represents the amount of risk that can be diversified away by holding Darma Henwa Tbk and Sumber Global Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sumber Global Energy and Darma Henwa 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 Darma Henwa Tbk are associated (or correlated) with Sumber Global. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sumber Global Energy has no effect on the direction of Darma Henwa i.e., Darma Henwa and Sumber Global go up and down completely randomly.
Pair Corralation between Darma Henwa and Sumber Global
Assuming the 90 days trading horizon Darma Henwa Tbk is expected to generate 3.13 times more return on investment than Sumber Global. However, Darma Henwa is 3.13 times more volatile than Sumber Global Energy. It trades about 0.17 of its potential returns per unit of risk. Sumber Global Energy is currently generating about -0.14 per unit of risk. If you would invest 9,300 in Darma Henwa Tbk on August 30, 2024 and sell it today you would earn a total of 2,100 from holding Darma Henwa Tbk or generate 22.58% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Darma Henwa Tbk vs. Sumber Global Energy
Performance |
| Timeline |
| Darma Henwa Tbk |
| Sumber Global Energy |
Darma Henwa and Sumber Global Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Darma Henwa and Sumber Global
The main advantage of trading using opposite Darma Henwa and Sumber Global positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Darma Henwa position performs unexpectedly, Sumber Global 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 Sumber Global will offset losses from the drop in Sumber Global's long position.| Darma Henwa vs. Barito Pacific Tbk | Darma Henwa vs. Charoen Pokphand Indonesia | Darma Henwa vs. Indocement Tunggal Prakarsa |
| Sumber Global vs. Golden Eagle Energy | Sumber Global vs. Baramulti Suksessarana Tbk | Sumber Global vs. TBS Energi Utama | Sumber Global vs. Resource Alam 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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