Correlation Between Indointernet Tbk and Dharma Polimetal
Can any of the company-specific risk be diversified away by investing in both Indointernet Tbk and Dharma Polimetal 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 Indointernet Tbk and Dharma Polimetal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Indointernet Tbk PT and Dharma Polimetal Tbk, you can compare the effects of market volatilities on Indointernet Tbk and Dharma Polimetal 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 Indointernet Tbk with a short position of Dharma Polimetal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Indointernet Tbk and Dharma Polimetal.
Diversification Opportunities for Indointernet Tbk and Dharma Polimetal
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Indointernet and Dharma is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Indointernet Tbk PT and Dharma Polimetal Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dharma Polimetal Tbk and Indointernet Tbk 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 Indointernet Tbk PT are associated (or correlated) with Dharma Polimetal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dharma Polimetal Tbk has no effect on the direction of Indointernet Tbk i.e., Indointernet Tbk and Dharma Polimetal go up and down completely randomly.
Pair Corralation between Indointernet Tbk and Dharma Polimetal
Assuming the 90 days trading horizon Indointernet Tbk PT is expected to generate 1.04 times more return on investment than Dharma Polimetal. However, Indointernet Tbk is 1.04 times more volatile than Dharma Polimetal Tbk. It trades about -0.14 of its potential returns per unit of risk. Dharma Polimetal Tbk is currently generating about -0.17 per unit of risk. If you would invest 460,000 in Indointernet Tbk PT on September 18, 2024 and sell it today you would lose (71,000) from holding Indointernet Tbk PT or give up 15.43% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Indointernet Tbk PT vs. Dharma Polimetal Tbk
Performance |
Timeline |
Indointernet Tbk |
Dharma Polimetal Tbk |
Indointernet Tbk and Dharma Polimetal Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Indointernet Tbk and Dharma Polimetal
The main advantage of trading using opposite Indointernet Tbk and Dharma Polimetal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Indointernet Tbk position performs unexpectedly, Dharma Polimetal 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 Dharma Polimetal will offset losses from the drop in Dharma Polimetal's long position.Indointernet Tbk vs. DCI Indonesia Tbk | Indointernet Tbk vs. Digital Mediatama Maxima | Indointernet Tbk vs. Multipolar Technology Tbk | Indointernet Tbk vs. Bank Net Indonesia |
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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 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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