Correlation Between Akbar Indomakmur and Gema Grahasarana
Can any of the company-specific risk be diversified away by investing in both Akbar Indomakmur and Gema Grahasarana 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 Akbar Indomakmur and Gema Grahasarana into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Akbar Indomakmur Stimec and Gema Grahasarana Tbk, you can compare the effects of market volatilities on Akbar Indomakmur and Gema Grahasarana 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 Akbar Indomakmur with a short position of Gema Grahasarana. Check out your portfolio center. Please also check ongoing floating volatility patterns of Akbar Indomakmur and Gema Grahasarana.
Diversification Opportunities for Akbar Indomakmur and Gema Grahasarana
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Akbar and Gema is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Akbar Indomakmur Stimec and Gema Grahasarana Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gema Grahasarana Tbk and Akbar Indomakmur 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 Akbar Indomakmur Stimec are associated (or correlated) with Gema Grahasarana. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gema Grahasarana Tbk has no effect on the direction of Akbar Indomakmur i.e., Akbar Indomakmur and Gema Grahasarana go up and down completely randomly.
Pair Corralation between Akbar Indomakmur and Gema Grahasarana
Assuming the 90 days trading horizon Akbar Indomakmur Stimec is expected to under-perform the Gema Grahasarana. In addition to that, Akbar Indomakmur is 1.67 times more volatile than Gema Grahasarana Tbk. It trades about -0.03 of its total potential returns per unit of risk. Gema Grahasarana Tbk is currently generating about -0.05 per unit of volatility. If you would invest 25,600 in Gema Grahasarana Tbk on September 13, 2024 and sell it today you would lose (2,400) from holding Gema Grahasarana Tbk or give up 9.37% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 98.41% |
Values | Daily Returns |
Akbar Indomakmur Stimec vs. Gema Grahasarana Tbk
Performance |
Timeline |
Akbar Indomakmur Stimec |
Gema Grahasarana Tbk |
Akbar Indomakmur and Gema Grahasarana Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Akbar Indomakmur and Gema Grahasarana
The main advantage of trading using opposite Akbar Indomakmur and Gema Grahasarana positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Akbar Indomakmur position performs unexpectedly, Gema Grahasarana 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 Gema Grahasarana will offset losses from the drop in Gema Grahasarana's long position.Akbar Indomakmur vs. Bayu Buana Tbk | Akbar Indomakmur vs. Alakasa Industrindo Tbk | Akbar Indomakmur vs. Mahaka Media Tbk | Akbar Indomakmur vs. Arthavest Tbk |
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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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