Correlation Between Alam Sutera and Sentul City
Can any of the company-specific risk be diversified away by investing in both Alam Sutera and Sentul City 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 Alam Sutera and Sentul City into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alam Sutera Realty and Sentul City Tbk, you can compare the effects of market volatilities on Alam Sutera and Sentul City 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 Alam Sutera with a short position of Sentul City. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alam Sutera and Sentul City.
Diversification Opportunities for Alam Sutera and Sentul City
-0.53 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Alam and Sentul is -0.53. Overlapping area represents the amount of risk that can be diversified away by holding Alam Sutera Realty and Sentul City Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sentul City Tbk and Alam Sutera 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 Alam Sutera Realty are associated (or correlated) with Sentul City. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sentul City Tbk has no effect on the direction of Alam Sutera i.e., Alam Sutera and Sentul City go up and down completely randomly.
Pair Corralation between Alam Sutera and Sentul City
Assuming the 90 days trading horizon Alam Sutera Realty is expected to under-perform the Sentul City. But the stock apears to be less risky and, when comparing its historical volatility, Alam Sutera Realty is 1.97 times less risky than Sentul City. The stock trades about -0.11 of its potential returns per unit of risk. The Sentul City Tbk is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 7,100 in Sentul City Tbk on December 30, 2024 and sell it today you would earn a total of 100.00 from holding Sentul City Tbk or generate 1.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Alam Sutera Realty vs. Sentul City Tbk
Performance |
Timeline |
Alam Sutera Realty |
Sentul City Tbk |
Alam Sutera and Sentul City Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alam Sutera and Sentul City
The main advantage of trading using opposite Alam Sutera and Sentul City positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alam Sutera position performs unexpectedly, Sentul City 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 Sentul City will offset losses from the drop in Sentul City's long position.Alam Sutera vs. Bumi Serpong Damai | Alam Sutera vs. Summarecon Agung Tbk | Alam Sutera vs. Lippo Karawaci Tbk | Alam Sutera vs. Ciputra Development Tbk |
Sentul City vs. Alam Sutera Realty | Sentul City vs. Kawasan Industri Jababeka | Sentul City vs. Lippo Karawaci Tbk | Sentul City vs. Ciputra Development Tbk |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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