Correlation Between Alam Sutera and City Retail
Can any of the company-specific risk be diversified away by investing in both Alam Sutera and City Retail 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 City Retail 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 City Retail Developments, you can compare the effects of market volatilities on Alam Sutera and City Retail 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 City Retail. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alam Sutera and City Retail.
Diversification Opportunities for Alam Sutera and City Retail
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Alam and City is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Alam Sutera Realty and City Retail Developments in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on City Retail Developments 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 City Retail. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of City Retail Developments has no effect on the direction of Alam Sutera i.e., Alam Sutera and City Retail go up and down completely randomly.
Pair Corralation between Alam Sutera and City Retail
Assuming the 90 days trading horizon Alam Sutera Realty is expected to under-perform the City Retail. In addition to that, Alam Sutera is 4.51 times more volatile than City Retail Developments. It trades about -0.2 of its total potential returns per unit of risk. City Retail Developments is currently generating about -0.14 per unit of volatility. If you would invest 14,000 in City Retail Developments on September 16, 2024 and sell it today you would lose (1,000.00) from holding City Retail Developments or give up 7.14% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Alam Sutera Realty vs. City Retail Developments
Performance |
Timeline |
Alam Sutera Realty |
City Retail Developments |
Alam Sutera and City Retail Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alam Sutera and City Retail
The main advantage of trading using opposite Alam Sutera and City Retail positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alam Sutera position performs unexpectedly, City Retail 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 City Retail will offset losses from the drop in City Retail'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 |
City Retail vs. Ciputra Development Tbk | City Retail vs. Bumi Serpong Damai | City Retail vs. Alam Sutera Realty | City Retail vs. Lippo Karawaci 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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