Correlation Between City Retail and Bukit Uluwatu
Can any of the company-specific risk be diversified away by investing in both City Retail and Bukit Uluwatu 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 City Retail and Bukit Uluwatu into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between City Retail Developments and Bukit Uluwatu Villa, you can compare the effects of market volatilities on City Retail and Bukit Uluwatu 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 City Retail with a short position of Bukit Uluwatu. Check out your portfolio center. Please also check ongoing floating volatility patterns of City Retail and Bukit Uluwatu.
Diversification Opportunities for City Retail and Bukit Uluwatu
-0.2 | Correlation Coefficient |
Good diversification
The 3 months correlation between City and Bukit is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding City Retail Developments and Bukit Uluwatu Villa in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bukit Uluwatu Villa and City Retail 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 City Retail Developments are associated (or correlated) with Bukit Uluwatu. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bukit Uluwatu Villa has no effect on the direction of City Retail i.e., City Retail and Bukit Uluwatu go up and down completely randomly.
Pair Corralation between City Retail and Bukit Uluwatu
Assuming the 90 days trading horizon City Retail Developments is expected to under-perform the Bukit Uluwatu. But the stock apears to be less risky and, when comparing its historical volatility, City Retail Developments is 12.85 times less risky than Bukit Uluwatu. The stock trades about -0.11 of its potential returns per unit of risk. The Bukit Uluwatu Villa is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 5,800 in Bukit Uluwatu Villa on December 29, 2024 and sell it today you would earn a total of 1,400 from holding Bukit Uluwatu Villa or generate 24.14% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
City Retail Developments vs. Bukit Uluwatu Villa
Performance |
Timeline |
City Retail Developments |
Bukit Uluwatu Villa |
City Retail and Bukit Uluwatu Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with City Retail and Bukit Uluwatu
The main advantage of trading using opposite City Retail and Bukit Uluwatu positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if City Retail position performs unexpectedly, Bukit Uluwatu 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 Bukit Uluwatu will offset losses from the drop in Bukit Uluwatu's long position.City Retail vs. Metropolitan Land Tbk | City Retail vs. Bekasi Fajar Industrial | City Retail vs. Greenwood Sejahtera Tbk | City Retail vs. Metropolitan Kentjana 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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