Correlation Between Kawasan Industri and Bumi Serpong
Can any of the company-specific risk be diversified away by investing in both Kawasan Industri and Bumi Serpong 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 Kawasan Industri and Bumi Serpong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kawasan Industri Jababeka and Bumi Serpong Damai, you can compare the effects of market volatilities on Kawasan Industri and Bumi Serpong 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 Kawasan Industri with a short position of Bumi Serpong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kawasan Industri and Bumi Serpong.
Diversification Opportunities for Kawasan Industri and Bumi Serpong
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Kawasan and Bumi is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Kawasan Industri Jababeka and Bumi Serpong Damai in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bumi Serpong Damai and Kawasan Industri 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 Kawasan Industri Jababeka are associated (or correlated) with Bumi Serpong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bumi Serpong Damai has no effect on the direction of Kawasan Industri i.e., Kawasan Industri and Bumi Serpong go up and down completely randomly.
Pair Corralation between Kawasan Industri and Bumi Serpong
Assuming the 90 days trading horizon Kawasan Industri Jababeka is expected to generate 0.73 times more return on investment than Bumi Serpong. However, Kawasan Industri Jababeka is 1.37 times less risky than Bumi Serpong. It trades about -0.05 of its potential returns per unit of risk. Bumi Serpong Damai is currently generating about -0.15 per unit of risk. If you would invest 18,600 in Kawasan Industri Jababeka on December 30, 2024 and sell it today you would lose (700.00) from holding Kawasan Industri Jababeka or give up 3.76% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Kawasan Industri Jababeka vs. Bumi Serpong Damai
Performance |
Timeline |
Kawasan Industri Jababeka |
Bumi Serpong Damai |
Kawasan Industri and Bumi Serpong Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kawasan Industri and Bumi Serpong
The main advantage of trading using opposite Kawasan Industri and Bumi Serpong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kawasan Industri position performs unexpectedly, Bumi Serpong 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 Bumi Serpong will offset losses from the drop in Bumi Serpong's long position.Kawasan Industri vs. Bakrieland Development Tbk | Kawasan Industri vs. Ciputra Development Tbk | Kawasan Industri vs. Sentul City Tbk | Kawasan Industri vs. Solusi Bangun 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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