Correlation Between Pelita Samudera and Paramita Bangun
Can any of the company-specific risk be diversified away by investing in both Pelita Samudera and Paramita Bangun 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 Pelita Samudera and Paramita Bangun into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pelita Samudera Shipping and Paramita Bangun Sarana, you can compare the effects of market volatilities on Pelita Samudera and Paramita Bangun 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 Pelita Samudera with a short position of Paramita Bangun. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pelita Samudera and Paramita Bangun.
Diversification Opportunities for Pelita Samudera and Paramita Bangun
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Pelita and Paramita is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Pelita Samudera Shipping and Paramita Bangun Sarana in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Paramita Bangun Sarana and Pelita Samudera 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 Pelita Samudera Shipping are associated (or correlated) with Paramita Bangun. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Paramita Bangun Sarana has no effect on the direction of Pelita Samudera i.e., Pelita Samudera and Paramita Bangun go up and down completely randomly.
Pair Corralation between Pelita Samudera and Paramita Bangun
Assuming the 90 days trading horizon Pelita Samudera is expected to generate 13.76 times less return on investment than Paramita Bangun. But when comparing it to its historical volatility, Pelita Samudera Shipping is 1.09 times less risky than Paramita Bangun. It trades about 0.01 of its potential returns per unit of risk. Paramita Bangun Sarana is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 26,678 in Paramita Bangun Sarana on September 2, 2024 and sell it today you would earn a total of 7,122 from holding Paramita Bangun Sarana or generate 26.7% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Pelita Samudera Shipping vs. Paramita Bangun Sarana
Performance |
Timeline |
Pelita Samudera Shipping |
Paramita Bangun Sarana |
Pelita Samudera and Paramita Bangun Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pelita Samudera and Paramita Bangun
The main advantage of trading using opposite Pelita Samudera and Paramita Bangun positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pelita Samudera position performs unexpectedly, Paramita Bangun 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 Paramita Bangun will offset losses from the drop in Paramita Bangun's long position.Pelita Samudera vs. Matahari Department Store | Pelita Samudera vs. Multi Medika Internasional | Pelita Samudera vs. Visi Media Asia | Pelita Samudera vs. Bayan Resources 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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