Correlation Between Bumi Resources and PT Wahana
Can any of the company-specific risk be diversified away by investing in both Bumi Resources and PT Wahana 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 Bumi Resources and PT Wahana into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bumi Resources Minerals and PT Wahana Interfood, you can compare the effects of market volatilities on Bumi Resources and PT Wahana 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 Bumi Resources with a short position of PT Wahana. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bumi Resources and PT Wahana.
Diversification Opportunities for Bumi Resources and PT Wahana
0.21 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Bumi and COCO is 0.21. Overlapping area represents the amount of risk that can be diversified away by holding Bumi Resources Minerals and PT Wahana Interfood in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PT Wahana Interfood and Bumi Resources 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 Bumi Resources Minerals are associated (or correlated) with PT Wahana. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PT Wahana Interfood has no effect on the direction of Bumi Resources i.e., Bumi Resources and PT Wahana go up and down completely randomly.
Pair Corralation between Bumi Resources and PT Wahana
Assuming the 90 days trading horizon Bumi Resources Minerals is expected to under-perform the PT Wahana. But the stock apears to be less risky and, when comparing its historical volatility, Bumi Resources Minerals is 1.22 times less risky than PT Wahana. The stock trades about -0.02 of its potential returns per unit of risk. The PT Wahana Interfood is currently generating about -0.01 of returns per unit of risk over similar time horizon. If you would invest 8,600 in PT Wahana Interfood on December 1, 2024 and sell it today you would lose (1,000.00) from holding PT Wahana Interfood or give up 11.63% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bumi Resources Minerals vs. PT Wahana Interfood
Performance |
Timeline |
Bumi Resources Minerals |
PT Wahana Interfood |
Bumi Resources and PT Wahana Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bumi Resources and PT Wahana
The main advantage of trading using opposite Bumi Resources and PT Wahana positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bumi Resources position performs unexpectedly, PT Wahana 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 PT Wahana will offset losses from the drop in PT Wahana's long position.Bumi Resources vs. Energi Mega Persada | Bumi Resources vs. Harum Energy Tbk | Bumi Resources vs. Delta Dunia Makmur | Bumi Resources vs. Benakat Petroleum Energy |
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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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