Correlation Between BP Plastics and ECM Libra
Can any of the company-specific risk be diversified away by investing in both BP Plastics and ECM Libra 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 BP Plastics and ECM Libra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BP Plastics Holding and ECM Libra Financial, you can compare the effects of market volatilities on BP Plastics and ECM Libra 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 BP Plastics with a short position of ECM Libra. Check out your portfolio center. Please also check ongoing floating volatility patterns of BP Plastics and ECM Libra.
Diversification Opportunities for BP Plastics and ECM Libra
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between 5100 and ECM is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding BP Plastics Holding and ECM Libra Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ECM Libra Financial and BP Plastics 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 BP Plastics Holding are associated (or correlated) with ECM Libra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ECM Libra Financial has no effect on the direction of BP Plastics i.e., BP Plastics and ECM Libra go up and down completely randomly.
Pair Corralation between BP Plastics and ECM Libra
Assuming the 90 days trading horizon BP Plastics is expected to generate 16.19 times less return on investment than ECM Libra. But when comparing it to its historical volatility, BP Plastics Holding is 1.85 times less risky than ECM Libra. It trades about 0.01 of its potential returns per unit of risk. ECM Libra Financial is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 17.00 in ECM Libra Financial on October 25, 2024 and sell it today you would earn a total of 1.00 from holding ECM Libra Financial or generate 5.88% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
BP Plastics Holding vs. ECM Libra Financial
Performance |
Timeline |
BP Plastics Holding |
ECM Libra Financial |
BP Plastics and ECM Libra Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BP Plastics and ECM Libra
The main advantage of trading using opposite BP Plastics and ECM Libra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BP Plastics position performs unexpectedly, ECM Libra 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 ECM Libra will offset losses from the drop in ECM Libra's long position.BP Plastics vs. Petronas Chemicals Group | BP Plastics vs. Binasat Communications Bhd | BP Plastics vs. ECM Libra Financial | BP Plastics vs. Dataprep Holdings Bhd |
ECM Libra vs. CSC Steel Holdings | ECM Libra vs. SSF Home Group | ECM Libra vs. CPE Technology Berhad | ECM Libra vs. YTL Hospitality REIT |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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