Correlation Between Public Packages and BP Plastics
Can any of the company-specific risk be diversified away by investing in both Public Packages and BP Plastics 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 Public Packages and BP Plastics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Public Packages Holdings and BP Plastics Holding, you can compare the effects of market volatilities on Public Packages and BP Plastics 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 Public Packages with a short position of BP Plastics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Public Packages and BP Plastics.
Diversification Opportunities for Public Packages and BP Plastics
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Public and 5100 is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding Public Packages Holdings and BP Plastics Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BP Plastics Holding and Public Packages 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 Public Packages Holdings are associated (or correlated) with BP Plastics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BP Plastics Holding has no effect on the direction of Public Packages i.e., Public Packages and BP Plastics go up and down completely randomly.
Pair Corralation between Public Packages and BP Plastics
Assuming the 90 days trading horizon Public Packages Holdings is expected to generate 1.07 times more return on investment than BP Plastics. However, Public Packages is 1.07 times more volatile than BP Plastics Holding. It trades about -0.02 of its potential returns per unit of risk. BP Plastics Holding is currently generating about -0.05 per unit of risk. If you would invest 83.00 in Public Packages Holdings on September 25, 2024 and sell it today you would lose (2.00) from holding Public Packages Holdings or give up 2.41% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 98.41% |
Values | Daily Returns |
Public Packages Holdings vs. BP Plastics Holding
Performance |
Timeline |
Public Packages Holdings |
BP Plastics Holding |
Public Packages and BP Plastics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Public Packages and BP Plastics
The main advantage of trading using opposite Public Packages and BP Plastics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Public Packages position performs unexpectedly, BP Plastics 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 BP Plastics will offset losses from the drop in BP Plastics' long position.Public Packages vs. Malayan Banking Bhd | Public Packages vs. Public Bank Bhd | Public Packages vs. Petronas Chemicals Group | Public Packages vs. Tenaga Nasional Bhd |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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