Correlation Between Hamama and Beeio Honey
Can any of the company-specific risk be diversified away by investing in both Hamama and Beeio Honey 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 Hamama and Beeio Honey into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hamama and Beeio Honey, you can compare the effects of market volatilities on Hamama and Beeio Honey 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 Hamama with a short position of Beeio Honey. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hamama and Beeio Honey.
Diversification Opportunities for Hamama and Beeio Honey
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hamama and Beeio is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Hamama and Beeio Honey in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Beeio Honey and Hamama 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 Hamama are associated (or correlated) with Beeio Honey. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Beeio Honey has no effect on the direction of Hamama i.e., Hamama and Beeio Honey go up and down completely randomly.
Pair Corralation between Hamama and Beeio Honey
Assuming the 90 days trading horizon Hamama is expected to generate 0.26 times more return on investment than Beeio Honey. However, Hamama is 3.83 times less risky than Beeio Honey. It trades about -0.08 of its potential returns per unit of risk. Beeio Honey is currently generating about -0.03 per unit of risk. If you would invest 41,660 in Hamama on September 28, 2024 and sell it today you would lose (3,760) from holding Hamama or give up 9.03% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Hamama vs. Beeio Honey
Performance |
Timeline |
Hamama |
Beeio Honey |
Hamama and Beeio Honey Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hamama and Beeio Honey
The main advantage of trading using opposite Hamama and Beeio Honey positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hamama position performs unexpectedly, Beeio Honey 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 Beeio Honey will offset losses from the drop in Beeio Honey's long position.The idea behind Hamama and Beeio Honey pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Beeio Honey vs. Teuza A Fairchild | Beeio Honey vs. Abra Information Technologies | Beeio Honey vs. Rimon Consulting Management | Beeio Honey vs. Blender Financial Technologies |
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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