Correlation Between Bong AB and Bjorn Borg
Can any of the company-specific risk be diversified away by investing in both Bong AB and Bjorn Borg 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 Bong AB and Bjorn Borg into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bong AB and Bjorn Borg AB, you can compare the effects of market volatilities on Bong AB and Bjorn Borg 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 Bong AB with a short position of Bjorn Borg. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bong AB and Bjorn Borg.
Diversification Opportunities for Bong AB and Bjorn Borg
0.25 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Bong and Bjorn is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding Bong AB and Bjorn Borg AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bjorn Borg AB and Bong AB 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 Bong AB are associated (or correlated) with Bjorn Borg. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bjorn Borg AB has no effect on the direction of Bong AB i.e., Bong AB and Bjorn Borg go up and down completely randomly.
Pair Corralation between Bong AB and Bjorn Borg
Assuming the 90 days trading horizon Bong AB is expected to generate 1.19 times more return on investment than Bjorn Borg. However, Bong AB is 1.19 times more volatile than Bjorn Borg AB. It trades about -0.11 of its potential returns per unit of risk. Bjorn Borg AB is currently generating about -0.25 per unit of risk. If you would invest 86.00 in Bong AB on September 1, 2024 and sell it today you would lose (6.00) from holding Bong AB or give up 6.98% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Bong AB vs. Bjorn Borg AB
Performance |
| Timeline |
| Bong AB |
| Bjorn Borg AB |
Bong AB and Bjorn Borg Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bong AB and Bjorn Borg
The main advantage of trading using opposite Bong AB and Bjorn Borg positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bong AB position performs unexpectedly, Bjorn Borg 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 Bjorn Borg will offset losses from the drop in Bjorn Borg's long position.The idea behind Bong AB and Bjorn Borg AB 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.| Bjorn Borg vs. NetJobs Group AB | Bjorn Borg vs. Mantex AB | Bjorn Borg vs. Doxa AB | Bjorn Borg vs. Clean Motion AB |
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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