Correlation Between Jeudan and Fast Ejendom
Can any of the company-specific risk be diversified away by investing in both Jeudan and Fast Ejendom 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 Jeudan and Fast Ejendom into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Jeudan and Fast Ejendom, you can compare the effects of market volatilities on Jeudan and Fast Ejendom 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 Jeudan with a short position of Fast Ejendom. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jeudan and Fast Ejendom.
Diversification Opportunities for Jeudan and Fast Ejendom
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Jeudan and Fast is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding Jeudan and Fast Ejendom in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fast Ejendom and Jeudan 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 Jeudan are associated (or correlated) with Fast Ejendom. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fast Ejendom has no effect on the direction of Jeudan i.e., Jeudan and Fast Ejendom go up and down completely randomly.
Pair Corralation between Jeudan and Fast Ejendom
Assuming the 90 days trading horizon Jeudan is expected to under-perform the Fast Ejendom. In addition to that, Jeudan is 1.24 times more volatile than Fast Ejendom. It trades about -0.46 of its total potential returns per unit of risk. Fast Ejendom is currently generating about -0.11 per unit of volatility. If you would invest 12,000 in Fast Ejendom on August 28, 2024 and sell it today you would lose (300.00) from holding Fast Ejendom or give up 2.5% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 95.45% |
| Values | Daily Returns |
Jeudan vs. Fast Ejendom
Performance |
| Timeline |
| Jeudan |
| Fast Ejendom |
Jeudan and Fast Ejendom Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Jeudan and Fast Ejendom
The main advantage of trading using opposite Jeudan and Fast Ejendom positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jeudan position performs unexpectedly, Fast Ejendom 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 Fast Ejendom will offset losses from the drop in Fast Ejendom's long position.The idea behind Jeudan and Fast Ejendom 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.| Fast Ejendom vs. Jeudan | Fast Ejendom vs. Copenhagen Capital AS | Fast Ejendom vs. Cemat AS | Fast Ejendom vs. Movinn AS |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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