Correlation Between Ringkjoebing Landbobank and DFDS AS
Can any of the company-specific risk be diversified away by investing in both Ringkjoebing Landbobank and DFDS AS 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 Ringkjoebing Landbobank and DFDS AS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ringkjoebing Landbobank AS and DFDS AS, you can compare the effects of market volatilities on Ringkjoebing Landbobank and DFDS AS 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 Ringkjoebing Landbobank with a short position of DFDS AS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ringkjoebing Landbobank and DFDS AS.
Diversification Opportunities for Ringkjoebing Landbobank and DFDS AS
-0.87 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Ringkjoebing and DFDS is -0.87. Overlapping area represents the amount of risk that can be diversified away by holding Ringkjoebing Landbobank AS and DFDS AS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DFDS AS and Ringkjoebing Landbobank 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 Ringkjoebing Landbobank AS are associated (or correlated) with DFDS AS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DFDS AS has no effect on the direction of Ringkjoebing Landbobank i.e., Ringkjoebing Landbobank and DFDS AS go up and down completely randomly.
Pair Corralation between Ringkjoebing Landbobank and DFDS AS
Assuming the 90 days trading horizon Ringkjoebing Landbobank AS is expected to generate 0.76 times more return on investment than DFDS AS. However, Ringkjoebing Landbobank AS is 1.31 times less risky than DFDS AS. It trades about 0.07 of its potential returns per unit of risk. DFDS AS is currently generating about -0.09 per unit of risk. If you would invest 93,842 in Ringkjoebing Landbobank AS on September 3, 2024 and sell it today you would earn a total of 21,158 from holding Ringkjoebing Landbobank AS or generate 22.55% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ringkjoebing Landbobank AS vs. DFDS AS
Performance |
| Timeline |
| Ringkjoebing Landbobank |
| DFDS AS |
Ringkjoebing Landbobank and DFDS AS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ringkjoebing Landbobank and DFDS AS
The main advantage of trading using opposite Ringkjoebing Landbobank and DFDS AS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ringkjoebing Landbobank position performs unexpectedly, DFDS AS 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 DFDS AS will offset losses from the drop in DFDS AS's long position.| Ringkjoebing Landbobank vs. Sydbank AS | Ringkjoebing Landbobank vs. Jyske Bank AS | Ringkjoebing Landbobank vs. Royal Unibrew AS | Ringkjoebing Landbobank vs. Spar Nord Bank |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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