Correlation Between Air France-KLM and Norse Atlantic
Can any of the company-specific risk be diversified away by investing in both Air France-KLM and Norse Atlantic 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 Air France-KLM and Norse Atlantic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Air France KLM SA and Norse Atlantic ASA, you can compare the effects of market volatilities on Air France-KLM and Norse Atlantic 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 Air France-KLM with a short position of Norse Atlantic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Air France-KLM and Norse Atlantic.
Diversification Opportunities for Air France-KLM and Norse Atlantic
-0.71 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Air and Norse is -0.71. Overlapping area represents the amount of risk that can be diversified away by holding Air France KLM SA and Norse Atlantic ASA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Norse Atlantic ASA and Air France-KLM 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 Air France KLM SA are associated (or correlated) with Norse Atlantic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Norse Atlantic ASA has no effect on the direction of Air France-KLM i.e., Air France-KLM and Norse Atlantic go up and down completely randomly.
Pair Corralation between Air France-KLM and Norse Atlantic
Assuming the 90 days horizon Air France KLM SA is expected to generate 0.39 times more return on investment than Norse Atlantic. However, Air France KLM SA is 2.58 times less risky than Norse Atlantic. It trades about -0.06 of its potential returns per unit of risk. Norse Atlantic ASA is currently generating about -0.05 per unit of risk. If you would invest 1,270 in Air France KLM SA on August 24, 2024 and sell it today you would lose (473.00) from holding Air France KLM SA or give up 37.24% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 98.39% |
| Values | Daily Returns |
Air France KLM SA vs. Norse Atlantic ASA
Performance |
| Timeline |
| Air France KLM |
| Norse Atlantic ASA |
Air France-KLM and Norse Atlantic Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Air France-KLM and Norse Atlantic
The main advantage of trading using opposite Air France-KLM and Norse Atlantic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Air France-KLM position performs unexpectedly, Norse Atlantic 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 Norse Atlantic will offset losses from the drop in Norse Atlantic's long position.| Air France-KLM vs. Cebu Air | Air France-KLM vs. easyJet plc | Air France-KLM vs. Norse Atlantic ASA | Air France-KLM vs. Air China Limited |
| Norse Atlantic vs. Finnair Oyj | Norse Atlantic vs. easyJet plc | Norse Atlantic vs. Air New Zealand | Norse Atlantic vs. Air China Limited |
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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