Correlation Between Linedata Services and Air France
Can any of the company-specific risk be diversified away by investing in both Linedata Services and Air France 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 Linedata Services and Air France into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Linedata Services SA and Air France KLM SA, you can compare the effects of market volatilities on Linedata Services and Air France 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 Linedata Services with a short position of Air France. Check out your portfolio center. Please also check ongoing floating volatility patterns of Linedata Services and Air France.
Diversification Opportunities for Linedata Services and Air France
0.09 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Linedata and Air is 0.09. Overlapping area represents the amount of risk that can be diversified away by holding Linedata Services SA and Air France KLM SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Air France KLM and Linedata Services 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 Linedata Services SA are associated (or correlated) with Air France. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Air France KLM has no effect on the direction of Linedata Services i.e., Linedata Services and Air France go up and down completely randomly.
Pair Corralation between Linedata Services and Air France
Assuming the 90 days trading horizon Linedata Services SA is expected to generate 0.8 times more return on investment than Air France. However, Linedata Services SA is 1.24 times less risky than Air France. It trades about 0.12 of its potential returns per unit of risk. Air France KLM SA is currently generating about 0.02 per unit of risk. If you would invest 8,200 in Linedata Services SA on October 9, 2024 and sell it today you would earn a total of 340.00 from holding Linedata Services SA or generate 4.15% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Linedata Services SA vs. Air France KLM SA
Performance |
| Timeline |
| Linedata Services |
| Air France KLM |
Linedata Services and Air France Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Linedata Services and Air France
The main advantage of trading using opposite Linedata Services and Air France positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Linedata Services position performs unexpectedly, Air France 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 Air France will offset losses from the drop in Air France's long position.| Linedata Services vs. Sword Group SE | Linedata Services vs. Lectra SA | Linedata Services vs. Neurones | Linedata Services vs. Aubay Socit Anonyme |
| Air France vs. Boiron SA | Air France vs. Parx Plastics NV | Air France vs. X Fab Silicon | Air France vs. Affluent Medical SAS |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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