Correlation Between Alfa Financial and Norwegian Air
Can any of the company-specific risk be diversified away by investing in both Alfa Financial and Norwegian Air 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 Alfa Financial and Norwegian Air into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alfa Financial Software and Norwegian Air Shuttle, you can compare the effects of market volatilities on Alfa Financial and Norwegian Air 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 Alfa Financial with a short position of Norwegian Air. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alfa Financial and Norwegian Air.
Diversification Opportunities for Alfa Financial and Norwegian Air
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Alfa and Norwegian is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Alfa Financial Software and Norwegian Air Shuttle in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Norwegian Air Shuttle and Alfa Financial 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 Alfa Financial Software are associated (or correlated) with Norwegian Air. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Norwegian Air Shuttle has no effect on the direction of Alfa Financial i.e., Alfa Financial and Norwegian Air go up and down completely randomly.
Pair Corralation between Alfa Financial and Norwegian Air
Assuming the 90 days trading horizon Alfa Financial Software is expected to generate 0.65 times more return on investment than Norwegian Air. However, Alfa Financial Software is 1.53 times less risky than Norwegian Air. It trades about 0.05 of its potential returns per unit of risk. Norwegian Air Shuttle is currently generating about 0.02 per unit of risk. If you would invest 20,718 in Alfa Financial Software on September 14, 2024 and sell it today you would earn a total of 1,132 from holding Alfa Financial Software or generate 5.46% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Alfa Financial Software vs. Norwegian Air Shuttle
Performance |
Timeline |
Alfa Financial Software |
Norwegian Air Shuttle |
Alfa Financial and Norwegian Air Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alfa Financial and Norwegian Air
The main advantage of trading using opposite Alfa Financial and Norwegian Air positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alfa Financial position performs unexpectedly, Norwegian Air 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 Norwegian Air will offset losses from the drop in Norwegian Air's long position.Alfa Financial vs. National Beverage Corp | Alfa Financial vs. Tyson Foods Cl | Alfa Financial vs. McEwen Mining | Alfa Financial vs. Anglesey Mining |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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