Correlation Between Air Lease and Willis Towers
Can any of the company-specific risk be diversified away by investing in both Air Lease and Willis Towers 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 Lease and Willis Towers into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Air Lease and Willis Towers Watson, you can compare the effects of market volatilities on Air Lease and Willis Towers 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 Lease with a short position of Willis Towers. Check out your portfolio center. Please also check ongoing floating volatility patterns of Air Lease and Willis Towers.
Diversification Opportunities for Air Lease and Willis Towers
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Air and Willis is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding Air Lease and Willis Towers Watson in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Willis Towers Watson and Air Lease 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 Lease are associated (or correlated) with Willis Towers. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Willis Towers Watson has no effect on the direction of Air Lease i.e., Air Lease and Willis Towers go up and down completely randomly.
Pair Corralation between Air Lease and Willis Towers
Assuming the 90 days trading horizon Air Lease is expected to generate 1.0 times less return on investment than Willis Towers. In addition to that, Air Lease is 1.28 times more volatile than Willis Towers Watson. It trades about 0.17 of its total potential returns per unit of risk. Willis Towers Watson is currently generating about 0.22 per unit of volatility. If you would invest 26,800 in Willis Towers Watson on September 27, 2024 and sell it today you would earn a total of 3,600 from holding Willis Towers Watson or generate 13.43% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Air Lease vs. Willis Towers Watson
Performance |
Timeline |
Air Lease |
Willis Towers Watson |
Air Lease and Willis Towers Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Air Lease and Willis Towers
The main advantage of trading using opposite Air Lease and Willis Towers positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Air Lease position performs unexpectedly, Willis Towers 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 Willis Towers will offset losses from the drop in Willis Towers' long position.Air Lease vs. COMMERCIAL VEHICLE | Air Lease vs. CARSALESCOM | Air Lease vs. Corporate Office Properties | Air Lease vs. COFCO Joycome Foods |
Willis Towers vs. Safety Insurance Group | Willis Towers vs. UNIQA INSURANCE GR | Willis Towers vs. Insurance Australia Group | Willis Towers vs. KINGBOARD CHEMICAL |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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