Correlation Between Textron and Alfa SAB
Can any of the company-specific risk be diversified away by investing in both Textron and Alfa SAB 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 Textron and Alfa SAB into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Textron and Alfa SAB de, you can compare the effects of market volatilities on Textron and Alfa SAB 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 Textron with a short position of Alfa SAB. Check out your portfolio center. Please also check ongoing floating volatility patterns of Textron and Alfa SAB.
Diversification Opportunities for Textron and Alfa SAB
Average diversification
The 3 months correlation between Textron and Alfa is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding Textron and Alfa SAB de in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Alfa SAB de and Textron 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 Textron are associated (or correlated) with Alfa SAB. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Alfa SAB de has no effect on the direction of Textron i.e., Textron and Alfa SAB go up and down completely randomly.
Pair Corralation between Textron and Alfa SAB
Assuming the 90 days trading horizon Textron is expected to generate 54.83 times less return on investment than Alfa SAB. But when comparing it to its historical volatility, Textron is 395.37 times less risky than Alfa SAB. It trades about 0.22 of its potential returns per unit of risk. Alfa SAB de is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 1,505 in Alfa SAB de on September 24, 2024 and sell it today you would earn a total of 14.00 from holding Alfa SAB de or generate 0.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 95.24% |
Values | Daily Returns |
Textron vs. Alfa SAB de
Performance |
Timeline |
Textron |
Alfa SAB de |
Textron and Alfa SAB Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Textron and Alfa SAB
The main advantage of trading using opposite Textron and Alfa SAB positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Textron position performs unexpectedly, Alfa SAB 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 Alfa SAB will offset losses from the drop in Alfa SAB's long position.The idea behind Textron and Alfa SAB de pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Alfa SAB vs. Grupo Mxico SAB | Alfa SAB vs. Fomento Econmico Mexicano | Alfa SAB vs. CEMEX SAB de | Alfa SAB vs. Gruma SAB de |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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