Correlation Between Alfa Financial and GSTechnologies
Can any of the company-specific risk be diversified away by investing in both Alfa Financial and GSTechnologies 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 GSTechnologies 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 GSTechnologies, you can compare the effects of market volatilities on Alfa Financial and GSTechnologies 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 GSTechnologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alfa Financial and GSTechnologies.
Diversification Opportunities for Alfa Financial and GSTechnologies
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Alfa and GSTechnologies is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding Alfa Financial Software and GSTechnologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GSTechnologies 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 GSTechnologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GSTechnologies has no effect on the direction of Alfa Financial i.e., Alfa Financial and GSTechnologies go up and down completely randomly.
Pair Corralation between Alfa Financial and GSTechnologies
Assuming the 90 days trading horizon Alfa Financial Software is expected to under-perform the GSTechnologies. But the stock apears to be less risky and, when comparing its historical volatility, Alfa Financial Software is 4.72 times less risky than GSTechnologies. The stock trades about -0.04 of its potential returns per unit of risk. The GSTechnologies is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 73.00 in GSTechnologies on October 24, 2024 and sell it today you would earn a total of 125.00 from holding GSTechnologies or generate 171.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Alfa Financial Software vs. GSTechnologies
Performance |
Timeline |
Alfa Financial Software |
GSTechnologies |
Alfa Financial and GSTechnologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alfa Financial and GSTechnologies
The main advantage of trading using opposite Alfa Financial and GSTechnologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alfa Financial position performs unexpectedly, GSTechnologies 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 GSTechnologies will offset losses from the drop in GSTechnologies' long position.Alfa Financial vs. Home Depot | Alfa Financial vs. Weiss Korea Opportunity | Alfa Financial vs. River and Mercantile | Alfa Financial vs. Chrysalis Investments |
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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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.
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