Correlation Between FT AlphaDEX and Evolve Cyber
Can any of the company-specific risk be diversified away by investing in both FT AlphaDEX and Evolve Cyber 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 FT AlphaDEX and Evolve Cyber into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between FT AlphaDEX Industrials and Evolve Cyber Security, you can compare the effects of market volatilities on FT AlphaDEX and Evolve Cyber 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 FT AlphaDEX with a short position of Evolve Cyber. Check out your portfolio center. Please also check ongoing floating volatility patterns of FT AlphaDEX and Evolve Cyber.
Diversification Opportunities for FT AlphaDEX and Evolve Cyber
0.91 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between FHG and Evolve is 0.91. Overlapping area represents the amount of risk that can be diversified away by holding FT AlphaDEX Industrials and Evolve Cyber Security in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Evolve Cyber Security and FT AlphaDEX 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 FT AlphaDEX Industrials are associated (or correlated) with Evolve Cyber. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Evolve Cyber Security has no effect on the direction of FT AlphaDEX i.e., FT AlphaDEX and Evolve Cyber go up and down completely randomly.
Pair Corralation between FT AlphaDEX and Evolve Cyber
Assuming the 90 days trading horizon FT AlphaDEX Industrials is expected to generate 0.61 times more return on investment than Evolve Cyber. However, FT AlphaDEX Industrials is 1.64 times less risky than Evolve Cyber. It trades about 0.03 of its potential returns per unit of risk. Evolve Cyber Security is currently generating about -0.05 per unit of risk. If you would invest 5,935 in FT AlphaDEX Industrials on September 15, 2024 and sell it today you would earn a total of 31.00 from holding FT AlphaDEX Industrials or generate 0.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
FT AlphaDEX Industrials vs. Evolve Cyber Security
Performance |
Timeline |
FT AlphaDEX Industrials |
Evolve Cyber Security |
FT AlphaDEX and Evolve Cyber Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with FT AlphaDEX and Evolve Cyber
The main advantage of trading using opposite FT AlphaDEX and Evolve Cyber positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FT AlphaDEX position performs unexpectedly, Evolve Cyber 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 Evolve Cyber will offset losses from the drop in Evolve Cyber's long position.FT AlphaDEX vs. First Trust AlphaDEX | FT AlphaDEX vs. BMO SPTSX Equal | FT AlphaDEX vs. First Trust Senior |
Evolve Cyber vs. First Trust AlphaDEX | Evolve Cyber vs. FT AlphaDEX Industrials | Evolve Cyber vs. BMO SPTSX Equal | Evolve Cyber vs. First Trust Senior |
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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