Correlation Between First Trust and Invesco New
Can any of the company-specific risk be diversified away by investing in both First Trust and Invesco New 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 First Trust and Invesco New into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust California and Invesco New York, you can compare the effects of market volatilities on First Trust and Invesco New 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 First Trust with a short position of Invesco New. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and Invesco New.
Diversification Opportunities for First Trust and Invesco New
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between First and Invesco is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding First Trust California and Invesco New York in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Invesco New York and First Trust 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 First Trust California are associated (or correlated) with Invesco New. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Invesco New York has no effect on the direction of First Trust i.e., First Trust and Invesco New go up and down completely randomly.
Pair Corralation between First Trust and Invesco New
Given the investment horizon of 90 days First Trust California is expected to generate 0.87 times more return on investment than Invesco New. However, First Trust California is 1.15 times less risky than Invesco New. It trades about 0.01 of its potential returns per unit of risk. Invesco New York is currently generating about -0.05 per unit of risk. If you would invest 4,989 in First Trust California on September 15, 2024 and sell it today you would earn a total of 5.00 from holding First Trust California or generate 0.1% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 98.46% |
Values | Daily Returns |
First Trust California vs. Invesco New York
Performance |
Timeline |
First Trust California |
Invesco New York |
First Trust and Invesco New Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Trust and Invesco New
The main advantage of trading using opposite First Trust and Invesco New positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, Invesco New 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 Invesco New will offset losses from the drop in Invesco New's long position.First Trust vs. First Trust Municipal | First Trust vs. First Trust Emerging | First Trust vs. First Trust Income | First Trust vs. First Trust Managed |
Invesco New vs. iShares California Muni | Invesco New vs. iShares Intermediate GovernmentCredit | Invesco New vs. iShares Agency Bond | Invesco New vs. iShares Short Term National |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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