Correlation Between First Trust and Axonic Strategic
Can any of the company-specific risk be diversified away by investing in both First Trust and Axonic Strategic 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 Axonic Strategic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust Exchange Traded and Axonic Strategic Income, you can compare the effects of market volatilities on First Trust and Axonic Strategic 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 Axonic Strategic. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and Axonic Strategic.
Diversification Opportunities for First Trust and Axonic Strategic
0.86 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between First and Axonic is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding First Trust Exchange Traded and Axonic Strategic Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Axonic Strategic Income 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 Exchange Traded are associated (or correlated) with Axonic Strategic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Axonic Strategic Income has no effect on the direction of First Trust i.e., First Trust and Axonic Strategic go up and down completely randomly.
Pair Corralation between First Trust and Axonic Strategic
Given the investment horizon of 90 days First Trust Exchange Traded is expected to generate 1.91 times more return on investment than Axonic Strategic. However, First Trust is 1.91 times more volatile than Axonic Strategic Income. It trades about 0.15 of its potential returns per unit of risk. Axonic Strategic Income is currently generating about 0.17 per unit of risk. If you would invest 1,999 in First Trust Exchange Traded on April 25, 2025 and sell it today you would earn a total of 58.00 from holding First Trust Exchange Traded or generate 2.9% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
First Trust Exchange Traded vs. Axonic Strategic Income
Performance |
Timeline |
First Trust Exchange |
Axonic Strategic Income |
First Trust and Axonic Strategic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Trust and Axonic Strategic
The main advantage of trading using opposite First Trust and Axonic Strategic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, Axonic Strategic 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 Axonic Strategic will offset losses from the drop in Axonic Strategic's long position.First Trust vs. Columbia Diversified Fixed | First Trust vs. MFS Active Core | First Trust vs. Doubleline Etf Trust | First Trust vs. Virtus Newfleet ABSMBS |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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