Correlation Between First Trust and Listed Funds
Can any of the company-specific risk be diversified away by investing in both First Trust and Listed Funds 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 Listed Funds into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust Energy and Listed Funds Trust, you can compare the effects of market volatilities on First Trust and Listed Funds 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 Listed Funds. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and Listed Funds.
Diversification Opportunities for First Trust and Listed Funds
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between First and Listed is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding First Trust Energy and Listed Funds Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Listed Funds Trust 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 Energy are associated (or correlated) with Listed Funds. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Listed Funds Trust has no effect on the direction of First Trust i.e., First Trust and Listed Funds go up and down completely randomly.
Pair Corralation between First Trust and Listed Funds
Considering the 90-day investment horizon First Trust Energy is expected to under-perform the Listed Funds. In addition to that, First Trust is 1.23 times more volatile than Listed Funds Trust. It trades about -0.01 of its total potential returns per unit of risk. Listed Funds Trust is currently generating about 0.12 per unit of volatility. If you would invest 2,808 in Listed Funds Trust on September 1, 2024 and sell it today you would earn a total of 479.00 from holding Listed Funds Trust or generate 17.06% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
First Trust Energy vs. Listed Funds Trust
Performance |
| Timeline |
| First Trust Energy |
| Listed Funds Trust |
First Trust and Listed Funds Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with First Trust and Listed Funds
The main advantage of trading using opposite First Trust and Listed Funds positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, Listed Funds 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 Listed Funds will offset losses from the drop in Listed Funds' long position.| First Trust vs. First Trust Materials | First Trust vs. First Trust IndustrialsProducer | First Trust vs. First Trust Financials | First Trust vs. First Trust Consumer |
| Listed Funds vs. Horizon Kinetics Inflation | Listed Funds vs. PrairieSky Royalty | Listed Funds vs. Listed Funds Trust | Listed Funds vs. Enerflex |
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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