Correlation Between First Trust and First Trust
Can any of the company-specific risk be diversified away by investing in both First Trust and First Trust 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 First Trust into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust NASDAQ 100 and First Trust California, you can compare the effects of market volatilities on First Trust and First Trust 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 First Trust. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and First Trust.
Diversification Opportunities for First Trust and First Trust
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between First and First is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding First Trust NASDAQ 100 and First Trust California in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on First Trust California 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 NASDAQ 100 are associated (or correlated) with First Trust. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of First Trust California has no effect on the direction of First Trust i.e., First Trust and First Trust go up and down completely randomly.
Pair Corralation between First Trust and First Trust
Given the investment horizon of 90 days First Trust NASDAQ 100 is expected to generate 2.84 times more return on investment than First Trust. However, First Trust is 2.84 times more volatile than First Trust California. It trades about 0.36 of its potential returns per unit of risk. First Trust California is currently generating about 0.2 per unit of risk. If you would invest 9,287 in First Trust NASDAQ 100 on September 1, 2024 and sell it today you would earn a total of 588.00 from holding First Trust NASDAQ 100 or generate 6.33% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
First Trust NASDAQ 100 vs. First Trust California
Performance |
| Timeline |
| First Trust NASDAQ |
| First Trust California |
First Trust and First Trust Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with First Trust and First Trust
The main advantage of trading using opposite First Trust and First Trust positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, First Trust 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 First Trust will offset losses from the drop in First Trust's long position.| First Trust vs. First Trust NASDAQ 100 | First Trust vs. First Trust Multi | First Trust vs. First Trust Large | First Trust vs. First Trust Large |
| First Trust vs. First Trust Municipal | First Trust vs. First Trust Emerging | First Trust vs. First Trust Income | First Trust vs. First Trust Managed |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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