Correlation Between First Trust and PGIM Large
Can any of the company-specific risk be diversified away by investing in both First Trust and PGIM Large 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 PGIM Large into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Trust Cboe and PGIM Large Cap Buffer, you can compare the effects of market volatilities on First Trust and PGIM Large 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 PGIM Large. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Trust and PGIM Large.
Diversification Opportunities for First Trust and PGIM Large
1.0 | Correlation Coefficient |
No risk reduction
The 3 months correlation between First and PGIM is 1.0. Overlapping area represents the amount of risk that can be diversified away by holding First Trust Cboe and PGIM Large Cap Buffer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PGIM Large Cap 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 Cboe are associated (or correlated) with PGIM Large. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PGIM Large Cap has no effect on the direction of First Trust i.e., First Trust and PGIM Large go up and down completely randomly.
Pair Corralation between First Trust and PGIM Large
Given the investment horizon of 90 days First Trust is expected to generate 1.16 times less return on investment than PGIM Large. In addition to that, First Trust is 1.11 times more volatile than PGIM Large Cap Buffer. It trades about 0.14 of its total potential returns per unit of risk. PGIM Large Cap Buffer is currently generating about 0.19 per unit of volatility. If you would invest 2,497 in PGIM Large Cap Buffer on August 30, 2024 and sell it today you would earn a total of 294.00 from holding PGIM Large Cap Buffer or generate 11.77% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 37.31% |
| Values | Daily Returns |
First Trust Cboe vs. PGIM Large Cap Buffer
Performance |
| Timeline |
| First Trust Cboe |
| PGIM Large Cap |
First Trust and PGIM Large Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with First Trust and PGIM Large
The main advantage of trading using opposite First Trust and PGIM Large positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Trust position performs unexpectedly, PGIM Large 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 PGIM Large will offset losses from the drop in PGIM Large's long position.| First Trust vs. FT Cboe Vest | First Trust vs. First Trust Exchange Traded | First Trust vs. FT Cboe Vest | First Trust vs. FT Cboe Vest |
| PGIM Large vs. FT Vest Equity | PGIM Large vs. Northern Lights | PGIM Large vs. Dimensional International High | PGIM Large vs. First Trust Exchange Traded |
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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