Correlation Between FT Cboe and PGIM Large

Can any of the company-specific risk be diversified away by investing in both FT Cboe 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 FT Cboe and PGIM Large into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between FT Cboe Vest and PGIM Large Cap Buffer, you can compare the effects of market volatilities on FT Cboe 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 FT Cboe with a short position of PGIM Large. Check out your portfolio center. Please also check ongoing floating volatility patterns of FT Cboe and PGIM Large.

Diversification Opportunities for FT Cboe and PGIM Large

0.76

Correlation Coefficient

FT Cboe  PGIM Large

Poor diversification

The 3 months correlation between DAUG and PGIM is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding FT Cboe Vest 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 FT Cboe 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 FT Cboe Vest 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 FT Cboe i.e., FT Cboe and PGIM Large go up and down completely randomly.

Pair Corralation between FT Cboe and PGIM Large

Given the investment horizon of 90 days FT Cboe Vest is expected to under-perform the PGIM Large. In addition to that, FT Cboe is 1.15 times more volatile than PGIM Large Cap Buffer. It trades about -0.04 of its total potential returns per unit of risk. PGIM Large Cap Buffer is currently generating about -0.01 per unit of volatility. If you would invest  2,773  in PGIM Large Cap Buffer on December 19, 2024 and sell it today you would lose (8.70) from holding PGIM Large Cap Buffer or give up 0.31% of portfolio value over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	100.0%
Values	Daily Returns

FT Cboe Vest  vs.  PGIM Large Cap Buffer

FT Cboe Vest

Risk-Adjusted Performance

Very Weak

Over the last 90 days FT Cboe Vest has generated negative risk-adjusted returns adding no value to investors with long positions. Despite nearly stable basic indicators, FT Cboe is not utilizing all of its potentials. The latest stock price disturbance, may contribute to mid-run losses for the stockholders.

PGIM Large Cap

Risk-Adjusted Performance

Very Weak

Over the last 90 days PGIM Large Cap Buffer has generated negative risk-adjusted returns adding no value to investors with long positions. Even with relatively invariable basic indicators, PGIM Large is not utilizing all of its potentials. The current stock price agitation, may contribute to short-term losses for the retail investors.

Pair Trading with FT Cboe and PGIM Large

The main advantage of trading using opposite FT Cboe and PGIM Large positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if FT Cboe 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.

The idea behind FT Cboe Vest and PGIM Large Cap Buffer pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.