Correlation Between NYSE Composite and Frank Value

Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Frank Value 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 NYSE Composite and Frank Value into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between NYSE Composite and Frank Value Fund, you can compare the effects of market volatilities on NYSE Composite and Frank Value 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 NYSE Composite with a short position of Frank Value. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Frank Value.

Diversification Opportunities for NYSE Composite and Frank Value

0.72

Correlation Coefficient

NYSE Composite  Frank Value

Poor diversification

The 3 months correlation between NYSE and Frank is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Frank Value Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Frank Value Fund and NYSE Composite 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 NYSE Composite are associated (or correlated) with Frank Value. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Frank Value Fund has no effect on the direction of NYSE Composite i.e., NYSE Composite and Frank Value go up and down completely randomly.

Pair Corralation between NYSE Composite and Frank Value

Assuming the 90 days trading horizon NYSE Composite is expected to generate 0.78 times more return on investment than Frank Value. However, NYSE Composite is 1.29 times less risky than Frank Value. It trades about -0.21 of its potential returns per unit of risk. Frank Value Fund is currently generating about -0.39 per unit of risk. If you would invest  1,989,103  in NYSE Composite on October 12, 2024 and sell it today you would lose (65,029) from holding NYSE Composite or give up 3.27% of portfolio value over 90 days.

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

NYSE Composite  vs.  Frank Value Fund

Pair Trading with NYSE Composite and Frank Value

The main advantage of trading using opposite NYSE Composite and Frank Value positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Frank Value 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 Frank Value will offset losses from the drop in Frank Value's long position.

The idea behind NYSE Composite and Frank Value Fund 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.