Correlation Between NYSE Composite and Customers Bancorp

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

By analyzing existing cross correlation between NYSE Composite and Customers Bancorp, you can compare the effects of market volatilities on NYSE Composite and Customers Bancorp 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 Customers Bancorp. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Customers Bancorp.

Diversification Opportunities for NYSE Composite and Customers Bancorp

-0.2

Correlation Coefficient

NYSE Composite  Customers Bancorp

Good diversification

The 3 months correlation between NYSE and Customers is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Customers Bancorp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Customers Bancorp 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 Customers Bancorp. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Customers Bancorp has no effect on the direction of NYSE Composite i.e., NYSE Composite and Customers Bancorp go up and down completely randomly.

Pair Corralation between NYSE Composite and Customers Bancorp

Assuming the 90 days trading horizon NYSE Composite is expected to under-perform the Customers Bancorp. In addition to that, NYSE Composite is 1.45 times more volatile than Customers Bancorp. It trades about -0.2 of its total potential returns per unit of risk. Customers Bancorp is currently generating about 0.11 per unit of volatility. If you would invest  2,535  in Customers Bancorp on October 11, 2024 and sell it today you would earn a total of  30.00  from holding Customers Bancorp or generate 1.18% return on investment over 90 days.

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

NYSE Composite  vs.  Customers Bancorp

Pair Trading with NYSE Composite and Customers Bancorp

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

The idea behind NYSE Composite and Customers Bancorp 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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.