Correlation Between NYSE Composite and Crm Long/short

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

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

Diversification Opportunities for NYSE Composite and Crm Long/short

0.88

Correlation Coefficient

NYSE Composite  Crm Long/short

Very poor diversification

The 3 months correlation between NYSE and Crm is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Crm Longshort Opport in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Crm Longshort Opport 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 Crm Long/short. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Crm Longshort Opport has no effect on the direction of NYSE Composite i.e., NYSE Composite and Crm Long/short go up and down completely randomly.

Pair Corralation between NYSE Composite and Crm Long/short

Assuming the 90 days trading horizon NYSE Composite is expected to generate 1.09 times more return on investment than Crm Long/short. However, NYSE Composite is 1.09 times more volatile than Crm Longshort Opport. It trades about 0.14 of its potential returns per unit of risk. Crm Longshort Opport is currently generating about 0.14 per unit of risk. If you would invest  1,627,444  in NYSE Composite on September 4, 2024 and sell it today you would earn a total of  393,878  from holding NYSE Composite or generate 24.2% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Strong
Accuracy	99.6%
Values	Daily Returns

NYSE Composite  vs.  Crm Longshort Opport

Pair Trading with NYSE Composite and Crm Long/short

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

The idea behind NYSE Composite and Crm Longshort Opport 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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.