Correlation Between NYSE Composite and First American
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and First American 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 First American into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and First American Funds, you can compare the effects of market volatilities on NYSE Composite and First American 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 First American. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and First American.
Diversification Opportunities for NYSE Composite and First American
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between NYSE and First is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and First American Funds in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on First American Funds 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 First American. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of First American Funds has no effect on the direction of NYSE Composite i.e., NYSE Composite and First American go up and down completely randomly.
Pair Corralation between NYSE Composite and First American
Assuming the 90 days trading horizon NYSE Composite is expected to generate 4.76 times more return on investment than First American. However, NYSE Composite is 4.76 times more volatile than First American Funds. It trades about 0.11 of its potential returns per unit of risk. First American Funds is currently generating about 0.14 per unit of risk. If you would invest 1,549,991 in NYSE Composite on September 1, 2024 and sell it today you would earn a total of 477,213 from holding NYSE Composite or generate 30.79% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
NYSE Composite vs. First American Funds
Performance |
Timeline |
NYSE Composite and First American Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
First American Funds
Pair trading matchups for First American
Pair Trading with NYSE Composite and First American
The main advantage of trading using opposite NYSE Composite and First American positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, First American 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 First American will offset losses from the drop in First American's long position.NYSE Composite vs. Acumen Pharmaceuticals | NYSE Composite vs. Mind Medicine | NYSE Composite vs. NL Industries | NYSE Composite vs. Ecovyst |
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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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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