Correlation Between NYSE Composite and CPI Aerostructures
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and CPI Aerostructures 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 CPI Aerostructures into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and CPI Aerostructures, you can compare the effects of market volatilities on NYSE Composite and CPI Aerostructures 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 CPI Aerostructures. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and CPI Aerostructures.
Diversification Opportunities for NYSE Composite and CPI Aerostructures
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between NYSE and CPI is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and CPI Aerostructures in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CPI Aerostructures 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 CPI Aerostructures. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CPI Aerostructures has no effect on the direction of NYSE Composite i.e., NYSE Composite and CPI Aerostructures go up and down completely randomly.
Pair Corralation between NYSE Composite and CPI Aerostructures
Assuming the 90 days trading horizon NYSE Composite is expected to generate 0.23 times more return on investment than CPI Aerostructures. However, NYSE Composite is 4.37 times less risky than CPI Aerostructures. It trades about 0.08 of its potential returns per unit of risk. CPI Aerostructures is currently generating about 0.02 per unit of risk. If you would invest 1,532,846 in NYSE Composite on August 27, 2024 and sell it today you would earn a total of 479,499 from holding NYSE Composite or generate 31.28% 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. CPI Aerostructures
Performance |
Timeline |
NYSE Composite and CPI Aerostructures Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
CPI Aerostructures
Pair trading matchups for CPI Aerostructures
Pair Trading with NYSE Composite and CPI Aerostructures
The main advantage of trading using opposite NYSE Composite and CPI Aerostructures positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, CPI Aerostructures 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 CPI Aerostructures will offset losses from the drop in CPI Aerostructures' long position.NYSE Composite vs. Hooker Furniture | NYSE Composite vs. Hudson Pacific Properties | NYSE Composite vs. Canlan Ice Sports | NYSE Composite vs. Boston Properties |
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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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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