Correlation Between NYSE Composite and Galenfeha
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Galenfeha 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 Galenfeha into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Galenfeha, you can compare the effects of market volatilities on NYSE Composite and Galenfeha 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 Galenfeha. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Galenfeha.
Diversification Opportunities for NYSE Composite and Galenfeha
-0.19 | Correlation Coefficient |
Good diversification
The 3 months correlation between NYSE and Galenfeha is -0.19. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Galenfeha in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Galenfeha 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 Galenfeha. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Galenfeha has no effect on the direction of NYSE Composite i.e., NYSE Composite and Galenfeha go up and down completely randomly.
Pair Corralation between NYSE Composite and Galenfeha
Assuming the 90 days trading horizon NYSE Composite is expected to under-perform the Galenfeha. But the index apears to be less risky and, when comparing its historical volatility, NYSE Composite is 317.58 times less risky than Galenfeha. The index trades about -0.37 of its potential returns per unit of risk. The Galenfeha is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 2.80 in Galenfeha on September 25, 2024 and sell it today you would earn a total of 1,047 from holding Galenfeha or generate 37400.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.24% |
Values | Daily Returns |
NYSE Composite vs. Galenfeha
Performance |
Timeline |
NYSE Composite and Galenfeha Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Galenfeha
Pair trading matchups for Galenfeha
Pair Trading with NYSE Composite and Galenfeha
The main advantage of trading using opposite NYSE Composite and Galenfeha positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Galenfeha 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 Galenfeha will offset losses from the drop in Galenfeha's long position.NYSE Composite vs. Cincinnati Financial | NYSE Composite vs. Integral Ad Science | NYSE Composite vs. Stagwell | NYSE Composite vs. Atlantic American |
Galenfeha vs. SMG Industries | Galenfeha vs. NXT Energy Solutions | Galenfeha vs. Dawson Geophysical | Galenfeha vs. Calfrac Well Services |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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