Correlation Between NYSE Composite and Exchange Bank
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Exchange Bank 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 Exchange Bank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Exchange Bank, you can compare the effects of market volatilities on NYSE Composite and Exchange Bank 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 Exchange Bank. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Exchange Bank.
Diversification Opportunities for NYSE Composite and Exchange Bank
0.16 | Correlation Coefficient |
Average diversification
The 3 months correlation between NYSE and Exchange is 0.16. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Exchange Bank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Exchange Bank 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 Exchange Bank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Exchange Bank has no effect on the direction of NYSE Composite i.e., NYSE Composite and Exchange Bank go up and down completely randomly.
Pair Corralation between NYSE Composite and Exchange Bank
Assuming the 90 days trading horizon NYSE Composite is expected to generate 0.34 times more return on investment than Exchange Bank. However, NYSE Composite is 2.92 times less risky than Exchange Bank. It trades about -0.21 of its potential returns per unit of risk. Exchange Bank is currently generating about -0.14 per unit of risk. If you would invest 1,988,190 in NYSE Composite on October 11, 2024 and sell it today you would lose (64,116) from holding NYSE Composite or give up 3.22% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
NYSE Composite vs. Exchange Bank
Performance |
Timeline |
NYSE Composite and Exchange Bank Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Exchange Bank
Pair trading matchups for Exchange Bank
Pair Trading with NYSE Composite and Exchange Bank
The main advantage of trading using opposite NYSE Composite and Exchange Bank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Exchange Bank 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 Exchange Bank will offset losses from the drop in Exchange Bank's long position.NYSE Composite vs. Femasys | NYSE Composite vs. Teradyne | NYSE Composite vs. Toro Co | NYSE Composite vs. Space Communication |
Exchange Bank vs. Foreign Trade Bank | Exchange Bank vs. Comerica | Exchange Bank vs. Delhi Bank Corp | Exchange Bank vs. CCSB Financial Corp |
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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.
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