Correlation Between NYSE Composite and Snam SpA
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Snam SpA 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 Snam SpA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Snam SpA ADR, you can compare the effects of market volatilities on NYSE Composite and Snam SpA 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 Snam SpA. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Snam SpA.
Diversification Opportunities for NYSE Composite and Snam SpA
-0.37 | Correlation Coefficient |
Very good diversification
The 3 months correlation between NYSE and Snam is -0.37. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Snam SpA ADR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Snam SpA ADR 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 Snam SpA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Snam SpA ADR has no effect on the direction of NYSE Composite i.e., NYSE Composite and Snam SpA go up and down completely randomly.
Pair Corralation between NYSE Composite and Snam SpA
Assuming the 90 days trading horizon NYSE Composite is expected to generate 0.56 times more return on investment than Snam SpA. However, NYSE Composite is 1.77 times less risky than Snam SpA. It trades about 0.07 of its potential returns per unit of risk. Snam SpA ADR is currently generating about 0.01 per unit of risk. If you would invest 1,518,431 in NYSE Composite on September 20, 2024 and sell it today you would earn a total of 380,265 from holding NYSE Composite or generate 25.04% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
NYSE Composite vs. Snam SpA ADR
Performance |
| Timeline |
NYSE Composite and Snam SpA Volatility Contrast
Predicted Return Density |
| Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Snam SpA ADR
Pair trading matchups for Snam SpA
Pair Trading with NYSE Composite and Snam SpA
The main advantage of trading using opposite NYSE Composite and Snam SpA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Snam SpA 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 Snam SpA will offset losses from the drop in Snam SpA's long position.| NYSE Composite vs. Relx PLC ADR | NYSE Composite vs. Century Aluminum | NYSE Composite vs. Udemy Inc | NYSE Composite vs. Blue Moon Metals |
| Snam SpA vs. Northwest Natural Gas | Snam SpA vs. NewJersey Resources | Snam SpA vs. Atmos Energy | Snam SpA vs. Suburban Propane Partners |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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