Correlation Between NYSE Composite and Western Asset
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Western Asset 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 Western Asset into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Western Asset Pennsylvania, you can compare the effects of market volatilities on NYSE Composite and Western Asset 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 Western Asset. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Western Asset.
Diversification Opportunities for NYSE Composite and Western Asset
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between NYSE and Western is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Western Asset Pennsylvania in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Western Asset Pennsy 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 Western Asset. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Western Asset Pennsy has no effect on the direction of NYSE Composite i.e., NYSE Composite and Western Asset go up and down completely randomly.
Pair Corralation between NYSE Composite and Western Asset
Assuming the 90 days trading horizon NYSE Composite is expected to generate 3.18 times more return on investment than Western Asset. However, NYSE Composite is 3.18 times more volatile than Western Asset Pennsylvania. It trades about 0.14 of its potential returns per unit of risk. Western Asset Pennsylvania is currently generating about 0.15 per unit of risk. If you would invest 1,800,696 in NYSE Composite on September 1, 2024 and sell it today you would earn a total of 226,508 from holding NYSE Composite or generate 12.58% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 99.21% |
| Values | Daily Returns |
NYSE Composite vs. Western Asset Pennsylvania
Performance |
| Timeline |
NYSE Composite and Western Asset Volatility Contrast
Predicted Return Density |
| Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Western Asset Pennsylvania
Pair trading matchups for Western Asset
Pair Trading with NYSE Composite and Western Asset
The main advantage of trading using opposite NYSE Composite and Western Asset positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Western Asset 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 Western Asset will offset losses from the drop in Western Asset'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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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