Correlation Between NYSE Composite and Goldman Sachs
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Goldman Sachs 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 Goldman Sachs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Goldman Sachs Mid, you can compare the effects of market volatilities on NYSE Composite and Goldman Sachs 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 Goldman Sachs. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Goldman Sachs.
Diversification Opportunities for NYSE Composite and Goldman Sachs
0.95 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between NYSE and Goldman is 0.95. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Goldman Sachs Mid in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Goldman Sachs Mid 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 Goldman Sachs. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Goldman Sachs Mid has no effect on the direction of NYSE Composite i.e., NYSE Composite and Goldman Sachs go up and down completely randomly.
Pair Corralation between NYSE Composite and Goldman Sachs
Assuming the 90 days trading horizon NYSE Composite is expected to generate 1.63 times less return on investment than Goldman Sachs. But when comparing it to its historical volatility, NYSE Composite is 1.43 times less risky than Goldman Sachs. It trades about 0.24 of its potential returns per unit of risk. Goldman Sachs Mid is currently generating about 0.28 of returns per unit of risk over similar time horizon. If you would invest 3,708 in Goldman Sachs Mid on August 28, 2024 and sell it today you would earn a total of 209.00 from holding Goldman Sachs Mid or generate 5.64% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
NYSE Composite vs. Goldman Sachs Mid
Performance |
| Timeline |
NYSE Composite and Goldman Sachs Volatility Contrast
Predicted Return Density |
| Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Goldman Sachs Mid
Pair trading matchups for Goldman Sachs
Pair Trading with NYSE Composite and Goldman Sachs
The main advantage of trading using opposite NYSE Composite and Goldman Sachs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Goldman Sachs 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 Goldman Sachs will offset losses from the drop in Goldman Sachs' 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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