Correlation Between Icon Information and Goldman Sachs
Can any of the company-specific risk be diversified away by investing in both Icon Information 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 Icon Information and Goldman Sachs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Icon Information Technology and Goldman Sachs High, you can compare the effects of market volatilities on Icon Information 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 Icon Information with a short position of Goldman Sachs. Check out your portfolio center. Please also check ongoing floating volatility patterns of Icon Information and Goldman Sachs.
Diversification Opportunities for Icon Information and Goldman Sachs
-0.06 | Correlation Coefficient |
Good diversification
The 3 months correlation between Icon and Goldman is -0.06. Overlapping area represents the amount of risk that can be diversified away by holding Icon Information Technology and Goldman Sachs High in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Goldman Sachs High and Icon Information 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 Icon Information Technology 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 High has no effect on the direction of Icon Information i.e., Icon Information and Goldman Sachs go up and down completely randomly.
Pair Corralation between Icon Information and Goldman Sachs
Assuming the 90 days horizon Icon Information Technology is expected to generate 3.08 times more return on investment than Goldman Sachs. However, Icon Information is 3.08 times more volatile than Goldman Sachs High. It trades about 0.02 of its potential returns per unit of risk. Goldman Sachs High is currently generating about -0.02 per unit of risk. If you would invest 1,693 in Icon Information Technology on August 30, 2024 and sell it today you would earn a total of 13.00 from holding Icon Information Technology or generate 0.77% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Icon Information Technology vs. Goldman Sachs High
Performance |
Timeline |
Icon Information Tec |
Goldman Sachs High |
Icon Information and Goldman Sachs Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Icon Information and Goldman Sachs
The main advantage of trading using opposite Icon Information and Goldman Sachs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Icon Information 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.Icon Information vs. Federated Short Intermediate Duration | Icon Information vs. Mirova Global Green | Icon Information vs. Ambrus Core Bond | Icon Information vs. Versatile Bond Portfolio |
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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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