Correlation Between Pure Storage and Goldman Sachs
Can any of the company-specific risk be diversified away by investing in both Pure Storage 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 Pure Storage and Goldman Sachs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pure Storage and Goldman Sachs Group, you can compare the effects of market volatilities on Pure Storage 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 Pure Storage with a short position of Goldman Sachs. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pure Storage and Goldman Sachs.
Diversification Opportunities for Pure Storage and Goldman Sachs
0.35 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Pure and Goldman is 0.35. Overlapping area represents the amount of risk that can be diversified away by holding Pure Storage and Goldman Sachs Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Goldman Sachs Group and Pure Storage 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 Pure Storage 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 Group has no effect on the direction of Pure Storage i.e., Pure Storage and Goldman Sachs go up and down completely randomly.
Pair Corralation between Pure Storage and Goldman Sachs
Given the investment horizon of 90 days Pure Storage is expected to generate 2.11 times more return on investment than Goldman Sachs. However, Pure Storage is 2.11 times more volatile than Goldman Sachs Group. It trades about 0.08 of its potential returns per unit of risk. Goldman Sachs Group is currently generating about 0.13 per unit of risk. If you would invest 3,616 in Pure Storage on October 11, 2024 and sell it today you would earn a total of 2,810 from holding Pure Storage or generate 77.71% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Pure Storage vs. Goldman Sachs Group
Performance |
Timeline |
Pure Storage |
Goldman Sachs Group |
Pure Storage and Goldman Sachs Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pure Storage and Goldman Sachs
The main advantage of trading using opposite Pure Storage and Goldman Sachs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pure Storage 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.Pure Storage vs. Seagate Technology PLC | Pure Storage vs. HP Inc | Pure Storage vs. Dell Technologies | Pure Storage vs. Western Digital |
Goldman Sachs vs. Morgan Stanley | Goldman Sachs vs. JPMorgan Chase Co | Goldman Sachs vs. Wells Fargo | Goldman Sachs vs. Citigroup |
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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