Correlation Between Goldman Sachs and Dreyfus Research
Can any of the company-specific risk be diversified away by investing in both Goldman Sachs and Dreyfus Research 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 Goldman Sachs and Dreyfus Research into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Goldman Sachs Clean and Dreyfus Research Growth, you can compare the effects of market volatilities on Goldman Sachs and Dreyfus Research 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 Goldman Sachs with a short position of Dreyfus Research. Check out your portfolio center. Please also check ongoing floating volatility patterns of Goldman Sachs and Dreyfus Research.
Diversification Opportunities for Goldman Sachs and Dreyfus Research
-0.46 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Goldman and Dreyfus is -0.46. Overlapping area represents the amount of risk that can be diversified away by holding Goldman Sachs Clean and Dreyfus Research Growth in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dreyfus Research Growth and Goldman Sachs 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 Goldman Sachs Clean are associated (or correlated) with Dreyfus Research. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dreyfus Research Growth has no effect on the direction of Goldman Sachs i.e., Goldman Sachs and Dreyfus Research go up and down completely randomly.
Pair Corralation between Goldman Sachs and Dreyfus Research
Assuming the 90 days horizon Goldman Sachs Clean is expected to generate 0.83 times more return on investment than Dreyfus Research. However, Goldman Sachs Clean is 1.21 times less risky than Dreyfus Research. It trades about -0.19 of its potential returns per unit of risk. Dreyfus Research Growth is currently generating about -0.16 per unit of risk. If you would invest 832.00 in Goldman Sachs Clean on October 17, 2024 and sell it today you would lose (35.00) from holding Goldman Sachs Clean or give up 4.21% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Goldman Sachs Clean vs. Dreyfus Research Growth
Performance |
Timeline |
Goldman Sachs Clean |
Dreyfus Research Growth |
Goldman Sachs and Dreyfus Research Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Goldman Sachs and Dreyfus Research
The main advantage of trading using opposite Goldman Sachs and Dreyfus Research positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Goldman Sachs position performs unexpectedly, Dreyfus Research 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 Dreyfus Research will offset losses from the drop in Dreyfus Research's long position.Goldman Sachs vs. Quantitative Longshort Equity | Goldman Sachs vs. Ab Select Equity | Goldman Sachs vs. Calvert International Equity | Goldman Sachs vs. Enhanced Fixed Income |
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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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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