Correlation Between Goldman Sachs and Oklahoma Municipal
Can any of the company-specific risk be diversified away by investing in both Goldman Sachs and Oklahoma Municipal 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 Oklahoma Municipal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Goldman Sachs Inflation and Oklahoma Municipal Fund, you can compare the effects of market volatilities on Goldman Sachs and Oklahoma Municipal 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 Oklahoma Municipal. Check out your portfolio center. Please also check ongoing floating volatility patterns of Goldman Sachs and Oklahoma Municipal.
Diversification Opportunities for Goldman Sachs and Oklahoma Municipal
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between GOLDMAN and OKLAHOMA is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Goldman Sachs Inflation and Oklahoma Municipal Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Oklahoma Municipal 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 Inflation are associated (or correlated) with Oklahoma Municipal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Oklahoma Municipal has no effect on the direction of Goldman Sachs i.e., Goldman Sachs and Oklahoma Municipal go up and down completely randomly.
Pair Corralation between Goldman Sachs and Oklahoma Municipal
Assuming the 90 days horizon Goldman Sachs Inflation is expected to generate 1.06 times more return on investment than Oklahoma Municipal. However, Goldman Sachs is 1.06 times more volatile than Oklahoma Municipal Fund. It trades about 0.22 of its potential returns per unit of risk. Oklahoma Municipal Fund is currently generating about 0.03 per unit of risk. If you would invest 921.00 in Goldman Sachs Inflation on December 23, 2024 and sell it today you would earn a total of 32.00 from holding Goldman Sachs Inflation or generate 3.47% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Goldman Sachs Inflation vs. Oklahoma Municipal Fund
Performance |
Timeline |
Goldman Sachs Inflation |
Oklahoma Municipal |
Goldman Sachs and Oklahoma Municipal Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Goldman Sachs and Oklahoma Municipal
The main advantage of trading using opposite Goldman Sachs and Oklahoma Municipal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Goldman Sachs position performs unexpectedly, Oklahoma Municipal 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 Oklahoma Municipal will offset losses from the drop in Oklahoma Municipal's long position.Goldman Sachs vs. Hewitt Money Market | Goldman Sachs vs. Money Market Obligations | Goldman Sachs vs. Rbc Money Market | Goldman Sachs vs. John Hancock Money |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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