Correlation Between Dodge Cox and Segall Bryant
Can any of the company-specific risk be diversified away by investing in both Dodge Cox and Segall Bryant 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 Dodge Cox and Segall Bryant into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dodge Cox Emerging and Segall Bryant Hamill, you can compare the effects of market volatilities on Dodge Cox and Segall Bryant 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 Dodge Cox with a short position of Segall Bryant. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dodge Cox and Segall Bryant.
Diversification Opportunities for Dodge Cox and Segall Bryant
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Dodge and Segall is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding Dodge Cox Emerging and Segall Bryant Hamill in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Segall Bryant Hamill and Dodge Cox 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 Dodge Cox Emerging are associated (or correlated) with Segall Bryant. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Segall Bryant Hamill has no effect on the direction of Dodge Cox i.e., Dodge Cox and Segall Bryant go up and down completely randomly.
Pair Corralation between Dodge Cox and Segall Bryant
Assuming the 90 days horizon Dodge Cox Emerging is expected to generate 9.14 times more return on investment than Segall Bryant. However, Dodge Cox is 9.14 times more volatile than Segall Bryant Hamill. It trades about 0.12 of its potential returns per unit of risk. Segall Bryant Hamill is currently generating about 0.15 per unit of risk. If you would invest 871.00 in Dodge Cox Emerging on December 28, 2024 and sell it today you would earn a total of 55.00 from holding Dodge Cox Emerging or generate 6.31% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Dodge Cox Emerging vs. Segall Bryant Hamill
Performance |
Timeline |
Dodge Cox Emerging |
Segall Bryant Hamill |
Dodge Cox and Segall Bryant Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dodge Cox and Segall Bryant
The main advantage of trading using opposite Dodge Cox and Segall Bryant positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dodge Cox position performs unexpectedly, Segall Bryant 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 Segall Bryant will offset losses from the drop in Segall Bryant's long position.Dodge Cox vs. Siit High Yield | Dodge Cox vs. Artisan High Income | Dodge Cox vs. Gmo High Yield | Dodge Cox vs. Ab Bond Inflation |
Segall Bryant vs. Segall Bryant Hamill | Segall Bryant vs. Segall Bryant Hamill | Segall Bryant vs. Segall Bryant Hamill | Segall Bryant vs. Segall Bryant Hamill |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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