Correlation Between Growth Strategy and Segall Bryant
Can any of the company-specific risk be diversified away by investing in both Growth Strategy 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 Growth Strategy and Segall Bryant into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Growth Strategy Fund and Segall Bryant Hamill, you can compare the effects of market volatilities on Growth Strategy 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 Growth Strategy with a short position of Segall Bryant. Check out your portfolio center. Please also check ongoing floating volatility patterns of Growth Strategy and Segall Bryant.
Diversification Opportunities for Growth Strategy and Segall Bryant
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between GROWTH and Segall is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Growth Strategy Fund 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 Growth Strategy 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 Growth Strategy Fund 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 Growth Strategy i.e., Growth Strategy and Segall Bryant go up and down completely randomly.
Pair Corralation between Growth Strategy and Segall Bryant
Assuming the 90 days horizon Growth Strategy is expected to generate 2.55 times less return on investment than Segall Bryant. But when comparing it to its historical volatility, Growth Strategy Fund is 2.04 times less risky than Segall Bryant. It trades about 0.14 of its potential returns per unit of risk. Segall Bryant Hamill is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 1,279 in Segall Bryant Hamill on September 4, 2024 and sell it today you would earn a total of 156.00 from holding Segall Bryant Hamill or generate 12.2% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Growth Strategy Fund vs. Segall Bryant Hamill
Performance |
Timeline |
Growth Strategy |
Segall Bryant Hamill |
Growth Strategy and Segall Bryant Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Growth Strategy and Segall Bryant
The main advantage of trading using opposite Growth Strategy and Segall Bryant positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Growth Strategy 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.Growth Strategy vs. International Developed Markets | Growth Strategy vs. Global Real Estate | Growth Strategy vs. Global Real Estate | Growth Strategy vs. Global Real Estate |
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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 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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