Correlation Between Segall Bryant and First Eagle
Can any of the company-specific risk be diversified away by investing in both Segall Bryant and First Eagle 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 Segall Bryant and First Eagle into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Segall Bryant Hamill and First Eagle Small, you can compare the effects of market volatilities on Segall Bryant and First Eagle 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 Segall Bryant with a short position of First Eagle. Check out your portfolio center. Please also check ongoing floating volatility patterns of Segall Bryant and First Eagle.
Diversification Opportunities for Segall Bryant and First Eagle
0.95 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Segall and First is 0.95. Overlapping area represents the amount of risk that can be diversified away by holding Segall Bryant Hamill and First Eagle Small in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on First Eagle Small and Segall Bryant 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 Segall Bryant Hamill are associated (or correlated) with First Eagle. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of First Eagle Small has no effect on the direction of Segall Bryant i.e., Segall Bryant and First Eagle go up and down completely randomly.
Pair Corralation between Segall Bryant and First Eagle
Assuming the 90 days horizon Segall Bryant is expected to generate 1.22 times less return on investment than First Eagle. But when comparing it to its historical volatility, Segall Bryant Hamill is 1.73 times less risky than First Eagle. It trades about 0.21 of its potential returns per unit of risk. First Eagle Small is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 974.00 in First Eagle Small on May 19, 2025 and sell it today you would earn a total of 109.00 from holding First Eagle Small or generate 11.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Segall Bryant Hamill vs. First Eagle Small
Performance |
Timeline |
Segall Bryant Hamill |
First Eagle Small |
Segall Bryant and First Eagle Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Segall Bryant and First Eagle
The main advantage of trading using opposite Segall Bryant and First Eagle positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Segall Bryant position performs unexpectedly, First Eagle 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 First Eagle will offset losses from the drop in First Eagle's long position.Segall Bryant vs. Alphacentric Hedged Market | Segall Bryant vs. Blackrock Emerging Markets | Segall Bryant vs. Ashmore Emerging Markets | Segall Bryant vs. Rbc Emerging Markets |
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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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