Correlation Between Gmo Benchmark-free and Gmo Trust
Can any of the company-specific risk be diversified away by investing in both Gmo Benchmark-free and Gmo Trust 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 Gmo Benchmark-free and Gmo Trust into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gmo Benchmark Free Fund and Gmo Trust , you can compare the effects of market volatilities on Gmo Benchmark-free and Gmo Trust 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 Gmo Benchmark-free with a short position of Gmo Trust. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gmo Benchmark-free and Gmo Trust.
Diversification Opportunities for Gmo Benchmark-free and Gmo Trust
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Gmo and Gmo is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Gmo Benchmark Free Fund and Gmo Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gmo Trust and Gmo Benchmark-free 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 Gmo Benchmark Free Fund are associated (or correlated) with Gmo Trust. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gmo Trust has no effect on the direction of Gmo Benchmark-free i.e., Gmo Benchmark-free and Gmo Trust go up and down completely randomly.
Pair Corralation between Gmo Benchmark-free and Gmo Trust
Assuming the 90 days horizon Gmo Benchmark Free Fund is expected to under-perform the Gmo Trust. But the mutual fund apears to be less risky and, when comparing its historical volatility, Gmo Benchmark Free Fund is 2.08 times less risky than Gmo Trust. The mutual fund trades about -0.09 of its potential returns per unit of risk. The Gmo Trust is currently generating about 0.29 of returns per unit of risk over similar time horizon. If you would invest 2,353 in Gmo Trust on September 3, 2024 and sell it today you would earn a total of 149.00 from holding Gmo Trust or generate 6.33% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Gmo Benchmark Free Fund vs. Gmo Trust
Performance |
| Timeline |
| Gmo Benchmark Free |
| Gmo Trust |
Gmo Benchmark-free and Gmo Trust Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Gmo Benchmark-free and Gmo Trust
The main advantage of trading using opposite Gmo Benchmark-free and Gmo Trust positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gmo Benchmark-free position performs unexpectedly, Gmo Trust 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 Gmo Trust will offset losses from the drop in Gmo Trust's long position.| Gmo Benchmark-free vs. Ab Bond Inflation | Gmo Benchmark-free vs. Lord Abbett Inflation | Gmo Benchmark-free vs. Tiaa Cref Inflation Linked Bond | Gmo Benchmark-free vs. Arrow Managed Futures |
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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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