Correlation Between Ab Impact and Commodities Strategy
Can any of the company-specific risk be diversified away by investing in both Ab Impact and Commodities Strategy 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 Ab Impact and Commodities Strategy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ab Impact Municipal and Commodities Strategy Fund, you can compare the effects of market volatilities on Ab Impact and Commodities Strategy 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 Ab Impact with a short position of Commodities Strategy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ab Impact and Commodities Strategy.
Diversification Opportunities for Ab Impact and Commodities Strategy
0.15 | Correlation Coefficient |
Average diversification
The 3 months correlation between ABIMX and Commodities is 0.15. Overlapping area represents the amount of risk that can be diversified away by holding Ab Impact Municipal and Commodities Strategy Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Commodities Strategy and Ab Impact 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 Ab Impact Municipal are associated (or correlated) with Commodities Strategy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Commodities Strategy has no effect on the direction of Ab Impact i.e., Ab Impact and Commodities Strategy go up and down completely randomly.
Pair Corralation between Ab Impact and Commodities Strategy
Assuming the 90 days horizon Ab Impact Municipal is expected to under-perform the Commodities Strategy. But the mutual fund apears to be less risky and, when comparing its historical volatility, Ab Impact Municipal is 2.47 times less risky than Commodities Strategy. The mutual fund trades about -0.06 of its potential returns per unit of risk. The Commodities Strategy Fund is currently generating about -0.01 of returns per unit of risk over similar time horizon. If you would invest 1,638 in Commodities Strategy Fund on September 25, 2024 and sell it today you would lose (8.00) from holding Commodities Strategy Fund or give up 0.49% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Ab Impact Municipal vs. Commodities Strategy Fund
Performance |
Timeline |
Ab Impact Municipal |
Commodities Strategy |
Ab Impact and Commodities Strategy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ab Impact and Commodities Strategy
The main advantage of trading using opposite Ab Impact and Commodities Strategy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ab Impact position performs unexpectedly, Commodities Strategy 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 Commodities Strategy will offset losses from the drop in Commodities Strategy's long position.Ab Impact vs. Towpath Technology | Ab Impact vs. Pgim Jennison Technology | Ab Impact vs. Invesco Technology Fund | Ab Impact vs. Goldman Sachs Technology |
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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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