Correlation Between Fidelity Sai and Cambria Cannabis
Can any of the company-specific risk be diversified away by investing in both Fidelity Sai and Cambria Cannabis 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 Fidelity Sai and Cambria Cannabis into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fidelity Sai International and Cambria Cannabis ETF, you can compare the effects of market volatilities on Fidelity Sai and Cambria Cannabis 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 Fidelity Sai with a short position of Cambria Cannabis. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fidelity Sai and Cambria Cannabis.
Diversification Opportunities for Fidelity Sai and Cambria Cannabis
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Fidelity and Cambria is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Fidelity Sai International and Cambria Cannabis ETF in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cambria Cannabis ETF and Fidelity Sai 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 Fidelity Sai International are associated (or correlated) with Cambria Cannabis. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cambria Cannabis ETF has no effect on the direction of Fidelity Sai i.e., Fidelity Sai and Cambria Cannabis go up and down completely randomly.
Pair Corralation between Fidelity Sai and Cambria Cannabis
Assuming the 90 days horizon Fidelity Sai International is expected to generate 0.58 times more return on investment than Cambria Cannabis. However, Fidelity Sai International is 1.73 times less risky than Cambria Cannabis. It trades about 0.14 of its potential returns per unit of risk. Cambria Cannabis ETF is currently generating about -0.13 per unit of risk. If you would invest 812.00 in Fidelity Sai International on December 29, 2024 and sell it today you would earn a total of 56.00 from holding Fidelity Sai International or generate 6.9% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Fidelity Sai International vs. Cambria Cannabis ETF
Performance |
Timeline |
Fidelity Sai Interna |
Cambria Cannabis ETF |
Fidelity Sai and Cambria Cannabis Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fidelity Sai and Cambria Cannabis
The main advantage of trading using opposite Fidelity Sai and Cambria Cannabis positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fidelity Sai position performs unexpectedly, Cambria Cannabis 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 Cambria Cannabis will offset losses from the drop in Cambria Cannabis' long position.Fidelity Sai vs. Nomura Real Estate | Fidelity Sai vs. Fidelity Real Estate | Fidelity Sai vs. Invesco Real Estate | Fidelity Sai vs. Franklin 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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