Correlation Between Alpha Architect and Cambria Trinity
Can any of the company-specific risk be diversified away by investing in both Alpha Architect and Cambria Trinity 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 Alpha Architect and Cambria Trinity into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alpha Architect Gdsdn and Cambria Trinity ETF, you can compare the effects of market volatilities on Alpha Architect and Cambria Trinity 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 Alpha Architect with a short position of Cambria Trinity. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alpha Architect and Cambria Trinity.
Diversification Opportunities for Alpha Architect and Cambria Trinity
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Alpha and Cambria is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding Alpha Architect Gdsdn and Cambria Trinity ETF in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cambria Trinity ETF and Alpha Architect 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 Alpha Architect Gdsdn are associated (or correlated) with Cambria Trinity. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cambria Trinity ETF has no effect on the direction of Alpha Architect i.e., Alpha Architect and Cambria Trinity go up and down completely randomly.
Pair Corralation between Alpha Architect and Cambria Trinity
Given the investment horizon of 90 days Alpha Architect Gdsdn is expected to generate 1.18 times more return on investment than Cambria Trinity. However, Alpha Architect is 1.18 times more volatile than Cambria Trinity ETF. It trades about -0.04 of its potential returns per unit of risk. Cambria Trinity ETF is currently generating about -0.25 per unit of risk. If you would invest 3,227 in Alpha Architect Gdsdn on October 8, 2024 and sell it today you would lose (18.00) from holding Alpha Architect Gdsdn or give up 0.56% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Alpha Architect Gdsdn vs. Cambria Trinity ETF
Performance |
Timeline |
Alpha Architect Gdsdn |
Cambria Trinity ETF |
Alpha Architect and Cambria Trinity Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alpha Architect and Cambria Trinity
The main advantage of trading using opposite Alpha Architect and Cambria Trinity positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alpha Architect position performs unexpectedly, Cambria Trinity 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 Trinity will offset losses from the drop in Cambria Trinity's long position.Alpha Architect vs. Janus Henderson Mortgage Backed | Alpha Architect vs. LeaderSharesTM AlphaFactor Core | Alpha Architect vs. ClearShares Ultra Short Maturity | Alpha Architect vs. Hartford Short Duration |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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