Correlation Between SPDR BOFA and Astoria Quality
Can any of the company-specific risk be diversified away by investing in both SPDR BOFA and Astoria Quality 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 SPDR BOFA and Astoria Quality into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SPDR BOFA MERRILL and Astoria Quality Kings, you can compare the effects of market volatilities on SPDR BOFA and Astoria Quality 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 SPDR BOFA with a short position of Astoria Quality. Check out your portfolio center. Please also check ongoing floating volatility patterns of SPDR BOFA and Astoria Quality.
Diversification Opportunities for SPDR BOFA and Astoria Quality
0.92 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between SPDR and Astoria is 0.92. Overlapping area represents the amount of risk that can be diversified away by holding SPDR BOFA MERRILL and Astoria Quality Kings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Astoria Quality Kings and SPDR BOFA 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 SPDR BOFA MERRILL are associated (or correlated) with Astoria Quality. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Astoria Quality Kings has no effect on the direction of SPDR BOFA i.e., SPDR BOFA and Astoria Quality go up and down completely randomly.
Pair Corralation between SPDR BOFA and Astoria Quality
Given the investment horizon of 90 days SPDR BOFA MERRILL is expected to generate 1.78 times more return on investment than Astoria Quality. However, SPDR BOFA is 1.78 times more volatile than Astoria Quality Kings. It trades about 0.11 of its potential returns per unit of risk. Astoria Quality Kings is currently generating about 0.14 per unit of risk. If you would invest 1,266 in SPDR BOFA MERRILL on August 27, 2024 and sell it today you would earn a total of 584.00 from holding SPDR BOFA MERRILL or generate 46.13% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
SPDR BOFA MERRILL vs. Astoria Quality Kings
Performance |
| Timeline |
| SPDR BOFA MERRILL |
| Astoria Quality Kings |
SPDR BOFA and Astoria Quality Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with SPDR BOFA and Astoria Quality
The main advantage of trading using opposite SPDR BOFA and Astoria Quality positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SPDR BOFA position performs unexpectedly, Astoria Quality 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 Astoria Quality will offset losses from the drop in Astoria Quality's long position.| SPDR BOFA vs. Invesco Dynamic Large | SPDR BOFA vs. Perella Weinberg Partners | SPDR BOFA vs. HUMANA INC | SPDR BOFA vs. Aquagold International |
| Astoria Quality vs. Cambria Micro And | Astoria Quality vs. Invesco Actively Managed | Astoria Quality vs. iShares Trust | Astoria Quality vs. EMCS |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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