Correlation Between Quantified Stf and Campbell Systematic
Can any of the company-specific risk be diversified away by investing in both Quantified Stf and Campbell Systematic 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 Quantified Stf and Campbell Systematic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Quantified Stf Fund and Campbell Systematic Macro, you can compare the effects of market volatilities on Quantified Stf and Campbell Systematic 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 Quantified Stf with a short position of Campbell Systematic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Quantified Stf and Campbell Systematic.
Diversification Opportunities for Quantified Stf and Campbell Systematic
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Quantified and Campbell is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Quantified Stf Fund and Campbell Systematic Macro in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Campbell Systematic Macro and Quantified Stf 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 Quantified Stf Fund are associated (or correlated) with Campbell Systematic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Campbell Systematic Macro has no effect on the direction of Quantified Stf i.e., Quantified Stf and Campbell Systematic go up and down completely randomly.
Pair Corralation between Quantified Stf and Campbell Systematic
Assuming the 90 days horizon Quantified Stf Fund is expected to generate 2.74 times more return on investment than Campbell Systematic. However, Quantified Stf is 2.74 times more volatile than Campbell Systematic Macro. It trades about 0.09 of its potential returns per unit of risk. Campbell Systematic Macro is currently generating about 0.04 per unit of risk. If you would invest 1,537 in Quantified Stf Fund on September 24, 2024 and sell it today you would earn a total of 403.00 from holding Quantified Stf Fund or generate 26.22% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Quantified Stf Fund vs. Campbell Systematic Macro
Performance |
Timeline |
Quantified Stf |
Campbell Systematic Macro |
Quantified Stf and Campbell Systematic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Quantified Stf and Campbell Systematic
The main advantage of trading using opposite Quantified Stf and Campbell Systematic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Quantified Stf position performs unexpectedly, Campbell Systematic 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 Campbell Systematic will offset losses from the drop in Campbell Systematic's long position.Quantified Stf vs. Columbia Income Opportunities | Quantified Stf vs. Ashmore Emerging Markets | Quantified Stf vs. Ashmore Emerging Markets | Quantified Stf vs. Blackrock Gov Bd |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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