Correlation Between Davis Financial and Mainstay High
Can any of the company-specific risk be diversified away by investing in both Davis Financial and Mainstay High 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 Davis Financial and Mainstay High into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Davis Financial Fund and Mainstay High Yield, you can compare the effects of market volatilities on Davis Financial and Mainstay High 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 Davis Financial with a short position of Mainstay High. Check out your portfolio center. Please also check ongoing floating volatility patterns of Davis Financial and Mainstay High.
Diversification Opportunities for Davis Financial and Mainstay High
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Davis and Mainstay is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Davis Financial Fund and Mainstay High Yield in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mainstay High Yield and Davis Financial 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 Davis Financial Fund are associated (or correlated) with Mainstay High. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mainstay High Yield has no effect on the direction of Davis Financial i.e., Davis Financial and Mainstay High go up and down completely randomly.
Pair Corralation between Davis Financial and Mainstay High
Assuming the 90 days horizon Davis Financial Fund is expected to generate 6.6 times more return on investment than Mainstay High. However, Davis Financial is 6.6 times more volatile than Mainstay High Yield. It trades about 0.05 of its potential returns per unit of risk. Mainstay High Yield is currently generating about 0.0 per unit of risk. If you would invest 6,218 in Davis Financial Fund on October 8, 2024 and sell it today you would earn a total of 209.00 from holding Davis Financial Fund or generate 3.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Davis Financial Fund vs. Mainstay High Yield
Performance |
Timeline |
Davis Financial |
Mainstay High Yield |
Davis Financial and Mainstay High Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Davis Financial and Mainstay High
The main advantage of trading using opposite Davis Financial and Mainstay High positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Davis Financial position performs unexpectedly, Mainstay High 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 Mainstay High will offset losses from the drop in Mainstay High's long position.Davis Financial vs. Blackrock Science Technology | Davis Financial vs. Pgim Jennison Technology | Davis Financial vs. Towpath Technology | Davis Financial vs. Invesco Technology Fund |
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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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