Correlation Between Federated Kaufmann and Pace Large
Can any of the company-specific risk be diversified away by investing in both Federated Kaufmann and Pace Large 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 Federated Kaufmann and Pace Large into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Federated Kaufmann Large and Pace Large Growth, you can compare the effects of market volatilities on Federated Kaufmann and Pace Large 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 Federated Kaufmann with a short position of Pace Large. Check out your portfolio center. Please also check ongoing floating volatility patterns of Federated Kaufmann and Pace Large.
Diversification Opportunities for Federated Kaufmann and Pace Large
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Federated and Pace is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Federated Kaufmann Large and Pace Large Growth in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pace Large Growth and Federated Kaufmann 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 Federated Kaufmann Large are associated (or correlated) with Pace Large. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pace Large Growth has no effect on the direction of Federated Kaufmann i.e., Federated Kaufmann and Pace Large go up and down completely randomly.
Pair Corralation between Federated Kaufmann and Pace Large
Assuming the 90 days horizon Federated Kaufmann Large is expected to under-perform the Pace Large. In addition to that, Federated Kaufmann is 1.18 times more volatile than Pace Large Growth. It trades about -0.1 of its total potential returns per unit of risk. Pace Large Growth is currently generating about -0.1 per unit of volatility. If you would invest 1,548 in Pace Large Growth on December 30, 2024 and sell it today you would lose (120.00) from holding Pace Large Growth or give up 7.75% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Federated Kaufmann Large vs. Pace Large Growth
Performance |
Timeline |
Federated Kaufmann Large |
Pace Large Growth |
Federated Kaufmann and Pace Large Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Federated Kaufmann and Pace Large
The main advantage of trading using opposite Federated Kaufmann and Pace Large positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Federated Kaufmann position performs unexpectedly, Pace Large 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 Pace Large will offset losses from the drop in Pace Large's long position.Federated Kaufmann vs. Short Term Government Fund | Federated Kaufmann vs. Us Government Securities | Federated Kaufmann vs. Blackrock Government Bond | Federated Kaufmann vs. Virtus Seix Government |
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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 Portfolio File Import module to quickly import all of your third-party portfolios from your local drive in csv format.
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