Correlation Between Catalyst/smh High and Federated Bond
Can any of the company-specific risk be diversified away by investing in both Catalyst/smh High and Federated Bond 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 Catalyst/smh High and Federated Bond into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Catalystsmh High Income and Federated Bond Fund, you can compare the effects of market volatilities on Catalyst/smh High and Federated Bond 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 Catalyst/smh High with a short position of Federated Bond. Check out your portfolio center. Please also check ongoing floating volatility patterns of Catalyst/smh High and Federated Bond.
Diversification Opportunities for Catalyst/smh High and Federated Bond
-0.09 | Correlation Coefficient |
Good diversification
The 3 months correlation between Catalyst/smh and Federated is -0.09. Overlapping area represents the amount of risk that can be diversified away by holding Catalystsmh High Income and Federated Bond Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated Bond and Catalyst/smh High 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 Catalystsmh High Income are associated (or correlated) with Federated Bond. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated Bond has no effect on the direction of Catalyst/smh High i.e., Catalyst/smh High and Federated Bond go up and down completely randomly.
Pair Corralation between Catalyst/smh High and Federated Bond
Assuming the 90 days horizon Catalystsmh High Income is expected to under-perform the Federated Bond. In addition to that, Catalyst/smh High is 1.28 times more volatile than Federated Bond Fund. It trades about -0.03 of its total potential returns per unit of risk. Federated Bond Fund is currently generating about 0.15 per unit of volatility. If you would invest 817.00 in Federated Bond Fund on December 23, 2024 and sell it today you would earn a total of 19.00 from holding Federated Bond Fund or generate 2.33% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Catalystsmh High Income vs. Federated Bond Fund
Performance |
Timeline |
Catalystsmh High Income |
Federated Bond |
Catalyst/smh High and Federated Bond Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Catalyst/smh High and Federated Bond
The main advantage of trading using opposite Catalyst/smh High and Federated Bond positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Catalyst/smh High position performs unexpectedly, Federated Bond 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 Federated Bond will offset losses from the drop in Federated Bond's long position.Catalyst/smh High vs. Transamerica Financial Life | Catalyst/smh High vs. Vanguard Financials Index | Catalyst/smh High vs. Rmb Mendon Financial | Catalyst/smh High vs. Davis Financial 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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